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Timo Teräsvirta
(Timo Terasvirta)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Blog mentions

As found by EconAcademics.org, the blog aggregator for Economics research:
  1. van Dijk, D.J.C. & Terasvirta, T. & Franses, Ph.H.B.F., 2000. "Smooth transition autoregressive models - A survey of recent developments," Econometric Institute Research Papers EI 2000-23/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Mentioned in:

    1. Guest Contribution: "An assessment of the US jobless recovery through a non-linear Okun’s law"
      by Menzie Chinn in Econbrowser on 2012-12-18 04:05:06

Wikipedia or ReplicationWiki mentions

(Only mentions on Wikipedia that link back to a page on a RePEc service)
  1. Skalin, Joakim & Terasvirta, Timo, 1999. "Another Look at Swedish Business Cycles, 1861-1988," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(4), pages 359-378, July-Aug..

    Mentioned in:

    1. Another look at Swedish business cycles, 1861-1988 (Journal of Applied Econometrics 1999) in ReplicationWiki ()
  2. Lutkepohl, Helmut & Terasvirta, Timo & Wolters, Jurgen, 1999. "Investigating Stability and Linearity of a German M1 Money Demand Function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 511-525, Sept.-Oct.

    Mentioned in:

    1. Investigating stability and linearity of a German M1 money demand function (Journal of Applied Econometrics 1999) in ReplicationWiki ()
  3. Rahiala, Markku & Terasvirta, Timo, 1988. "Formation of Firms' Production Decisions in Finnish Manufacturing Industries," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 3(2), pages 125-137, April.

    Mentioned in:

    1. Formation of firms' production decisions in finnish manufacturing industries (Journal of Applied Econometrics 1988) in ReplicationWiki ()
  4. Tobias Rydén & Timo Teräsvirta & Stefan Åsbrink, 1998. "Stylized facts of daily return series and the hidden Markov model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(3), pages 217-244.

    Mentioned in:

    1. Stylized facts of daily return series and the hidden Markov model (Journal of Applied Econometrics 1998) in ReplicationWiki ()

Working papers

  1. Jian Kang & Johan Stax Jakobsen & Annastiina Silvennoinen & Timo Teräsvirta & Glen Wade, 2022. "A parsimonious test of constancy of a positive definite correlation matrix in a multivariate time-varying GARCH model," CREATES Research Papers 2022-01, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2023. "Building Multivariate Time-Varying Smooth Transition Correlation GARCH Models, with an Application to the Four Largest Australian Banks," Econometrics, MDPI, vol. 11(1), pages 1-37, February.

  2. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2021. "Four Australian Banks and the Multivariate Time-Varying Smooth Transition Correlation GARCH model," CREATES Research Papers 2021-13, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    2. Jian Kang & Johan Stax Jakobsen & Annastiina Silvennoinen & Timo Teräsvirta & Glen Wade, 2022. "A parsimonious test of constancy of a positive definite correlation matrix in a multivariate time-varying GARCH model," CREATES Research Papers 2022-01, Department of Economics and Business Economics, Aarhus University.

  3. Changli He & Jian Kang & Timo Teräsvirta & Shuhua Zhang, 2019. "Long monthly temperature series and the Vector Seasonal Shifting Mean and Covariance Autoregressive model," CREATES Research Papers 2019-18, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Changli He & Jian Kang & Timo Teräsvirta & Shuhua Zhang, 2019. "Comparing long monthly Chinese and selected European temperature series using the Vector Seasonal Shifting Mean and Covariance Autoregressive model," CREATES Research Papers 2019-19, Department of Economics and Business Economics, Aarhus University.

  4. Changli He & Jian Kang & Timo Teräsvirta & Shuhua Zhang, 2019. "Comparing long monthly Chinese and selected European temperature series using the Vector Seasonal Shifting Mean and Covariance Autoregressive model," CREATES Research Papers 2019-19, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. He, Changli & Kang, Jian & Silvennoinen, Annastiina & Teräsvirta, Timo, 2023. "Long monthly European temperature series and the North Atlantic Oscillation," Energy Economics, Elsevier, vol. 126(C).
    2. González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir, 2023. "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS 37968, Universidad Carlos III de Madrid. Departamento de Estadística.
    3. Changli He & Jian Kang & Timo Teräsvirta & Shuhua Zhang, 2019. "Comparing long monthly Chinese and selected European temperature series using the Vector Seasonal Shifting Mean and Covariance Autoregressive model," CREATES Research Papers 2019-19, Department of Economics and Business Economics, Aarhus University.

  5. Dakyung Seong & Jin Seo Cho & Timo Teräsvirta, 2019. "Comprehensive Testing of Linearity against the Smooth Transition Autoregressive Model," CREATES Research Papers 2019-17, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Jin Seo Cho & Matthew Greenwood-Nimmo & Yongcheol Shin, 2021. "Recent Developments of the Autoregressive Distributed Lag Modelling Framework," Working papers 2021rwp-186, Yonsei University, Yonsei Economics Research Institute.

  6. Changli He & Jian Kang & Timo Teräsvirta & Shuhua Zhang, 2018. "The Shifting Seasonal Mean Autoregressive Model and Seasonality in the Central England Monthly Temperature Series, 1772-2016," CREATES Research Papers 2018-15, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. He, Changli & Kang, Jian & Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Long monthly temperature series and the Vector Seasonal Shifting Mean and Covariance Autoregressive model," Journal of Econometrics, Elsevier, vol. 239(1).
    2. He, Changli & Kang, Jian & Silvennoinen, Annastiina & Teräsvirta, Timo, 2023. "Long monthly European temperature series and the North Atlantic Oscillation," Energy Economics, Elsevier, vol. 126(C).
    3. Tommaso Proietti & Diego J. Pedregal, 2021. "Seasonality in High Frequency Time Series," CEIS Research Paper 508, Tor Vergata University, CEIS, revised 11 Mar 2021.
    4. Changli He & Jian Kang & Timo Teräsvirta & Shuhua Zhang, 2019. "Comparing long monthly Chinese and selected European temperature series using the Vector Seasonal Shifting Mean and Covariance Autoregressive model," CREATES Research Papers 2019-19, Department of Economics and Business Economics, Aarhus University.
    5. Webel, Karsten, 2022. "A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series," Discussion Papers 31/2022, Deutsche Bundesbank.

  7. Stan Hurn & Nicholas Johnson & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Transition from the Taylor rule to the zero lower bound," CREATES Research Papers 2018-31, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Vito Polito, 2020. "Nonlinear Business Cycle and Optimal Policy: A VSTAR Perspective," CESifo Working Paper Series 8060, CESifo.

  8. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Conrad, Christian & Schienle, Melanie, 2019. "Testing for an omitted multiplicative long-term component in GARCH models," Working Paper Series in Economics 121, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    2. Feng, Yuanhua & Härdle, Wolfgang Karl, 2020. "A data-driven P-spline smoother and the P-Spline-GARCH models," IRTG 1792 Discussion Papers 2020-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    3. Wu, Xinyu & Xie, Haibin, 2021. "A realized EGARCH-MIDAS model with higher moments," Finance Research Letters, Elsevier, vol. 38(C).

  9. Andrés González & Timo Teräsvirta & Dick van Dijk & Yukai Yang, 2017. "Panel Smooth Transition Regression Models," CREATES Research Papers 2017-36, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. António Afonso & Michael G. Arghyrou & María Dolores Gadea & Alexandros Kontonikas, 2017. ""Whatever it takes" to resolve the European sovereign debt crisis? Bond pricing regime switches and monetary policy effects," Working Papers REM 2017/02, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    2. Jinzhao Chen, 2015. "Interprovincial Competitiveness and Economic Growth: Evidence from Chinese Provincial Data (1992–2008)," Pacific Economic Review, Wiley Blackwell, vol. 20(3), pages 388-414, August.
    3. Anne laure Delatte & Julien Fouquau, 2010. "Smooth transition in China: New evidence in the cointegrating money demand relationship," Economics Bulletin, AccessEcon, vol. 30(1), pages 265-273.
    4. Jean-Pierre Allegret & Cécile Couharde & Dramane Coulibaly & Valérie Mignon, 2013. "Current accounts and oil price fluctuations in oil-exporting countries: the role of financial development," Working Papers hal-04141185, HAL.
    5. Nidhaleddine Ben Cheikh & Oussama Ben Hmiden & Younes Ben Zaied & Sabri Boubaker, 2021. "Do sovereign credit ratings matter for corporate credit ratings?," Annals of Operations Research, Springer, vol. 297(1), pages 77-114, February.
    6. Cécile Couharde & Rémi Generoso, 2015. "Hydro-climatic thresholds and economic growth reversals in developing countries: an empirical investigation," Working Papers hal-04141392, HAL.
    7. Gilbert Colletaz & Christophe Hurlin, 2006. "Threshold Effects of the Public Capital Productivity : An International Panel Smooth Transition Approach," Working Papers halshs-00008056, HAL.
    8. Esra Alp Coskun & Nicholas Apergis & Yener Coskun, 2022. "Threshold effects of housing affordability and financial development on the house price‐consumption nexus," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 1785-1806, April.
    9. Rao, B. Bhaskara & Tamazian, Artur & Kumar, Saten, 2009. "Systems GMM estimates of the Feldstein-Horioka puzzle for the OECD countries and tests for structural breaks," MPRA Paper 15312, University Library of Munich, Germany.
    10. Hermann Ndoya hegueu & Aristophane Djeufack dongmo, 2021. "Urbanization, Governance and Informal Economy: an African Tale," Economics Bulletin, AccessEcon, vol. 41(3), pages 1525-1540.
    11. Virginie Coudert & Valérie Mignon, 2013. "The ‘Forward Premium Puzzle’ and the Sovereign Default risk," Post-Print hal-01385839, HAL.
    12. Reitz, Stefan & Rülke, Jan & Stadtmann, Georg, 2012. "Nonlinear Expectations in Speculative Markets," VfS Annual Conference 2012 (Goettingen): New Approaches and Challenges for the Labor Market of the 21st Century 62045, Verein für Socialpolitik / German Economic Association.
    13. Simplice A. Asongu & Nicholas M. Odhiambo, 2019. "Insurance Policy Thresholds for Economic Growth in Africa," CEREDEC Working Papers 19/037, Centre de Recherche pour le Développement Economique (CEREDEC).
    14. Virginie Coudert & Cécile Couharde & Valérie Mignon, 2013. "Pegging emerging currencies in the face of dollar swings," Post-Print hal-01411740, HAL.
    15. Ulucak, Recep & Koçak, Emrah & Erdoğan, Seyfettin & Kassouri, Yacouba, 2020. "Investigating the non-linear effects of globalization on material consumption in the EU countries: Evidence from PSTR estimation," Resources Policy, Elsevier, vol. 67(C).
    16. Bulent Guloglu & Saban Nazlioglu, 2013. "Impacts of Inflation on Agricultural Prices: Panel Smooth Transition Regression Analysis," Research Journal of Politics, Economics and Management, Sakarya University, Faculty of Economics and Administrative Sciences, vol. 1(1), pages 1-20, January.
    17. Mensi, Walid & Hammoudeh, Shawkat & Tiwari, Aviral Kumar & Al-Yahyaee, Khamis Hamed, 2020. "Impact of Islamic banking development and major macroeconomic variables on economic growth for Islamic countries: Evidence from panel smooth transition models," Economic Systems, Elsevier, vol. 44(1).
    18. Reitz, Stefan & Rülke, Jan-Christoph & Stadtmann, Georg, 2012. "Nonlinear expectations in speculative markets: Evidence from the ECB survey of professional forecasters," Discussion Papers 311, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    19. Sèwanoudé Honoré HOUNGBEDJI, 2021. "Budget policy, economic cycle and debt in the West African Economic and Monetary Union (WAEMU) countries: Empirical evidence based on a regime change model," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(4(629), W), pages 151-168, Winter.
    20. Gomes, Gabriel & Hache, Emmanuel & Mignon, Valérie & Paris, Anthony, 2018. "On the current account - biofuels link in emerging and developing countries: do oil price fluctuations matter?," Energy Policy, Elsevier, vol. 116(C), pages 60-67.
    21. Joshua Aizenman & Nan Geng, 2009. "Adjustment of State Owned and Foreign-Funded Enterprises in China to Economic Reforms,1980s-2007: a logistic smooth transition regression (LSTR) approach," NBER Working Papers 15274, National Bureau of Economic Research, Inc.
    22. Jean-Louis Combes & Alexandru Minea & Pegdéwendé Nestor Sawadogo, 2021. "Does the composition of government spending matter for government bond spreads?," Post-Print hal-03136159, HAL.
    23. Yıldırım, Durmuş Çağrı & Esen, Ömer & Yıldırım, Seda, 2022. "The nonlinear effects of environmental innovation on energy sector-based carbon dioxide emissions in OECD countries," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
    24. Ugo Panizza & Andrea Filippo Presbitero, 2013. "Public Debt and Economic Growth in Advanced Economies: A Survey," Mo.Fi.R. Working Papers 78, Money and Finance Research group (Mo.Fi.R.) - Univ. Politecnica Marche - Dept. Economic and Social Sciences.
    25. Tue Gørgens & Allan H. Würtz, 2019. "Threshold Regression with Endogeneity for Short Panels," Econometrics, MDPI, vol. 7(2), pages 1-8, May.
    26. Giannellis, Nikolaos & Koukouritakis, Minoas, 2019. "Gold price and exchange rates: A panel smooth transition regression model for the G7 countries," The North American Journal of Economics and Finance, Elsevier, vol. 49(C), pages 27-46.
    27. Valérie Mignon & Marc Joëts, 2011. "On the link between forward energy prices: A nonlinear panel cointegration approach," Working Papers hal-04140978, HAL.
    28. Simplice A. Asongu & Jean R. F. K. Bouanza & Armand F. Akpa, 2024. "Governance and Structural Transformation in Africa: Thresholds of Lifelong Gender Inclusive Education," Working Papers of The Association for Promoting Women in Research and Development in Africa (ASPROWORDA). 24/010, The Association for Promoting Women in Research and Development in Africa (ASPROWORDA).
    29. Salwa Trabelsi, 2019. "The governance threshold effect on the relationship between public education financing and income inequality," Economics Bulletin, AccessEcon, vol. 39(2), pages 1057-1075.
    30. Alexandru Minea & Patrick Villieu, 2008. "Investissement public et effets non linéaires des déficits budgétaires," Post-Print halshs-00364606, HAL.
    31. Anne-Laure Delatte & Julien Fouquau, 2012. "What Drove the Massive Hoarding of International Reserves in Emerging Economies? A Time-Varying Approach," Post-Print hal-01410598, HAL.
    32. Gabriel Gomes, 2016. "On the impact of dollar movements on oil currencies," Working Papers 2016-11, CEPII research center.
    33. Coudert, Virginie & Couharde, Cécile & Mignon, Valérie, 2015. "On the impact of volatility on the real exchange rate – terms of trade nexus: Revisiting commodity currencies," Journal of International Money and Finance, Elsevier, vol. 58(C), pages 110-127.
    34. Raphael Espinoza & Hyginus Leon & Ananthakrishnan Prasad, 2012. "When Should We Worry about Inflation?," The World Bank Economic Review, World Bank, vol. 26(1), pages 100-127.
    35. Po-Chin Wu & Chung-Chih Lee, 2018. "The non-linear impact of monetary policy on international reserves: macroeconomic variables nexus," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 45(1), pages 165-185, February.
    36. K. Peren Arin & Emin Gahramanov & Tolga Omay & Mehmet A. Ulubasoglu, 2019. "A tale of two taxes: State-dependency of tax policy," CAMA Working Papers 2019-68, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    37. Birgit Strikholm & Timo Teräsvirta, 2006. "A sequential procedure for determining the number of regimes in a threshold autoregressive model," Econometrics Journal, Royal Economic Society, vol. 9(3), pages 472-491, November.
    38. Anne-Laure Delatte & Mathieu Gex & Antonia Lòpez-Villavicencio, 2011. "Has the CDS market influenced the borrowing cost of European countries during the sovereign crisis?," Post-Print hal-00658200, HAL.
    39. Simplice A. Asongu & Nicholas M. Odhiambo, 2020. "The role of Globalization in Modulating the Effect of Environmental Degradation on Inclusive Human Development," Working Papers of the African Governance and Development Institute. 20/015, African Governance and Development Institute..
    40. Jinzhao Chen, 2012. "Real Exchange Rate and Economic Growth: Evidence from Chinese Provincial Data (1992 - 2008)," Working Papers halshs-00667467, HAL.
    41. Simplice A. Asongu & Jean R. F. K. Bouanza & Peter Agyemang-Mintah, 2024. "Globalization in Lifelong Gender Inclusive Education for Structural Transformation in Africa," Working Papers of the African Governance and Development Institute. 24/013, African Governance and Development Institute..
    42. Hao FANG & Joseph C. P. SHIEH & Tsang-Yao CHANG & Meng-Wen WU, 2020. "Which Types of Stocks Herded by Foreign Institutional Investors are Informational in the Emerging Stock Market?," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 31-48, September.
    43. Tolga Omay & Mubariz Hasanov & Nuri Uçar, 2012. "Energy Consumption and Economic Growth: Evidence from Nonlinear Panel Cointegration and Causality Tests," Hacettepe University Department of Economics Working Papers 20130, Hacettepe University, Department of Economics.
    44. Couharde, Cécile & Sallenave, Audrey, 2013. "How do currency misalignments’ threshold affect economic growth?," Journal of Macroeconomics, Elsevier, vol. 36(C), pages 106-120.
    45. Blaise Gnimassoun & Valérie Mignon, 2013. "Current-Account Adjustments and Exchange-Rate Misalignments," Working Papers 2013-29, CEPII research center.
    46. Golbabaei, Ali & Botshekan, Mahmoud, 2022. "The capital ratio and the interest rate spread: A panel threshold regression approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 85(C), pages 289-302.
    47. Cécile Couharde & Serge Rey & Audrey Sallenave, 2016. "External debt and real exchange rates’ adjustment in the euro area: new evidence from a nonlinear NATREX model," Applied Economics, Taylor & Francis Journals, vol. 48(11), pages 966-986, March.
    48. Simplice A. Asongu & Hillary C. Ezeaku, 2020. "Aid Grants vs. Technical Cooperation Grants: Implications for Inclusive Growth in Sub-Saharan Africa, 1984-2018," Working Papers of the African Governance and Development Institute. 20/091, African Governance and Development Institute..
    49. Virginie Coudert & Cécile Couharde & Valérie Mignon, 2013. "On the Impact of Oil Price Volatility on the Real Exchange Rate - Terms of Trade Nexus : Revisiting Commodity Currencies," Working Papers 2013-40, CEPII research center.
    50. Duarte, Rosa & Pinilla, Vicente & Serrano, Ana, 2013. "Is there an environmental Kuznets curve for water use? A panel smooth transition regression approach," Economic Modelling, Elsevier, vol. 31(C), pages 518-527.
    51. Po-Chin Wu & Shiao-Yen Liu & Tsai-Yuan Huang, 2017. "Non-linear Growth-Determinants Nexus: The Role of Sovereign Debt," Hacienda Pública Española / Review of Public Economics, IEF, vol. 222(3), pages 43-63, September.
    52. Jeannine Bailliu & Doga Bilgin & Kun Mo & Kurt Niquidet & Benjamin Sawatzky, 2019. "Global Commodity Markets and Rebalancing in China: The Case of Copper," Discussion Papers 2019-3, Bank of Canada.
    53. Arghyrou, Michael G & Gadea, Mar a Dolores, 2019. "Private bank deposits and macro/fiscal risk in the euro-area," Cardiff Economics Working Papers E2019/6, Cardiff University, Cardiff Business School, Economics Section.
    54. Natalia Zugravu-Soilita & Vincent Geronimi & Jessy Tsang & Christine Le Gargasson, 2020. "Promoting heritage for a sustainable development: the case of tourism in the island economies [Promouvoir le patrimoine pour un développement soutenable : le cas du tourisme dans les économies insu," Post-Print hal-03709168, HAL.
    55. Jude C. Eggoh & Patrick Villieu, 2013. "Un réexamen de la non-linéarité entre le développement financier et la croissance économique," Revue d'économie politique, Dalloz, vol. 123(2), pages 211-236.
    56. Leppin, Julian Sebastian, 2014. "The relation between overreaction in forecasts and uncertainty: A nonlinear approachvon," HWWI Research Papers 158, Hamburg Institute of International Economics (HWWI).
    57. Bui, Tung Duy & Bui, Hoai Thi Mai, 2020. "Threshold effect of economic openness on bank risk-taking: Evidence from emerging markets," Economic Modelling, Elsevier, vol. 91(C), pages 790-803.
    58. Hacioglu Hoke, Sinem & Kapetanios, George, 2017. "Common correlated effect cross-sectional dependence corrections for non-linear conditional mean panel models," Bank of England working papers 683, Bank of England.
    59. Julien Fouquau, 2007. "The Feldstein-Horiaka Puzzle: a Panel Smooth Transition Regression Approach," Post-Print halshs-00222938, HAL.
    60. Miao, Ke & Su, Liangjun & Wang, Wendun, 2020. "Panel threshold regressions with latent group structures," Journal of Econometrics, Elsevier, vol. 214(2), pages 451-481.
    61. Cho, Dooyeon, 2015. "The role of covered interest parity in explaining the forward premium anomaly within a nonlinear panel framework," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 229-238.
    62. Po-Chin Wu & Chia-Jui Chang, 2017. "Nonlinear impacts of debt ratio and term spread on inward FDI performance persistence," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 34(3), pages 369-388, December.
    63. Hela Namouri & Fredj Jawadi & Zied Ftiti & Néjib Hachicha, 2018. "Threshold effect in the relationship between investor sentiment and stock market returns: a PSTR specification," Applied Economics, Taylor & Francis Journals, vol. 50(5), pages 559-573, January.
    64. Danilo Trupkin & Raul Ibarra, 2011. "The Relationship between Inflation and Growth:A Panel Smooth Transition Regression Approach for Developed and Developing Countries," Documentos de Trabajo/Working Papers 1107, Facultad de Ciencias Empresariales y Economia. Universidad de Montevideo..
    65. Geng, Nan, 2011. "The dynamics of market structure and firm-level adjustment to India's pro-market economic liberalizing reforms, 1988-2006: A Time Varying Panel Smooth Transition Regression (TV-PSTR) approach," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 506-519, October.
    66. Djeneba Doumbia, 2019. "The quest for pro-poor and inclusive growth: the role of governance," Applied Economics, Taylor & Francis Journals, vol. 51(16), pages 1762-1783, April.
    67. Coulibaly, Dramane & Kempf, Hubert, 2019. "Inflation targeting and the forward bias puzzle in emerging countries," Journal of International Money and Finance, Elsevier, vol. 90(C), pages 19-33.
    68. Zhang, Mingming & Zhang, Shichang & Lee, Chien-Chiang & Zhou, Dequn, 2021. "Effects of trade openness on renewable energy consumption in OECD countries: New insights from panel smooth transition regression modelling," Energy Economics, Elsevier, vol. 104(C).
    69. JUDE, Cristina & LEVIEUGE, Gregory, 2013. "Growth effect of FDI in developing economies: The role of institutional quality," MPRA Paper 49321, University Library of Munich, Germany.
    70. Ibrahim Ahamada & Dramane Coulibaly, 2011. "How does financial development influence the impact of remittances on growth volatility?," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00629898, HAL.
    71. Cécile Couharde & Issiaka Coulibaly & Olivier Damette, 2012. "Misalignments and Dynamics of Real Exchange Rates in the CFA Franc Zone," Post-Print hal-01411706, HAL.
    72. Saïd Souam & Yacine Belarbi & Faycal Hamdi & Abderaouf Khalfi, 2021. "Growth, institutions and oil dependence: a buffered threshold panel approach," Post-Print hal-03148732, HAL.
    73. Julien Fouquau & Ghislaine Destais & Christophe Hurlin, 2009. "Energy demand models: a threshold panel specification of the 'Kuznets curve'," Applied Economics Letters, Taylor & Francis Journals, vol. 16(12), pages 1241-1244.
    74. Po-Chin Wu & Shiao-Yen Liu & Sheng-Chieh Pan, 2014. "Nonlinear relationship between health care expenditure and its determinants: a panel smooth transition regression model," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 41(4), pages 713-729, November.
    75. Muhammad Khan, 2013. "Inflation and Sectoral Output Growth Variability in Bulgaria," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 55(4), pages 687-704, December.
    76. Peng, Hua-Rong & Qin, Xiong-Feng, 2024. "Digitalization as a trigger for a rebound effect of electricity use," Energy, Elsevier, vol. 300(C).
    77. Pijnenburg, Katharina, 2017. "The spatial dimension of US house prices," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 54(2), pages 466-481.
    78. Liu, Bing & Yin, Weijun & Chen, Gang & Yao, Jing, 2023. "The threshold effect of climate risk and the non-linear role of climate policy uncertainty on insurance demand: Evidence from OECD countries," Finance Research Letters, Elsevier, vol. 55(PA).
    79. Alexandru Minea & Patrick Villieu, 2009. "Impôt, déficit et croissance économique : un réexamen de la courbe de Laffer," Post-Print hal-00448337, HAL.
    80. Tiba, Sofien, 2019. "Modeling the nexus between resources abundance and economic growth: An overview from the PSTR model," Resources Policy, Elsevier, vol. 64(C).
    81. Jiake Li & Wei Wang & Meng Li & Qiao Li & Zeming Liu & Wei Chen & Yanan Wang, 2022. "Impact of Land Management Scale on the Carbon Emissions of the Planting Industry in China," Land, MDPI, vol. 11(6), pages 1-15, May.
    82. A.S. Hurn & Annastiina Silvennoinen & Timo Teräsvirta, 2014. "A Smooth Transition Logit Model of the Effects of Deregulation in the Electricity Market," CREATES Research Papers 2014-09, Department of Economics and Business Economics, Aarhus University.
    83. Anne-Laure Delatte & Julien Fouquau, 2011. "The determinants of International Reserves in the Emerging countries: a non linear approach," Post-Print hal-00822326, HAL.
    84. Catherine Bruneau & Anne-Laure Delatte & Julien Fouquau, 2012. "Is the European sovereign crisis self-fulfilling ? Empirical evidence about the drivers of market sentiments," Documents de Travail de l'OFCE 2012-22, Observatoire Francais des Conjonctures Economiques (OFCE).
    85. Jer-Shiou Chiou & Bor-Yi Huang & Pei-Shan Wu & Chun-Ni Tsai, 2011. "The impacts of diversified operations on lending of financial institution," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 13(4), pages 587-599, June.
    86. Zhang, Zan & Hu, Wenjun & Chang, Tsangyao, 2019. "Nonlinear effects of P2P lending on bank loans in a Panel Smooth Transition Regression model," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 468-473.
    87. Issiaka Coulibaly, 2014. "Competitiveness and growth within the CFA franc zone: Does the switch to the Euro matter?," International Economics, CEPII research center, issue 139, pages 1-18.
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    340. Sekandary, Ghezal & Bask, Mikael, 2023. "Monetary policy uncertainty, monetary policy surprises and stock returns," Journal of Economics and Business, Elsevier, vol. 124(C).
    341. Lee, Chia-Hao & Chou, Pei-I, 2019. "Information dissemination and investors’ sensitivity," The Quarterly Review of Economics and Finance, Elsevier, vol. 74(C), pages 242-250.
    342. Tran, Ngan, 2018. "Debt threshold for fiscal sustainability assessment in emerging economies," Journal of Policy Modeling, Elsevier, vol. 40(2), pages 375-394.
    343. Zha, Donglan & Ding, Ning, 2015. "Threshold characteristic of energy efficiency on substitution between energy and non-energy factors," Economic Modelling, Elsevier, vol. 46(C), pages 180-187.
    344. Po-Chin Wu & Hsiao & I-Chung & Tsai & Meng-Hua, 2018. "Nonlinear Effect of Business Cycle on Lottery Sales Stability," Advances in Management and Applied Economics, SCIENPRESS Ltd, vol. 8(4), pages 1-3.

  10. Matthew T. Holt & Timo Teräsvirta, 2017. "Global Hemispheric Temperatures and Co–Shifting: A Vector Shifting–Mean Autoregressive Analysis," CREATES Research Papers 2017-05, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. C. Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2024. "Temperature in the Iberian Peninsula: Trend, seasonality, and heterogeneity," Papers 2406.14145, arXiv.org.
    2. He, Changli & Kang, Jian & Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Long monthly temperature series and the Vector Seasonal Shifting Mean and Covariance Autoregressive model," Journal of Econometrics, Elsevier, vol. 239(1).
    3. González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir, 2023. "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS 37968, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Marc Gronwald, 2023. "Explosive Temperatures," CESifo Working Paper Series 10680, CESifo.
    5. Friedrich, Marina & Lin, Yicong, 2024. "Sieve bootstrap inference for linear time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 239(1).

  11. Annastiina Silvennoinen & Timo Teräsvirta, 2017. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," CREATES Research Papers 2017-28, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. He, Changli & Kang, Jian & Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Long monthly temperature series and the Vector Seasonal Shifting Mean and Covariance Autoregressive model," Journal of Econometrics, Elsevier, vol. 239(1).
    2. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    3. Susana Martins & Cristina Amado, 2018. "Financial Market Contagion and the Sovereign Debt Crisis: A Smooth Transition Approach," NIPE Working Papers 08/2018, NIPE - Universidade do Minho.
    4. Campos-Martins, Susana & Amado, Cristina, 2022. "Financial market linkages and the sovereign debt crisis," Journal of International Money and Finance, Elsevier, vol. 123(C).

  12. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2017. "Modelling and forecasting WIG20 daily returns," CREATES Research Papers 2017-29, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    2. Mazur Błażej & Pipień Mateusz, 2018. "Time-varying asymmetry and tail thickness in long series of daily financial returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-21, December.
    3. Paulo Soares Esteves & Miguel Portela & António Rua, 2018. "Does domestic demand matter for firms’ exports?," NIPE Working Papers 18/2018, NIPE - Universidade do Minho.
    4. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2023. "Building Multivariate Time-Varying Smooth Transition Correlation GARCH Models, with an Application to the Four Largest Australian Banks," Econometrics, MDPI, vol. 11(1), pages 1-37, February.
    5. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2017. "Modelling and forecasting WIG20 daily returns," CREATES Research Papers 2017-29, Department of Economics and Business Economics, Aarhus University.
    6. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2021. "Four Australian Banks and the Multivariate Time-Varying Smooth Transition Correlation GARCH model," CREATES Research Papers 2021-13, Department of Economics and Business Economics, Aarhus University.

  13. Annastiina Silvennoinen & Timo Teräsvirta, 2015. "Testing constancy of unconditional variance in volatility models by misspecification and specification tests," CREATES Research Papers 2015-47, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    2. Fonseca, Thais C O & Cerqueira, Vinicius S & Migon, Helio S & Torres, Christian A C, 2021. "Evaluating the performance of degrees of freedom estimation in asymmetric GARCH models with t-student innovations," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 40(2), April.
    3. Conrad, Christian & Schienle, Melanie, 2019. "Testing for an omitted multiplicative long-term component in GARCH models," Working Paper Series in Economics 121, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    4. Pape, Katharina & Wied, Dominik & Galeano, Pedro, 2016. "Monitoring multivariate variance changes," Journal of Empirical Finance, Elsevier, vol. 39(PA), pages 54-68.
    5. He, Changli & Kang, Jian & Teräsvirta, Timo & Zhang, Shuhua, 2019. "The shifting seasonal mean autoregressive model and seasonality in the Central England monthly temperature series, 1772–2016," Econometrics and Statistics, Elsevier, vol. 12(C), pages 1-24.
    6. Changli He & Jian Kang & Timo Teräsvirta & Shuhua Zhang, 2019. "Comparing long monthly Chinese and selected European temperature series using the Vector Seasonal Shifting Mean and Covariance Autoregressive model," CREATES Research Papers 2019-19, Department of Economics and Business Economics, Aarhus University.
    7. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2017. "Modelling and forecasting WIG20 daily returns," CREATES Research Papers 2017-29, Department of Economics and Business Economics, Aarhus University.
    8. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2021. "Four Australian Banks and the Multivariate Time-Varying Smooth Transition Correlation GARCH model," CREATES Research Papers 2021-13, Department of Economics and Business Economics, Aarhus University.

  14. A.S. Hurn & Annastiina Silvennoinen & Timo Teräsvirta, 2014. "A Smooth Transition Logit Model of the Effects of Deregulation in the Electricity Market," CREATES Research Papers 2014-09, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Andres Gonzalez & Timo Terasvirta & Dick van Dijk, 2005. "Panel Smooth Transition Regression Models," Research Paper Series 165, Quantitative Finance Research Centre, University of Technology, Sydney.
    2. Apergis, Nicholas & Polemis, Michael, 2018. "Electricity supply shocks and economic growth across the US states: evidence from a time-varying Bayesian panel VAR model, aggregate and disaggregate energy sources," MPRA Paper 84954, University Library of Munich, Germany.
    3. Wei Wei & Asger Lunde, 2020. "Identifying Risk Factors and Their Premia: A Study on Electricity Prices," Monash Econometrics and Business Statistics Working Papers 10/20, Monash University, Department of Econometrics and Business Statistics.
    4. Wei Wei & Asger Lunde, 2023. "Identifying Risk Factors and Their Premia: A Study on Electricity Prices," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1647-1679.
    5. Murat Midilic, 2016. "Estimation Of Star-Garch Models With Iteratively Weighted Least Squares," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 16/918, Ghent University, Faculty of Economics and Business Administration.
    6. Susana Martins & Cristina Amado, 2018. "Financial Market Contagion and the Sovereign Debt Crisis: A Smooth Transition Approach," NIPE Working Papers 08/2018, NIPE - Universidade do Minho.
    7. Mwampashi, Muthe Mathias & Nikitopoulos, Christina Sklibosios & Rai, Alan & Konstandatos, Otto, 2022. "Large-scale and rooftop solar generation in the NEM: A tale of two renewables strategies," Energy Economics, Elsevier, vol. 115(C).
    8. Urbina, Jilber, 2016. "Crecimiento del crédito en Nicaragua, ¿Crecimiento natural o boom crediticio? [Credit growth in Nicaragua: Natural growth or credit boom?]," MPRA Paper 75577, University Library of Munich, Germany, revised Nov 2016.
    9. Mwampashi, Muthe Mathias & Nikitopoulos, Christina Sklibosios & Rai, Alan, 2024. "From 30- to 5-minute settlement rule in the NEM: An early evaluation," Energy Policy, Elsevier, vol. 194(C).
    10. Mardi Dungey & Ali Ghahremanlou & Ngo Van Long, 2017. "Strategic Bidding of Electric Power Generating Companies: Evidence from the Australian National Energy Market," CESifo Working Paper Series 6819, CESifo.
    11. Manner, Hans & Türk, Dennis & Eichler, Michael, 2016. "Modeling and forecasting multivariate electricity price spikes," Energy Economics, Elsevier, vol. 60(C), pages 255-265.
    12. Lin Han & Ivor Cribben & Stefan Trueck, 2022. "Extremal Dependence in Australian Electricity Markets," Papers 2202.09970, arXiv.org.
    13. Grossi, Luigi & Heim, Sven & Waterson, Michael, 2017. "The impact of the German response to the Fukushima earthquake," Energy Economics, Elsevier, vol. 66(C), pages 450-465.
    14. Csereklyei, Zsuzsanna & Khezr, Peyman, 2024. "How do changes in settlement periods affect wholesale market prices? Evidence from Australia's National Electricity Market," Energy Economics, Elsevier, vol. 132(C).
    15. Campos-Martins, Susana & Amado, Cristina, 2022. "Financial market linkages and the sovereign debt crisis," Journal of International Money and Finance, Elsevier, vol. 123(C).

  15. Timo Teräsvirta & Yukai Yang, 2014. "Specification, Estimation and Evaluation of Vector Smooth Transition Autoregressive Models with Applications," CREATES Research Papers 2014-08, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Chatterjee Pratiti, 2019. "Asymmetric impact of uncertainty in recessions: are emerging countries more vulnerable?," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 23(2), pages 1-27, April.
    2. Caggiano, Giovanni & Castelnuovo, Efrem & Groshenny, Nicolas, 2014. "Uncertainty shocks and unemployment dynamics in U.S. recessions," Journal of Monetary Economics, Elsevier, vol. 67(C), pages 78-92.
    3. Mehmet Balcilar & Kirsten Thompson & Rangan Gupta & Renee van Eyden, 2014. "Testing the Asymmetric Effects of Financial Conditions in South Africa: A Nonlinear Vector Autoregression Approach," Working Papers 15-11, Eastern Mediterranean University, Department of Economics.
    4. Frauke Schleer & Willi Semmler, 2014. "Financial Sector and Output Dynamics in the Euro Area: Non-linearities Reconsidered," SCEPA working paper series. 2014-5, Schwartz Center for Economic Policy Analysis (SCEPA), The New School.
    5. Terasvirta, Timo & Yang, Yukai, 2014. "Linearity and misspecification tests for vector smooth transition regression models," LIDAM Discussion Papers CORE 2014061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Svetlana Vtyurina & Zulima Leal, 2016. "Fiscal Multipliers and Institutions in Peru: Getting the Largest Bang for the Sol," IMF Working Papers 2016/144, International Monetary Fund.
    7. Jawadi Fredj & Mallick Sushanta K. & Sousa Ricardo M., 2014. "Fiscal policy in the BRICs," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 18(2), pages 201-215, April.
    8. Kotz Hans-Helmut & Semmler Willi & Tahri Ibrahim, 2018. "Financial fragmentation and the monetary transmission mechanism in the euro area: a smooth transition VAR approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-19, December.
    9. Frauke Schleer, 2015. "Finding Starting-Values for the Estimation of Vector STAR Models," Econometrics, MDPI, vol. 3(1), pages 1-26, January.
    10. Schleer, Frauke & Semmler, Willi, 2014. "Financial sector-output dynamics in the euro area: Non-linearities reconsidered," ZEW Discussion Papers 13-068 [rev.], ZEW - Leibniz Centre for European Economic Research.
    11. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
    12. Luiggi Donayre & Neil A. Wilmot, 2016. "The Asymmetric Effects of Oil Price Shocks on the Canadian Economy," International Journal of Energy Economics and Policy, Econjournals, vol. 6(2), pages 167-182.
    13. Willi Semmler & Christian R. Proaño, 2015. "Escape Routes from Sovereign Default Risk in the Euro Area," International Symposia in Economic Theory and Econometrics, in: Monetary Policy in the Context of the Financial Crisis: New Challenges and Lessons, volume 24, pages 163-193, Emerald Group Publishing Limited.
    14. YANG, Yukai, 2014. "Testing constancy of the error covariance matrix in vector models against parametric alternatives using a spectral decomposition," LIDAM Discussion Papers CORE 2014017, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Nidhaleddine Ben Cheikh & Sami Ben Naceur & Oussama Kanaan & Christophe Rault, 2021. "Investigating the asymmetric impact of oil prices on GCC stock markets," Post-Print hal-03529868, HAL.
    16. Fredj Jawadi & Georges Prat, 2017. "Equity prices and fundamentals: a DDM–APT mixed approach," Review of Quantitative Finance and Accounting, Springer, vol. 49(3), pages 661-695, October.
    17. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Fed’s unconventional monetary policy and risk spillover in the US financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 42-52.
    18. Ubilava, David, 2017. "The ENSO Effect and Asymmetries in Wheat Price Dynamics," World Development, Elsevier, vol. 96(C), pages 490-502.
    19. Balcilar, Mehmet & Usman, Ojonugwa & Duman, Gazi Murat, 2024. "Nonlinear network connectedness: Assessing financial risk transmission in MENA and influence of external financial conditions," Emerging Markets Review, Elsevier, vol. 62(C).
    20. Bucci, Andrea & Palomba, Giulio & Rossi, Eduardo, 2023. "The role of uncertainty in forecasting volatility comovements across stock markets," Economic Modelling, Elsevier, vol. 125(C).
    21. Nidhaleddine Ben Cheikh & Younes Ben Zaied & Pascal Nguyen, 2018. "Nonlinear Exchange Rate Transmission in the Euro Area: A Multivariate Smooth Transition Regression Approach," Economics Bulletin, AccessEcon, vol. 38(3), pages 1590-1602.
    22. Andrea Bucci, 2024. "A sequential test procedure for the choice of the number of regimes in multivariate nonlinear models," Papers 2406.02152, arXiv.org.
    23. Donayre, Luiggi & Panovska, Irina, 2016. "State-dependent exchange rate pass-through behavior," Journal of International Money and Finance, Elsevier, vol. 64(C), pages 170-195.
    24. NIDHALEDDINE BEN CHEIKH & SAMI BEN NACEUR & OUSSAMA KANAAN & Christophe RAULT, 2019. "Oil Prices and GCC Stock Markets: New Evidence from Vector Smooth Transition Models," LEO Working Papers / DR LEO 2697, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    25. Glen Livingston Jr & Darfiana Nur, 2020. "Bayesian estimation and model selection of a multivariate smooth transition autoregressive model," Environmetrics, John Wiley & Sons, Ltd., vol. 31(6), September.
    26. Andrea Bucci, 2022. "A smooth transition autoregressive model for matrix-variate time series," Papers 2212.08615, arXiv.org.
    27. Donayre, Luiggi & Panovska, Irina, 2018. "U.S. wage growth and nonlinearities: The roles of inflation and unemployment," Economic Modelling, Elsevier, vol. 68(C), pages 273-292.
    28. José Pedro Bastos Neves & Willi Semmler, 2022. "Credit, output and financial stress: A non‐linear LVSTAR application to Brazil," Metroeconomica, Wiley Blackwell, vol. 73(3), pages 900-923, July.
    29. Matusche, Alexander & Wacks, Johannes, 2023. "Does wealth inequality affect the transmission of monetary policy?," Journal of Macroeconomics, Elsevier, vol. 75(C).
    30. Martin Bruns & Michele Piffer, 2021. "Monetary policy shocks over the business cycle: Extending the Smooth Transition framework," University of East Anglia School of Economics Working Paper Series 2021-07, School of Economics, University of East Anglia, Norwich, UK..
    31. Cheikh, Nidhaleddine Ben & Zaied, Younes Ben, 2023. "Investigating the dynamics of crude oil and clean energy markets in times of geopolitical tensions," Energy Economics, Elsevier, vol. 124(C).
    32. Fotiou, Alexandra, 2022. "Non-linearities in fiscal policy: The role of debt," European Economic Review, Elsevier, vol. 150(C).
    33. Hou, Chenghan & Nguyen, Bao H., 2018. "Understanding the US natural gas market: A Markov switching VAR approach," Energy Economics, Elsevier, vol. 75(C), pages 42-53.
    34. Chatterjee, Pratiti, 2024. "Uncertainty shocks, financial frictions, and business cycle asymmetries across countries," European Economic Review, Elsevier, vol. 162(C).
    35. Schleer, Frauke, 2013. "Finding starting-values for maximum likelihood estimation of vector STAR models," ZEW Discussion Papers 13-076, ZEW - Leibniz Centre for European Economic Research.

  16. Timo Teräsvirta & Yukai Yang, 2014. "Linearity and Misspecification Tests for Vector Smooth Transition Regression Models," CREATES Research Papers 2014-04, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Guay Lim & Sarantis Tsiaplias, 2016. "Non-Linearities in the Relationship between House Prices and Interest Rates: Implications for Monetary Policy," Melbourne Institute Working Paper Series wp2016n02, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    2. Giovanni Caggiano & Efrem Castelnuovo & Juan Manuel Figueres, 2018. "Economic Policy Uncertainty Spillovers in Booms and Busts," "Marco Fanno" Working Papers 0220, Dipartimento di Scienze Economiche "Marco Fanno".
    3. Frauke Schleer & Willi Semmler, 2014. "Financial Sector and Output Dynamics in the Euro Area: Non-linearities Reconsidered," SCEPA working paper series. 2014-5, Schwartz Center for Economic Policy Analysis (SCEPA), The New School.
    4. Cheng, Chak Hung Jack & Chiu, Ching-Wai (Jeremy), 2016. "Nonlinearities of mortgage spreads over the business cycles," Bank of England working papers 634, Bank of England.
    5. Mehmet Balcilar & David Roubaud & Ojonugwa Usman & Mark E. Wohar, 2021. "Testing the asymmetric effects of exchange rate pass‐through in BRICS countries: Does the state of the economy matter?," The World Economy, Wiley Blackwell, vol. 44(1), pages 188-233, January.
    6. Schleer, Frauke & Semmler, Willi, 2014. "Financial sector-output dynamics in the euro area: Non-linearities reconsidered," ZEW Discussion Papers 13-068 [rev.], ZEW - Leibniz Centre for European Economic Research.
    7. Jiang, Yonghong & He, Luli & Meng, Juan & Nie, He, 2019. "Nonlinear impact of economic policy uncertainty shocks on credit scale: Evidence from China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 521(C), pages 626-634.
    8. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
    9. Luiggi Donayre & Neil A. Wilmot, 2016. "The Asymmetric Effects of Oil Price Shocks on the Canadian Economy," International Journal of Energy Economics and Policy, Econjournals, vol. 6(2), pages 167-182.
    10. Giovanni Caggiano & Efrem Castelnuovo & Gabriela Nodari, 2020. "Uncertainty and monetary policy in good and bad times: A replication of the VAR investigation by Bloom (2009)," "Marco Fanno" Working Papers 0261, Dipartimento di Scienze Economiche "Marco Fanno".
    11. Giovanni Caggiano & Efrem Castelnuovo & Gabriela Nodari, 2017. "Uncertainty and Monetary Policy in Good and Bad Times," RBA Research Discussion Papers rdp2017-06, Reserve Bank of Australia.
    12. Willi Semmler & Christian R. Proaño, 2015. "Escape Routes from Sovereign Default Risk in the Euro Area," International Symposia in Economic Theory and Econometrics, in: Monetary Policy in the Context of the Financial Crisis: New Challenges and Lessons, volume 24, pages 163-193, Emerald Group Publishing Limited.
    13. YANG, Yukai, 2014. "Testing constancy of the error covariance matrix in vector models against parametric alternatives using a spectral decomposition," LIDAM Discussion Papers CORE 2014017, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Caggiano, Giovanni & Castelnuovo, Efrem & Figueres, Juan Manuel, 2017. "Economic policy uncertainty and unemployment in the United States: A nonlinear approach," Economics Letters, Elsevier, vol. 151(C), pages 31-34.
    15. Christina Anderl & Guglielmo Maria Caporale, 2021. "Testing for UIP: Nonlinearities, Monetary Announcements and Interest Rate Expectations," CESifo Working Paper Series 9027, CESifo.
    16. Fredj Jawadi & Souhir Chlibi & Abdoulkarim Idi Cheffou, 2019. "Computing stock price comovements with a three-regime panel smooth transition error correction model," Annals of Operations Research, Springer, vol. 274(1), pages 331-345, March.
    17. Ernst, Ekkehard & Semmler, Willi & Haider, Alexander, 2017. "Debt-deflation, financial market stress and regime change – Evidence from Europe using MRVAR," Journal of Economic Dynamics and Control, Elsevier, vol. 81(C), pages 115-139.
    18. Abdelkamel Alj & Christophe Ley & Guy Melard, 2015. "Asymptotic Properties of QML Estimators for VARMA Models with Time-Dependent Coefficients: Part I," Working Papers ECARES ECARES 2015-21, ULB -- Universite Libre de Bruxelles.
    19. Chak Hung Jack Cheng & Ching‐Wai (Jeremy) Chiu, 2020. "Nonlinear Effects of Mortgage Spreads Over the Business Cycle," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 52(6), pages 1593-1611, September.
    20. Balcilar, Mehmet & Roubaud, David & Usman, Ojonugwa & Wohar, Mark E., 2021. "Moving out of the linear rut: A period-specific and regime-dependent exchange rate and oil price pass-through in the BRICS countries," Energy Economics, Elsevier, vol. 98(C).
    21. Ubilava, David, 2017. "The ENSO Effect and Asymmetries in Wheat Price Dynamics," World Development, Elsevier, vol. 96(C), pages 490-502.
    22. Nguyen, Bao H. & Okimoto, Tatsuyoshi, 2019. "Asymmetric reactions of the US natural gas market and economic activity," Energy Economics, Elsevier, vol. 80(C), pages 86-99.
    23. Bucci, Andrea & Palomba, Giulio & Rossi, Eduardo, 2023. "The role of uncertainty in forecasting volatility comovements across stock markets," Economic Modelling, Elsevier, vol. 125(C).
    24. Fontaine, Idriss & Razafindravaosolonirina, Justinien & Didier, Laurent, 2018. "Chinese policy uncertainty shocks and the world macroeconomy: Evidence from STVAR," China Economic Review, Elsevier, vol. 51(C), pages 1-19.
    25. Andrea Bucci, 2024. "A sequential test procedure for the choice of the number of regimes in multivariate nonlinear models," Papers 2406.02152, arXiv.org.
    26. Steven M. Fazzari & James Morley & Irina B. Panovska, 2017. "When Do Discretionary Changes in Government Spending or Taxes Have Larger Effects?," Discussion Papers 2017-04, School of Economics, The University of New South Wales.
    27. Giovanni Caggiano & Efrem Castelnuovo & Gabriela Nodari, 2022. "Uncertainty and monetary policy in good and bad times: A replication of the vector autoregressive investigation by Bloom (2009)," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(1), pages 210-217, January.
    28. Kevin Larcher & Jaebeom Kim & Youngju Kim, 2019. "Uncertainty shocks and asymmetric dynamics in Korea: a non-linear approach," Applied Economics, Taylor & Francis Journals, vol. 51(6), pages 594-610, February.
    29. Glen Livingston Jr & Darfiana Nur, 2020. "Bayesian estimation and model selection of a multivariate smooth transition autoregressive model," Environmetrics, John Wiley & Sons, Ltd., vol. 31(6), September.
    30. Hwang, Inwook & Kim, Jaebeom, 2021. "Oil price shocks and the US stock market: A nonlinear approach," Journal of Empirical Finance, Elsevier, vol. 64(C), pages 23-36.
    31. Demetrescu, Matei & Leppin, Julian Sebastian & Reitz, Stefan, 2017. "Homogenous vs. heterogenous transition functions in smooth transition regressions: A LM-type test," Kiel Working Papers 2094, Kiel Institute for the World Economy (IfW Kiel).
    32. Christina Anderl & Guglielmo Maria Caporale, 2022. "Testing for UIP-Type Relationships: Nonlinearities, Monetary Announcements and Interest Rate Expectations," Open Economies Review, Springer, vol. 33(4), pages 705-749, September.
    33. Nguyen, Bao H. & Okimoto, Tatsuyoshi & Tran, Trung Duc, 2022. "Uncertainty-dependent and sign-dependent effects of oil market shocks," Journal of Commodity Markets, Elsevier, vol. 26(C).
    34. Mehmet Balcilar & David Roubaud & Ojonugwa Usman & Mark E. Wohar, 2019. "Testing the Asymmetric Effects of Exchange Rate and Oil Price Pass-Through in BRICS Countries: Does the state of the economy matter?," Working Papers 15-49, Eastern Mediterranean University, Department of Economics.
    35. Chlibi Souhir & Jawadi Fredj & Sellami Mohamed, 2017. "Modeling threshold effects in stock price co-movements: a vector nonlinear cointegration approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(1), pages 47-63, February.
    36. Linderoth, Gabriella & Meuller, Malte, 2024. "Inflation-Dependent Exchange Rate Pass-Through in Sweden: Insights from a Logistic Smooth Transition VAR Model," Working Paper Series 439, Sveriges Riksbank (Central Bank of Sweden).
    37. Wen, Bohui & Bi, ShaSha & Yuan, Ming & Hao, Jing, 2023. "Financial constraint, cross-sectoral spillover and systemic risk in China," International Review of Economics & Finance, Elsevier, vol. 84(C), pages 1-11.

  17. Paul Catani & Timo Teräsvirta & Meiqun Yin, 2014. "A Lagrange Multiplier Test for Testing the Adequacy of the Constant Conditional Correlation GARCH Model," CREATES Research Papers 2014-03, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    2. Gregory Rice & Tony Wirjanto & Yuqian Zhao, 2020. "Tests for conditional heteroscedasticity of functional data," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(6), pages 733-758, November.
    3. Lee, Taewook, 2016. "Wild bootstrap Ljung–Box test for cross correlations of multivariate time series," Economics Letters, Elsevier, vol. 147(C), pages 59-62.
    4. Rice, Gregory & Wirjanto, Tony & Zhao, Yuqian, 2019. "Tests for conditional heteroscedasticity with functional data and goodness-of-fit tests for FGARCH models," MPRA Paper 93048, University Library of Munich, Germany.
    5. Jian Kang & Johan Stax Jakobsen & Annastiina Silvennoinen & Timo Teräsvirta & Glen Wade, 2022. "A parsimonious test of constancy of a positive definite correlation matrix in a multivariate time-varying GARCH model," CREATES Research Papers 2022-01, Department of Economics and Business Economics, Aarhus University.
    6. Keqiang Dong & Liao Guo, 2021. "Research on the Spatial Correlation and Spatial Lag of COVID-19 Infection Based on Spatial Analysis," Sustainability, MDPI, vol. 13(21), pages 1-16, October.

  18. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Frauke Schleer & Willi Semmler, 2014. "Financial Sector and Output Dynamics in the Euro Area: Non-linearities Reconsidered," SCEPA working paper series. 2014-5, Schwartz Center for Economic Policy Analysis (SCEPA), The New School.
    2. Andrea Silvestrini & Andrea Zaghini, 2015. "Financial shocks and the real economy in a nonlinear world: a survey of the theoretical and empirical literature," Questioni di Economia e Finanza (Occasional Papers) 255, Bank of Italy, Economic Research and International Relations Area.
    3. Terasvirta, Timo & Yang, Yukai, 2014. "Linearity and misspecification tests for vector smooth transition regression models," LIDAM Discussion Papers CORE 2014061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. KANAZAWA, Nobuyuki & 金澤, 伸幸, 2018. "Radial Basis Functions Neural Networks for Nonlinear Time Series Analysis and Time-Varying Effects of Supply Shocks," Discussion paper series HIAS-E-64, Hitotsubashi Institute for Advanced Study, Hitotsubashi University.
    5. Kotz Hans-Helmut & Semmler Willi & Tahri Ibrahim, 2018. "Financial fragmentation and the monetary transmission mechanism in the euro area: a smooth transition VAR approach," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-19, December.
    6. Frauke Schleer, 2015. "Finding Starting-Values for the Estimation of Vector STAR Models," Econometrics, MDPI, vol. 3(1), pages 1-26, January.
    7. Schleer, Frauke & Semmler, Willi, 2014. "Financial sector-output dynamics in the euro area: Non-linearities reconsidered," ZEW Discussion Papers 13-068 [rev.], ZEW - Leibniz Centre for European Economic Research.
    8. A.S. Hurn & Annastiina Silvennoinen & Timo Teräsvirta, 2014. "A Smooth Transition Logit Model of the Effects of Deregulation in the Electricity Market," CREATES Research Papers 2014-09, Department of Economics and Business Economics, Aarhus University.
    9. Barnichon, Regis & Matthes, Christian, 2018. "Functional Approximation of Impulse Responses," Journal of Monetary Economics, Elsevier, vol. 99(C), pages 41-55.
    10. Hubrich, Kirstin & Skudelny, Frauke, 2016. "Forecast combination for euro area inflation: a cure in times of crisis?," Working Paper Series 1972, European Central Bank.
    11. Emilio Zanetti Chini, 2013. "Generalizing smooth transition autoregressions," CEIS Research Paper 294, Tor Vergata University, CEIS, revised 25 Sep 2014.
    12. Kalli, Maria & Griffin, Jim E., 2018. "Bayesian nonparametric vector autoregressive models," Journal of Econometrics, Elsevier, vol. 203(2), pages 267-282.
    13. Willi Semmler & Christian R. Proaño, 2015. "Escape Routes from Sovereign Default Risk in the Euro Area," International Symposia in Economic Theory and Econometrics, in: Monetary Policy in the Context of the Financial Crisis: New Challenges and Lessons, volume 24, pages 163-193, Emerald Group Publishing Limited.
    14. Nidhaleddine Ben Cheikh & Sami Ben Naceur & Oussama Kanaan & Christophe Rault, 2021. "Investigating the asymmetric impact of oil prices on GCC stock markets," Post-Print hal-03529868, HAL.
    15. Fève, Patrick & Garcia, Pablo & Sahuc, Jean-Guillaume, 2017. "State-dependent risk taking and the transmission of monetary policy shocks," TSE Working Papers 17-872, Toulouse School of Economics (TSE).
    16. Markku Lanne & Henri Nyberg, 2014. "Generalized Forecast Error Variance Decomposition for Linear and Nonlinear Multivariate Models," CREATES Research Papers 2014-17, Department of Economics and Business Economics, Aarhus University.
    17. Vito Polito, 2020. "Nonlinear Business Cycle and Optimal Policy: A VSTAR Perspective," CESifo Working Paper Series 8060, CESifo.
    18. Di Caro, Paolo, 2014. "Regional recessions and recoveries in theory and practice: a resilience-based overview," MPRA Paper 60300, University Library of Munich, Germany.
    19. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with smooth transition in variances," Journal of Economic Dynamics and Control, Elsevier, vol. 84(C), pages 43-57.
    20. Timo Teräsvirta, 2017. "Nonlinear models in macroeconometrics," CREATES Research Papers 2017-32, Department of Economics and Business Economics, Aarhus University.
    21. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Fed’s unconventional monetary policy and risk spillover in the US financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 42-52.
    22. Balcilar, Mehmet & Roubaud, David & Usman, Ojonugwa & Wohar, Mark E., 2021. "Moving out of the linear rut: A period-specific and regime-dependent exchange rate and oil price pass-through in the BRICS countries," Energy Economics, Elsevier, vol. 98(C).
    23. Iwanicz-Drozdowska, Małgorzata & Rogowicz, Karol & Kurowski, Łukasz & Smaga, Paweł, 2021. "Two decades of contagion effect on stock markets: Which events are more contagious?," Journal of Financial Stability, Elsevier, vol. 55(C).
    24. Helmut Lütkepohl & Aleksei Netsunajev, 2014. "Structural Vector Autoregressions with Smooth Transition in Variances: The Interaction between U.S. Monetary Policy and the Stock Market," Discussion Papers of DIW Berlin 1388, DIW Berlin, German Institute for Economic Research.
    25. Ubilava, David, 2017. "The ENSO Effect and Asymmetries in Wheat Price Dynamics," World Development, Elsevier, vol. 96(C), pages 490-502.
    26. Cheikh, Nidhaleddine Ben & Zaied, Younes Ben & Mattoussi, Wided, 2023. "Oil price shocks in the age of surging inflation," Energy Economics, Elsevier, vol. 128(C).
    27. Nguyen, Bao H. & Okimoto, Tatsuyoshi, 2019. "Asymmetric reactions of the US natural gas market and economic activity," Energy Economics, Elsevier, vol. 80(C), pages 86-99.
    28. Bucci, Andrea & Palomba, Giulio & Rossi, Eduardo, 2023. "The role of uncertainty in forecasting volatility comovements across stock markets," Economic Modelling, Elsevier, vol. 125(C).
    29. Gardini, Laura & Radi, Davide & Schmitt, Noemi & Sushko, Iryna & Westerhoff, Frank, 2023. "Sentiment-driven business cycle dynamics: An elementary macroeconomic model with animal spirits," Journal of Economic Behavior & Organization, Elsevier, vol. 210(C), pages 342-359.
    30. Arisara Romyen & Jianxu Liu & Songsak Sriboonchitta, 2019. "Export–Output Growth Nexus Using Threshold VAR and VEC Models: Empirical Evidence from Thailand," Economies, MDPI, vol. 7(2), pages 1-16, June.
    31. Andrea Bucci, 2024. "A sequential test procedure for the choice of the number of regimes in multivariate nonlinear models," Papers 2406.02152, arXiv.org.
    32. Galyna Grynkiv & Lars Stentoft, 2018. "Stationary Threshold Vector Autoregressive Models," JRFM, MDPI, vol. 11(3), pages 1-23, August.
    33. Glen Livingston Jr & Darfiana Nur, 2020. "Bayesian estimation and model selection of a multivariate smooth transition autoregressive model," Environmetrics, John Wiley & Sons, Ltd., vol. 31(6), September.
    34. Corrêa, Wilson Luiz Rotatori & Lopes, Luckas Sabioni, 2023. "Monetary policy transmission, productive activity, and inflation in Brazil: Does uncertainty matter?," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    35. Harun, Cicilia A. & Taruna, Aditya Anta & Ramdani,, 2021. "Capturing the nonlinear impact in distress state: Enhancing scenario design of stress test," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 265-288.
    36. Andrea Bucci, 2022. "A smooth transition autoregressive model for matrix-variate time series," Papers 2212.08615, arXiv.org.
    37. Semmler, Willi & Toure, Marieme, 2024. "Financial fragility, regime change, and monetary policy in an open economy – A model and empirical application to emerging market countries," International Economics, Elsevier, vol. 179(C).
    38. Blazsek, Szabolcs & Licht, Adrian, 2019. "Markov-switching score-driven multivariate models: outlier-robust measurement of the relationships between world crude oil production and US industrial production," UC3M Working papers. Economics 29030, Universidad Carlos III de Madrid. Departamento de Economía.
    39. Peter Martey Addo, 2014. "Multivariate Self-Exciting Threshold Autoregressive Models with eXogenous Input," Papers 1407.7738, arXiv.org.
    40. Ryuzo Miyao & Tatsuyoshi Okimoto, 2020. "Regime shifts in the effects of Japan’s unconventional monetary policies," Manchester School, University of Manchester, vol. 88(6), pages 749-772, December.
    41. Andrea Bucci & Giulio Palomba & Eduardo Rossi, 2019. "Does macroeconomics help in predicting stock markets volatility comovements? A nonlinear approach," Working Papers 440, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    42. Zhang, Xu & Yang, Xian & He, Qizhi, 2022. "Multi-scale systemic risk and spillover networks of commodity markets in the bullish and bearish regimes," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    43. Nguyen, Bao H. & Okimoto, Tatsuyoshi & Tran, Trung Duc, 2022. "Uncertainty-dependent and sign-dependent effects of oil market shocks," Journal of Commodity Markets, Elsevier, vol. 26(C).
    44. A. C. Cebrián & J. Abaurrea & J. Asín & E. Segarra, 2019. "Dynamic Regression Model for Hourly River Level Forecasting Under Risk Situations: an Application to the Ebro River," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(2), pages 523-537, January.
    45. Cheikh, Nidhaleddine Ben & Zaied, Younes Ben, 2023. "Investigating the dynamics of crude oil and clean energy markets in times of geopolitical tensions," Energy Economics, Elsevier, vol. 124(C).
    46. Igor L. Kheifets & Pentti J. Saikkonen, 2020. "Stationarity and ergodicity of vector STAR models," Econometric Reviews, Taylor & Francis Journals, vol. 39(4), pages 407-414, April.
    47. Giovanni De Luca & Paola Zuccolotto, 2021. "Regime dependent interconnectedness among fuzzy clusters of financial time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(2), pages 315-336, June.
    48. Li, Johnny Siu-Hang & Ng, Andrew C.Y. & Chan, Wai-Sum, 2015. "Managing financial risk in Chinese stock markets: Option pricing and modeling under a multivariate threshold autoregression," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 217-230.
    49. Hou, Chenghan & Nguyen, Bao H., 2018. "Understanding the US natural gas market: A Markov switching VAR approach," Energy Economics, Elsevier, vol. 75(C), pages 42-53.
    50. William Irungu Nganga & Julien Chevallier & Simon Wagura Ndiritu, 2018. "Regime changes and fiscal sustainability in Kenya with comparative nonlinear Granger causalities across East-African countries," Working Papers halshs-01941226, HAL.
    51. Schleer, Frauke, 2013. "Finding starting-values for maximum likelihood estimation of vector STAR models," ZEW Discussion Papers 13-076, ZEW - Leibniz Centre for European Economic Research.
    52. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
    53. Irungu, William Nganga & Chevallier, Julien & Ndiritu, Simon Wagura, 2020. "Regime changes and fiscal sustainability in Kenya," Economic Modelling, Elsevier, vol. 86(C), pages 1-9.
    54. Ana C. Cebrián & Ricardo Salillas, 2021. "Forecasting High-Frequency River Level Series Using Double Switching Regression with ARMA Errors," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(1), pages 299-313, January.
    55. Barnichon, Regis & Matthes, Christian, 2016. "Gaussian Mixture Approximations of Impulse Responses and The Non-Linear Effects of Monetary Shocks," CEPR Discussion Papers 11374, C.E.P.R. Discussion Papers.
    56. Maria Bolboaca & Sarah Fischer, 2019. "News Shocks: Different Effects in Boom and Recession?," Working Papers 19.01, Swiss National Bank, Study Center Gerzensee.

  19. Kappler, Marcus & Schleer, Frauke & Semmler, Willi & Teräsvirta, Timo & Winker, Peter, 2013. "Financial sector and output dynamics in the euro area countries," ZEW policy briefs 9/2013, ZEW - Leibniz Centre for European Economic Research.

    Cited by:

    1. Turuntseva, M. & Zyamalov, V., 2016. "Stock Markets under the Changing Terms of Trade," Journal of the New Economic Association, New Economic Association, vol. 31(3), pages 93-109.
    2. Willi Semmler & André Semmler & Christian Schoder, 2013. "Makroökonomische Effekte der Haushaltskonsolidierung in der Europäischen Union," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 82(4), pages 163-180.
    3. Ekkehard Ernst & Stefan Mittnik & Willi Semmler, 2016. "Interaction of Labour and Credit Market in Growth Regimes: A Theoretical and Empirical Analysis," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 45(3), pages 393-422, November.

  20. Matthew T. Holt & Timo Teräsvirta, 2012. "Global Hemispheric Temperature Trends and Co–Shifting: A Shifting Mean Vector Autoregressive Analysis," CREATES Research Papers 2012-54, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
    2. Walter Enders & Matthew T. Holt, 2014. "The Evolving Relationships between Agricultural and Energy Commodity Prices: A Shifting-Mean Vector Autoregressive Analysis," NBER Chapters, in: The Economics of Food Price Volatility, pages 135-187, National Bureau of Economic Research, Inc.
    3. Francisco Estrada & Pierre Perron, "undated". "Detection and attribution of climate change through econometric methods," Boston University - Department of Economics - Working Papers Series 2013-015, Boston University - Department of Economics.
    4. Barry K. Goodwin & Matthew T. Holt & Jeffrey P. Prestemon, 2021. "Semi-parametric models of spatial market integration," Empirical Economics, Springer, vol. 61(5), pages 2335-2361, November.

  21. Cristina Amado & Timo Teräsvirta, 2012. "Modelling Changes in the Unconditional Variance of Long Stock Return Series," CREATES Research Papers 2012-07, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    2. Hanck, Christoph & Demetrescu, Matei & Kruse, Robinson, 2015. "Fixed-b Asymptotics for t-Statistics in the Presence of Time-Varying Volatility," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112916, Verein für Socialpolitik / German Economic Association.
    3. Giuseppe Cavaliere & Morten Ørregaard Nielsen & Robert Taylor, 2017. "Quasi-Maximum Likelihood Estimation and Bootstrap Inference in Fractional Time Series Models with Heteroskedasticity of Unknown Form," CREATES Research Papers 2017-02, Department of Economics and Business Economics, Aarhus University.
    4. Xu, Ke-Li, 2013. "Power monotonicity in detecting volatility levels change," Economics Letters, Elsevier, vol. 121(1), pages 64-69.
    5. Demetrescu, Matei & Kruse, Robinson, 2015. "Testing heteroskedastic time series for normality," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113221, Verein für Socialpolitik / German Economic Association.
    6. Li, Dongxin & Zhang, Li & Li, Lihong, 2023. "Forecasting stock volatility with economic policy uncertainty: A smooth transition GARCH-MIDAS model," International Review of Financial Analysis, Elsevier, vol. 88(C).
    7. Silvennoinen Annastiina & Teräsvirta Timo, 2016. "Testing constancy of unconditional variance in volatility models by misspecification and specification tests," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 347-364, September.
    8. Shi, Yanlin & Ho, Kin-Yip, 2015. "Modeling high-frequency volatility with three-state FIGARCH models," Economic Modelling, Elsevier, vol. 51(C), pages 473-483.
    9. Alessandra Amendola & Vincenzo Candila & Antonio Scognamillo, 2017. "On the influence of US monetary policy on crude oil price volatility," Empirical Economics, Springer, vol. 52(1), pages 155-178, February.
    10. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2012. "Unit roots, nonlinearities and structural breaks," CREATES Research Papers 2012-14, Department of Economics and Business Economics, Aarhus University.
    11. Pape, Katharina & Wied, Dominik & Galeano, Pedro, 2016. "Monitoring multivariate variance changes," Journal of Empirical Finance, Elsevier, vol. 39(PA), pages 54-68.
    12. Skrobotov, Anton, 2020. "Survey on structural breaks and unit root tests," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 58, pages 96-141.
    13. Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun & Wang, Weining, 2021. "Long- and short-run components of factor betas: Implications for stock pricing," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    14. Ke-Li Xu & Jui-Chung Yang, 2015. "Towards Uniformly Efficient Trend Estimation Under Weak/Strong Correlation and Non-stationary Volatility," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 63-86, March.
    15. Yves Dominicy & Harry-Paul Vander Elst, 2015. "Macro-Driven VaR Forecasts: From Very High to Very Low Frequency Data," Working Papers ECARES ECARES 2015-41, ULB -- Universite Libre de Bruxelles.
    16. Mazur Błażej & Pipień Mateusz, 2018. "Time-varying asymmetry and tail thickness in long series of daily financial returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-21, December.
    17. Matei Demetrescu & Christoph Hanck & Robinson Kruse, 2016. "Fixed-b Inference in the Presence of Time-Varying Volatility," CREATES Research Papers 2016-01, Department of Economics and Business Economics, Aarhus University.
    18. Giampiero M. Gallo & Edoardo Otranto, 2018. "Combining sharp and smooth transitions in volatility dynamics: a fuzzy regime approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 549-573, April.
    19. Tommaso Proietti, 2015. "Exponential Smoothing, Long Memory and Volatility Prediction," CREATES Research Papers 2015-51, Department of Economics and Business Economics, Aarhus University.
    20. Demetrescu, Matei & Salish, Nazarii, 2024. "(Structural) VAR models with ignored changes in mean and volatility," International Journal of Forecasting, Elsevier, vol. 40(2), pages 840-854.
    21. Hao Jin & Si Zhang & Jinsuo Zhang, 2017. "Spurious regression due to neglected of non-stationary volatility," Computational Statistics, Springer, vol. 32(3), pages 1065-1081, September.
    22. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2021. "Choosing the frequency of volatility components within the Double Asymmetric GARCH–MIDAS–X model," Econometrics and Statistics, Elsevier, vol. 20(C), pages 12-28.
    23. Błażej Mazur & Mateusz Pipień, 2012. "On the Empirical Importance of Periodicity in the Volatility of Financial Returns - Time Varying GARCH as a Second Order APC(2) Process," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(2), pages 95-116, June.
    24. Ke Zhu, 2018. "Statistical inference for autoregressive models under heteroscedasticity of unknown form," Papers 1804.02348, arXiv.org, revised Aug 2018.
    25. Sucarrat, Genaro, 2016. "Equation-by-Equation Estimation of Multivariate Periodic Electricity Price Volatility," UC3M Working papers. Economics 23436, Universidad Carlos III de Madrid. Departamento de Economía.
    26. Demetrescu, Matei & Rodrigues, Paulo M.M., 2022. "Residual-augmented IVX predictive regression," Journal of Econometrics, Elsevier, vol. 227(2), pages 429-460.
    27. Isao Ishida & Virmantas Kvedaras, 2015. "Modeling Autoregressive Processes with Moving-Quantiles-Implied Nonlinearity," Econometrics, MDPI, vol. 3(1), pages 1-53, January.
    28. Hossein Asgharian & Charlotte Christiansen & Ai Jun Hou & Weining Wang, 2017. "Long- and Short-Run Components of Factor Betas: Implications for Equity Pricing," CREATES Research Papers 2017-34, Department of Economics and Business Economics, Aarhus University.
    29. Laurie Davies & Walter Kraemer, 2016. "Stylized Facts and Simulating Long Range Financial Data," CESifo Working Paper Series 5796, CESifo.
    30. Kawka, Rafael, 2022. "Convergence of spectral density estimators in the locally stationary framework," Econometrics and Statistics, Elsevier, vol. 24(C), pages 94-115.
    31. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2017. "Modelling and forecasting WIG20 daily returns," CREATES Research Papers 2017-29, Department of Economics and Business Economics, Aarhus University.
    32. Jiang, Xiandeng & Shi, Yanlin & Zhang, Zhaoyong, 2021. "Does US partisan conflict affect China’s foreign exchange reserves?," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 21-33.
    33. Cristina Amado & Timo Teräsvirta, 2017. "Specification and testing of multiplicative time-varying GARCH models with applications," Econometric Reviews, Taylor & Francis Journals, vol. 36(4), pages 421-446, April.
    34. Markus Vogl, 2022. "Quantitative modelling frontiers: a literature review on the evolution in financial and risk modelling after the financial crisis (2008–2019)," SN Business & Economics, Springer, vol. 2(12), pages 1-69, December.
    35. Feng, Lingbing & Fu, Tong & Shi, Yanlin, 2022. "How does news sentiment affect the states of Japanese stock return volatility?," International Review of Financial Analysis, Elsevier, vol. 84(C).
    36. Yuanyuan Zhang & Rong Liu & Qin Shao & Lijian Yang, 2020. "Two‐Step Estimation for Time Varying Arch Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(4), pages 551-570, July.

  22. Annastiina Silvennoinen & Timo Teräsvirta, 2012. "Modelling conditional correlations of asset returns: A smooth transition approach," CREATES Research Papers 2012-09, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    2. Bauwens, Luc & Otranto, Edoardo, 2020. "Nonlinearities and regimes in conditional correlations with different dynamics," LIDAM Reprints CORE 3128, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Ohashi, Kazuhiko & Okimoto, Tatsuyoshi, 2016. "Increasing trends in the excess comovement of commodity prices," Journal of Commodity Markets, Elsevier, vol. 1(1), pages 48-64.
    4. De Santis, Roberto A. & Stein, Michael, 2016. "Correlation changes between the risk-free rate and sovereign yields of euro area countries," Working Paper Series 1979, European Central Bank.
    5. Heejoon Han & Dennis Kristensen, 2012. "Asymptotic Theory for the QMLE in GARCH-X Models with Stationary and Non-Stationary Covariates," CREATES Research Papers 2012-25, Department of Economics and Business Economics, Aarhus University.
    6. João F. Caldeira & Guilherme V. Moura & Francisco J. Nogales & André A. P. Santos, 2017. "Combining Multivariate Volatility Forecasts: An Economic-Based Approach," Journal of Financial Econometrics, Oxford University Press, vol. 15(2), pages 247-285.
    7. He, Changli & Kang, Jian & Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Long monthly temperature series and the Vector Seasonal Shifting Mean and Covariance Autoregressive model," Journal of Econometrics, Elsevier, vol. 239(1).
    8. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    9. Chuffart, Thomas, 2022. "Interest in cryptocurrencies predicts conditional correlation dynamics," Finance Research Letters, Elsevier, vol. 46(PA).
    10. Saart, Patrick W. & Xia, Yingcun, 2022. "Functional time series approach to analyzing asset returns co-movements," Journal of Econometrics, Elsevier, vol. 229(1), pages 127-151.
    11. L. Bauwens & E. Otranto, 2013. "Modeling the Dependence of Conditional Correlations on Volatility," Working Paper CRENoS 201304, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    12. Emilio Zanetti Chini, 2018. "Forecasting dynamically asymmetric fluctuations of the U.S. business cycle," CREATES Research Papers 2018-13, Department of Economics and Business Economics, Aarhus University.
    13. Anne Péguin-Feissolle & Bilel Sanhaji, 2015. "Testing the Constancy of Conditional Correlations in Multivariate GARCH-type Models (Extended Version with Appendix)," AMSE Working Papers 1516, Aix-Marseille School of Economics, France.
    14. Tarciso Gouveia da Silva & Osmani Teixeira de Carvalho Guillén & George Augusto Noronha Morcerf & Andre de Melo Modenesi, 2020. "Effects of Monetary Policy News on Financial Assets: evidence from Brazil on a bivariate VAR-GARCH model (2006-17)," Working Papers Series 536, Central Bank of Brazil, Research Department.
    15. Susana Martins & Cristina Amado, 2018. "Financial Market Contagion and the Sovereign Debt Crisis: A Smooth Transition Approach," NIPE Working Papers 08/2018, NIPE - Universidade do Minho.
    16. BAUWENS, Luc & HAFNER, Christian M. & PIERRET, Diane, 2013. "Multivariate volatility modeling of electricity futures," LIDAM Reprints CORE 2526, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    17. Changli He & Jian Kang & Timo Teräsvirta & Shuhua Zhang, 2019. "Comparing long monthly Chinese and selected European temperature series using the Vector Seasonal Shifting Mean and Covariance Autoregressive model," CREATES Research Papers 2019-19, Department of Economics and Business Economics, Aarhus University.
    18. Annastiina Silvennoinen & Susan Thorp, 2015. "Crude Oil and Agricultural Futures: An Analysis of Correlation Dynamics," NCER Working Paper Series 109, National Centre for Econometric Research.
    19. Susana Campos-Martins & Cristina Amado, 2023. "Modelling causality in nonstationary variances with an application to carbon markets," NIPE Working Papers 13/2023, NIPE - Universidade do Minho.
    20. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    21. Silvennoinen, Annastiina & Thorp, Susan, 2013. "Financialization, crisis and commodity correlation dynamics," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 42-65.
    22. E. Otranto, 2015. "Adding Flexibility to Markov Switching Models," Working Paper CRENoS 201509, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    23. Dimitrios Thomakos & Johannes Klepsch & Dimitris N. Politis, 2020. "Model Free Inference on Multivariate Time Series with Conditional Correlations," Stats, MDPI, vol. 3(4), pages 1-26, November.
    24. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2023. "Building Multivariate Time-Varying Smooth Transition Correlation GARCH Models, with an Application to the Four Largest Australian Banks," Econometrics, MDPI, vol. 11(1), pages 1-37, February.
    25. Abdul Aziz, Nor Syahilla & Vrontos, Spyridon & M. Hasim, Haslifah, 2019. "Evaluation of multivariate GARCH models in an optimal asset allocation framework," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 568-596.
    26. Aslanidis, Nektarios & Martinez, Oscar, 2021. "Correlation regimes in international equity and bond returns," Economic Modelling, Elsevier, vol. 97(C), pages 397-410.
    27. Kryzanowski, Lawrence & Zhang, Jie & Zhong, Rui, 2017. "Cross-financial-market correlations and quantitative easing," Finance Research Letters, Elsevier, vol. 20(C), pages 13-21.
    28. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2021. "Four Australian Banks and the Multivariate Time-Varying Smooth Transition Correlation GARCH model," CREATES Research Papers 2021-13, Department of Economics and Business Economics, Aarhus University.
    29. Jian Kang & Johan Stax Jakobsen & Annastiina Silvennoinen & Timo Teräsvirta & Glen Wade, 2022. "A parsimonious test of constancy of a positive definite correlation matrix in a multivariate time-varying GARCH model," CREATES Research Papers 2022-01, Department of Economics and Business Economics, Aarhus University.
    30. Nauro Campos & Ekaterina Glebkina & Menelaos Karanasos & Panagiotis Koutroumpis, 2023. "Financial Development, Political Instability, Trade Openness and Growth in Brazil: Evidence from a New Dataset, 1890-2003," Open Economies Review, Springer, vol. 34(4), pages 831-861, September.
    31. Campos-Martins, Susana & Amado, Cristina, 2022. "Financial market linkages and the sovereign debt crisis," Journal of International Money and Finance, Elsevier, vol. 123(C).
    32. Haojun Pan & Yuxiang Tang & Guoqiang Wang, 2024. "A Stock Index Futures Price Prediction Approach Based on the MULTI-GARCH-LSTM Mixed Model," Mathematics, MDPI, vol. 12(11), pages 1-15, May.

  23. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2012. "Unit roots, nonlinearities and structural breaks," CREATES Research Papers 2012-14, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Kathia Pinz'on, 2016. "Analysis of Price and Income Elasticities of Energy Demand in Ecuador: A Dynamic OLS Approach," Papers 1611.05288, arXiv.org.
    2. Christensen, Bent Jesper & Varneskov, Rasmus Tangsgaard, 2017. "Medium band least squares estimation of fractional cointegration in the presence of low-frequency contamination," Journal of Econometrics, Elsevier, vol. 197(2), pages 218-244.
    3. Khan, Mashrur Mustaque & Yousuf, Ahmed Sadek, 2013. "Macroeconomic Forces and Stock Prices:Evidence from the Bangladesh Stock Market," MPRA Paper 46528, University Library of Munich, Germany.
    4. Robinson Kruse & Daniel Ventosa-Santaulària & Antonio E. Noriega, 2013. "Changes in persistence, spurious regressions and the Fisher hypothesis," CREATES Research Papers 2013-11, Department of Economics and Business Economics, Aarhus University.

  24. Cristina Amado & Timo Teräsvirta, 2011. "Conditional Correlation Models of Autoregressive Conditional Heteroskedasticity with Nonstationary GARCH Equations," CREATES Research Papers 2011-24, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    2. Cristina Amado & Timo Teräsvirta, 2011. "Modelling Volatility by Variance Decomposition," NIPE Working Papers 01/2011, NIPE - Universidade do Minho.
    3. Ngene, Geoffrey & Post, Jordin A. & Mungai, Ann N., 2018. "Volatility and shock interactions and risk management implications: Evidence from the U.S. and frontier markets," Emerging Markets Review, Elsevier, vol. 37(C), pages 181-198.
    4. Serge Darolles & Christian Francq & Sébastien Laurent, 2017. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Post-Print hal-04590471, HAL.
    5. De Santis, Roberto A. & Stein, Michael, 2016. "Correlation changes between the risk-free rate and sovereign yields of euro area countries," Working Paper Series 1979, European Central Bank.
    6. Fresoli, Diego Eduardo, 2014. "The uncertainty of conditional returns, volatilities and correlations in DCC models," DES - Working Papers. Statistics and Econometrics. WS ws140202, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Susana Martins & Cristina Amado, 2018. "Financial Market Contagion and the Sovereign Debt Crisis: A Smooth Transition Approach," NIPE Working Papers 08/2018, NIPE - Universidade do Minho.
    8. Ngene, Geoffrey M. & Lee Kim, Yea & Wang, Jinghua, 2019. "Who poisons the pool? Time-varying asymmetric and nonlinear causal inference between low-risk and high-risk bonds markets," Economic Modelling, Elsevier, vol. 81(C), pages 136-147.
    9. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    10. De Santis, Roberto A. & Stein, Michael, 2015. "Financial indicators signaling correlation changes in sovereign bond markets," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 86-102.
    11. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2023. "Building Multivariate Time-Varying Smooth Transition Correlation GARCH Models, with an Application to the Four Largest Australian Banks," Econometrics, MDPI, vol. 11(1), pages 1-37, February.
    12. Kang‐Soek Lee & Richard A. Werner, 2023. "Are lower interest rates really associated with higher growth? New empirical evidence on the interest rate thesis from 19 countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3960-3975, October.
    13. Bekiros, Stelios D., 2014. "Contagion, decoupling and the spillover effects of the US financial crisis: Evidence from the BRIC markets," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 58-69.
    14. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2021. "Four Australian Banks and the Multivariate Time-Varying Smooth Transition Correlation GARCH model," CREATES Research Papers 2021-13, Department of Economics and Business Economics, Aarhus University.
    15. Jian Kang & Johan Stax Jakobsen & Annastiina Silvennoinen & Timo Teräsvirta & Glen Wade, 2022. "A parsimonious test of constancy of a positive definite correlation matrix in a multivariate time-varying GARCH model," CREATES Research Papers 2022-01, Department of Economics and Business Economics, Aarhus University.
    16. Guerello, Chiara, 2016. "The effect of investors’ confidence on monetary policy transmission mechanism," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 248-266.
    17. Campos-Martins, Susana & Amado, Cristina, 2022. "Financial market linkages and the sovereign debt crisis," Journal of International Money and Finance, Elsevier, vol. 123(C).
    18. Yuanyuan Zhang & Rong Liu & Qin Shao & Lijian Yang, 2020. "Two‐Step Estimation for Time Varying Arch Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(4), pages 551-570, July.

  25. Anders Bredahl Kock & Timo Teräsvirta, 2011. "Forecasting performance of three automated modelling techniques during the economic crisis 2007-2009," CREATES Research Papers 2011-28, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Jena, Pradyot Ranjan & Majhi, Ritanjali & Kalli, Rajesh & Managi, Shunsuke & Majhi, Babita, 2021. "Impact of COVID-19 on GDP of major economies: Application of the artificial neural network forecaster," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 324-339.
    2. Jahn, Malte, 2018. "Artificial neural network regression models: Predicting GDP growth," HWWI Research Papers 185, Hamburg Institute of International Economics (HWWI).
    3. Ferrara, Laurent & Marcellino, Massimiliano & Mogliani, Matteo, 2015. "Macroeconomic forecasting during the Great Recession: The return of non-linearity?," International Journal of Forecasting, Elsevier, vol. 31(3), pages 664-679.
    4. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023. "Machine learning advances for time series forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
    5. Marcus Buckmann & Andreas Joseph, 2023. "An Interpretable Machine Learning Workflow with an Application to Economic Forecasting," International Journal of Central Banking, International Journal of Central Banking, vol. 19(4), pages 449-522, October.
    6. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis”," AQR Working Papers 201508, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2015.
    7. Jahn, Malte, 2020. "Artificial neural network regression models in a panel setting: Predicting economic growth," Economic Modelling, Elsevier, vol. 91(C), pages 148-154.
    8. Oscar Claveria & Enric Monte & Salvador Torra, 2016. "Modelling cross-dependencies between Spain’s regional tourism markets with an extension of the Gaussian process regression model," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(3), pages 341-357, August.
    9. Claudimar Pereira da Veiga & Cássia Rita Pereira da Veiga & Felipe Mendes Girotto & Diego Antonio Bittencourt Marconatto & Zhaohui Su, 2024. "Implementation of the ARIMA model for prediction of economic variables: evidence from the health sector in Brazil," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-11, December.
    10. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Regional tourism demand forecasting with machine learning models: Gaussian process regression vs. neural network models in a multiple-input multiple-output setting”," AQR Working Papers 201701, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2017.
    11. Zhidan Luo & Wei Guo & Qingfu Liu & Yiuman Tse, 2023. "A hybrid prediction model with time‐varying gain tracking differentiator in Taylor expansion: Evidence from precious metals," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(5), pages 1138-1149, August.
    12. Ahmed Ramzy Mohamed, 2022. "Artificial Neural Network for Modeling the Economic Performance: A New Perspective," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 20(3), pages 555-575, September.
    13. Lee Jinu, 2019. "A Neural Network Method for Nonlinear Time Series Analysis," Journal of Time Series Econometrics, De Gruyter, vol. 11(1), pages 1-18, January.
    14. Diogo de Prince & Emerson Fernandes Marçal & Pedro L. Valls Pereira, 2022. "Forecasting Industrial Production Using Its Aggregated and Disaggregated Series or a Combination of Both: Evidence from One Emerging Market Economy," Econometrics, MDPI, vol. 10(2), pages 1-34, June.
    15. Malte Jahn, 2023. "Artificial neural networks and time series of counts: A class of nonlinear INGARCH models," Papers 2304.01025, arXiv.org.
    16. Malte Jahn, 2023. "Regressing on distributions: The nonlinear effect of temperature on regional economic growth," Papers 2309.10481, arXiv.org.

  26. Cristina Amado & Timo Teräsvirta, 2011. "Modelling Volatility by Variance Decomposition," CREATES Research Papers 2011-01, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Bauwens, Luc & Dufays, Arnaud & Rombouts, Jeroen V.K., 2014. "Marginal likelihood for Markov-switching and change-point GARCH models," Journal of Econometrics, Elsevier, vol. 178(P3), pages 508-522.
    2. Arthur J. Lin & Hai-Yen Chang, 2020. "Volatility Transmission from Equity, Bulk Shipping, and Commodity Markets to Oil ETF and Energy Fund—A GARCH-MIDAS Model," Mathematics, MDPI, vol. 8(9), pages 1-21, September.
    3. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    4. Hanck, Christoph & Demetrescu, Matei & Kruse, Robinson, 2015. "Fixed-b Asymptotics for t-Statistics in the Presence of Time-Varying Volatility," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112916, Verein für Socialpolitik / German Economic Association.
    5. Hossein Asgharian & Charlotte Christiansen & Ai Jun Hou, 2014. "Macro-Finance Determinants of the Long-Run Stock-Bond Correlation: The DCC-MIDAS Specification," CREATES Research Papers 2014-13, Department of Economics and Business Economics, Aarhus University.
    6. Demetrescu, Matei & Kruse, Robinson, 2015. "Testing heteroskedastic time series for normality," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113221, Verein für Socialpolitik / German Economic Association.
    7. He, Changli & Kang, Jian & Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Long monthly temperature series and the Vector Seasonal Shifting Mean and Covariance Autoregressive model," Journal of Econometrics, Elsevier, vol. 239(1).
    8. Matias Quiroz & Laleh Tafakori & Hans Manner, 2024. "Forecasting realized covariances using HAR-type models," Papers 2412.10791, arXiv.org.
    9. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    10. Conrad, Christian & Schienle, Melanie, 2019. "Testing for an omitted multiplicative long-term component in GARCH models," Working Paper Series in Economics 121, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    11. Paul Catani & Timo Teräsvirta & Meiqun Yin, 2017. "A Lagrange multiplier test for testing the adequacy of constant conditional correlation GARCH model," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 599-621, October.
    12. Cristina Amado & Timo Teräsvirta, 2012. "Modelling Changes in the Unconditional Variance of Long Stock Return Series," CREATES Research Papers 2012-07, Department of Economics and Business Economics, Aarhus University.
    13. Silvennoinen Annastiina & Teräsvirta Timo, 2016. "Testing constancy of unconditional variance in volatility models by misspecification and specification tests," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 347-364, September.
    14. Naimoli, Antonio & Storti, Giuseppe, 2019. "Heterogeneous component multiplicative error models for forecasting trading volumes," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1332-1355.
    15. Dawei Zhang & Zhuo (June) Cheng & Hasan A. Qurban H. Mohammad & Barrie R. Nault, 2015. "Research Commentary—Information Technology Substitution Revisited," Information Systems Research, INFORMS, vol. 26(3), pages 480-495, September.
    16. Niklas Ahlgren & Alexander Back & Timo Terasvirta, 2024. "A new GARCH model with a deterministic time-varying intercept," Papers 2410.03239, arXiv.org, revised Oct 2024.
    17. Martínez-García Enrique, 2018. "Modeling time-variation over the business cycle (1960–2017): an international perspective," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-25, December.
    18. Henryk Gurgul & Roland Mestel & Robert Syrek, 2017. "MIDAS models in banking sector – systemic risk comparison," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 18(2), pages 165-181.
    19. Francisco Blasques & Enzo D'Innocenzo & Siem Jan Koopman, 2021. "Common and Idiosyncratic Conditional Volatility Factors: Theory and Empirical Evidence," Tinbergen Institute Discussion Papers 21-057/III, Tinbergen Institute.
    20. Emilio Zanetti Chini, 2013. "Generalizing smooth transition autoregressions," CEIS Research Paper 294, Tor Vergata University, CEIS, revised 25 Sep 2014.
    21. Daiki Maki & Yasushi Ota, 2021. "Testing for Time-Varying Properties Under Misspecified Conditional Mean and Variance," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1167-1182, April.
    22. Alessandra Amendola & Vincenzo Candila & Antonio Scognamillo, 2017. "On the influence of US monetary policy on crude oil price volatility," Empirical Economics, Springer, vol. 52(1), pages 155-178, February.
    23. Emilio Zanetti Chini, 2018. "Forecasting dynamically asymmetric fluctuations of the U.S. business cycle," CREATES Research Papers 2018-13, Department of Economics and Business Economics, Aarhus University.
    24. Timo Terasvirta & Zhenfang Zhao, 2011. "Stylized facts of return series, robust estimates and three popular models of volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 21(1-2), pages 67-94.
    25. Mobarek, Asma & Muradoglu, Gulnur & Mollah, Sabur & Hou, Ai Jun, 2016. "Determinants of time varying co-movements among international stock markets during crisis and non-crisis periods," Journal of Financial Stability, Elsevier, vol. 24(C), pages 1-11.
    26. Dinghai Xu, 2020. "Canadian Stock Market Volatility under COVID-19," Working Papers 2001, University of Waterloo, Department of Economics, revised May 2020.
    27. Yves Dominicy & Harry-Paul Vander Elst, 2015. "Macro-Driven VaR Forecasts: From Very High to Very Low Frequency Data," Working Papers ECARES ECARES 2015-41, ULB -- Universite Libre de Bruxelles.
    28. Wilson Ye Chen & Richard H. Gerlach, 2017. "Semiparametric GARCH via Bayesian model averaging," Papers 1708.07587, arXiv.org.
    29. Mazur Błażej & Pipień Mateusz, 2018. "Time-varying asymmetry and tail thickness in long series of daily financial returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-21, December.
    30. Matei Demetrescu & Christoph Hanck & Robinson Kruse, 2016. "Fixed-b Inference in the Presence of Time-Varying Volatility," CREATES Research Papers 2016-01, Department of Economics and Business Economics, Aarhus University.
    31. Matias Quiroz & Laleh Tafakori & Hans Manner, 2024. "Forecasting Realized Covariances Using HAR-Type Models," Graz Economics Papers 2024-20, University of Graz, Department of Economics.
    32. Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    33. Tommaso Proietti, 2015. "Exponential Smoothing, Long Memory and Volatility Prediction," CREATES Research Papers 2015-51, Department of Economics and Business Economics, Aarhus University.
    34. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2021. "Choosing the frequency of volatility components within the Double Asymmetric GARCH–MIDAS–X model," Econometrics and Statistics, Elsevier, vol. 20(C), pages 12-28.
    35. Susana Martins & Cristina Amado, 2018. "Financial Market Contagion and the Sovereign Debt Crisis: A Smooth Transition Approach," NIPE Working Papers 08/2018, NIPE - Universidade do Minho.
    36. Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H., 2014. "Bayesian estimation of smoothly mixing time-varying parameter GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 194-209.
    37. Grote, Claudia & Bertram, Philip, 2015. "A comparative Study of Volatility Breaks," Hannover Economic Papers (HEP) dp-558, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    38. He, Changli & Kang, Jian & Teräsvirta, Timo & Zhang, Shuhua, 2019. "The shifting seasonal mean autoregressive model and seasonality in the Central England monthly temperature series, 1772–2016," Econometrics and Statistics, Elsevier, vol. 12(C), pages 1-24.
    39. Bertelsen, Kristoffer Pons & Borup, Daniel & Jakobsen, Johan Stax, 2021. "Stock market volatility and public information flow: A non-linear perspective," Economics Letters, Elsevier, vol. 204(C).
    40. Eric Hillebrand & Marcelo C. Medeiros, 2012. "Nonlinearity, Breaks, and Long-Range Dependence in Time-Series Models," CREATES Research Papers 2012-30, Department of Economics and Business Economics, Aarhus University.
    41. Matei Demetrescu & Christoph Hanck & Robinson Kruse‐Becher, 2022. "Robust inference under time‐varying volatility: A real‐time evaluation of professional forecasters," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(5), pages 1010-1030, August.
    42. Ke Zhu, 2018. "Statistical inference for autoregressive models under heteroscedasticity of unknown form," Papers 1804.02348, arXiv.org, revised Aug 2018.
    43. Christian Conrad & Robert F. Engle, 2021. "Modelling Volatility Cycles: The (MF)2 GARCH Model," Working Paper series 21-05, Rimini Centre for Economic Analysis.
    44. Alicia Adsera, Ana Ferrer and Virginia Herranz, 2020. "Descriptive labour market outcomes of immigrant women across Europe," Working Papers 2004, University of Waterloo, Department of Economics, revised 2020.
    45. Sucarrat, Genaro, 2016. "Equation-by-Equation Estimation of Multivariate Periodic Electricity Price Volatility," UC3M Working papers. Economics 23436, Universidad Carlos III de Madrid. Departamento de Economía.
    46. VAN BELLEGEM, Sébastien, 2011. "Locally stationary volatility modelling," LIDAM Discussion Papers CORE 2011041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    47. Demetrescu, Matei & Rodrigues, Paulo M.M., 2022. "Residual-augmented IVX predictive regression," Journal of Econometrics, Elsevier, vol. 227(2), pages 429-460.
    48. Hossein Asgharian & Charlotte Christiansen & Ai Jun Hou & Weining Wang, 2017. "Long- and Short-Run Components of Factor Betas: Implications for Equity Pricing," CREATES Research Papers 2017-34, Department of Economics and Business Economics, Aarhus University.
    49. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2023. "Building Multivariate Time-Varying Smooth Transition Correlation GARCH Models, with an Application to the Four Largest Australian Banks," Econometrics, MDPI, vol. 11(1), pages 1-37, February.
    50. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2017. "Modelling and forecasting WIG20 daily returns," CREATES Research Papers 2017-29, Department of Economics and Business Economics, Aarhus University.
    51. Yew-Choe Lum & Sardar M. N. Islam, 2016. "Time Varying Behavior of Share Returns in Australia: 1988–2004," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 19(01), pages 1-14, March.
    52. Matei Demetrescu & Robinson Kruse-Becher, 2021. "Is U.S. real output growth really non-normal? Testing distributional assumptions in time-varying location-scale models," CREATES Research Papers 2021-07, Department of Economics and Business Economics, Aarhus University.
    53. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2019. "On the asymmetric impact of macro–variables on volatility," Economic Modelling, Elsevier, vol. 76(C), pages 135-152.
    54. Cristina Amado & Timo Teräsvirta, 2017. "Specification and testing of multiplicative time-varying GARCH models with applications," Econometric Reviews, Taylor & Francis Journals, vol. 36(4), pages 421-446, April.
    55. Daiki Maki & Yasushi Ota, 2019. "Testing for time-varying properties under misspecified conditional mean and variance," Papers 1907.12107, arXiv.org, revised Aug 2019.
    56. Wu, Xinyu & Xie, Haibin, 2021. "A realized EGARCH-MIDAS model with higher moments," Finance Research Letters, Elsevier, vol. 38(C).
    57. Jiang, Feiyu & Li, Dong & Zhu, Ke, 2021. "Adaptive inference for a semiparametric generalized autoregressive conditional heteroskedasticity model," Journal of Econometrics, Elsevier, vol. 224(2), pages 306-329.
    58. Feiyu Jiang & Dong Li & Ke Zhu, 2019. "Adaptive inference for a semiparametric generalized autoregressive conditional heteroskedasticity model," Papers 1907.04147, arXiv.org, revised Oct 2020.
    59. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2021. "Four Australian Banks and the Multivariate Time-Varying Smooth Transition Correlation GARCH model," CREATES Research Papers 2021-13, Department of Economics and Business Economics, Aarhus University.
    60. Jian Kang & Johan Stax Jakobsen & Annastiina Silvennoinen & Timo Teräsvirta & Glen Wade, 2022. "A parsimonious test of constancy of a positive definite correlation matrix in a multivariate time-varying GARCH model," CREATES Research Papers 2022-01, Department of Economics and Business Economics, Aarhus University.
    61. Li, Chenxing & Maheu, John M & Yang, Qiao, 2022. "An Infinite Hidden Markov Model with Stochastic Volatility," MPRA Paper 115456, University Library of Munich, Germany.
    62. Christian Conrad & Onno Kleen, 2020. "Two are better than one: Volatility forecasting using multiplicative component GARCH‐MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 19-45, January.
    63. Campos-Martins, Susana & Amado, Cristina, 2022. "Financial market linkages and the sovereign debt crisis," Journal of International Money and Finance, Elsevier, vol. 123(C).
    64. Yuanyuan Zhang & Rong Liu & Qin Shao & Lijian Yang, 2020. "Two‐Step Estimation for Time Varying Arch Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 41(4), pages 551-570, July.

  27. Timo Teräsvirta, 2011. "Nonlinear models for autoregressive conditional heteroskedasticity," CREATES Research Papers 2011-02, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Gallo, Giampiero M. & Otranto, Edoardo, 2015. "Forecasting realized volatility with changing average levels," International Journal of Forecasting, Elsevier, vol. 31(3), pages 620-634.

  28. Anders Bredahl Kock & Timo Teräsvirta, 2011. "Forecasting Macroeconomic Variables using Neural Network Models and Three Automated Model Selection Techniques," CREATES Research Papers 2011-27, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. David Hendry & Lea Schneider & Jason E. Smerdon, 2016. "Detecting Volcanic Eruptions in Temperature Reconstructions by Designed Break-Indicator Saturation," Economics Series Working Papers 780, University of Oxford, Department of Economics.
    2. Guilherme Schultz Lindenmeyer & Hudson Silva Torrent, 2024. "Boosting and Predictability of Macroeconomic Variables: Evidence from Brazil," Computational Economics, Springer;Society for Computational Economics, vol. 64(1), pages 377-409, July.
    3. Muhammad Nadim Hanif & Khurrum S. Mughal & Javed Iqbal, 2018. "A Thick ANN Model for Forecasting Inflation," SBP Working Paper Series 99, State Bank of Pakistan, Research Department.
    4. Kock, Anders Bredahl & Teräsvirta, Timo, 2014. "Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009," International Journal of Forecasting, Elsevier, vol. 30(3), pages 616-631.
    5. Kock Anders Bredahl, 2011. "Forecasting with Universal Approximators and a Learning Algorithm," Journal of Time Series Econometrics, De Gruyter, vol. 3(3), pages 1-32, October.
    6. Vito Polito & Yunyi Zhang, 2021. "Tackling Large Outliers in Macroeconomic Data with Vector Artificial Neural Network Autoregression," CESifo Working Paper Series 9395, CESifo.
    7. Andrii Babii & Eric Ghysels & Jonas Striaukas, 2024. "Econometrics of machine learning methods in economic forecasting," Chapters, in: Michael P. Clements & Ana Beatriz Galvão (ed.), Handbook of Research Methods and Applications in Macroeconomic Forecasting, chapter 10, pages 246-273, Edward Elgar Publishing.
    8. Kauppi, Heikki & Virtanen, Timo, 2021. "Boosting nonlinear predictability of macroeconomic time series," International Journal of Forecasting, Elsevier, vol. 37(1), pages 151-170.
    9. Tae-Hwy Lee & Zhou Xi & Ru Zhang, 2013. "Testing for Neglected Nonlinearity Using Regularized Artificial Neural Networks," Working Papers 201422, University of California at Riverside, Department of Economics, revised Apr 2012.
    10. Heikki Kauppi & Timo Virtanen, 2018. "Boosting Non-linear Predictabilityof Macroeconomic Time Series," Discussion Papers 124, Aboa Centre for Economics.
    11. Anders Bredahl Kock & Laurent A.F. Callot, 2012. "Oracle Efficient Estimation and Forecasting with the Adaptive LASSO and the Adaptive Group LASSO in Vector Autoregressions," CREATES Research Papers 2012-38, Department of Economics and Business Economics, Aarhus University.
    12. Anna Almosova & Niek Andresen, 2023. "Nonlinear inflation forecasting with recurrent neural networks," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(2), pages 240-259, March.
    13. Tea Šestanović & Josip Arnerić, 2021. "Can Recurrent Neural Networks Predict Inflation in Euro Zone as Good as Professional Forecasters?," Mathematics, MDPI, vol. 9(19), pages 1-13, October.
    14. Håvard Hungnes, 2020. "Equal predictability test for multi-step-ahead system forecasts invariant to linear transformations," Discussion Papers 931, Statistics Norway, Research Department.
    15. Håvard Hungnes, 2018. "Encompassing tests for evaluating multi-step system forecasts invariant to linear transformations," Discussion Papers 871, Statistics Norway, Research Department.
    16. Wang, Lu & Ma, Feng & Hao, Jianyang & Gao, Xinxin, 2021. "Forecasting crude oil volatility with geopolitical risk: Do time-varying switching probabilities play a role?," International Review of Financial Analysis, Elsevier, vol. 76(C).
    17. Lee Jinu, 2019. "A Neural Network Method for Nonlinear Time Series Analysis," Journal of Time Series Econometrics, De Gruyter, vol. 11(1), pages 1-18, January.
    18. Daniel Wochner, 2020. "Dynamic Factor Trees and Forests – A Theory-led Machine Learning Framework for Non-Linear and State-Dependent Short-Term U.S. GDP Growth Predictions," KOF Working papers 20-472, KOF Swiss Economic Institute, ETH Zurich.

  29. Anders Bredahl Kock & Timo Teräsvirta, 2010. "Forecasting with nonlinear time series models," CREATES Research Papers 2010-01, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Masayoshi Hayashi, 2012. "Forecasting Welfare Caseloads: The Case of the Japanese Public Assistance Program," CIRJE F-Series CIRJE-F-846, CIRJE, Faculty of Economics, University of Tokyo.
    2. Kock, Anders Bredahl & Teräsvirta, Timo, 2014. "Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009," International Journal of Forecasting, Elsevier, vol. 30(3), pages 616-631.
    3. Jennifer Castle & David Hendry, 2013. "Semi-automatic Non-linear Model selection," Economics Series Working Papers 654, University of Oxford, Department of Economics.
    4. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
    5. Anders Bredahl Kock & Timo Teräsvirta, 2016. "Forecasting Macroeconomic Variables Using Neural Network Models and Three Automated Model Selection Techniques," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1753-1779, December.
    6. Claveria, Oscar & Torra, Salvador, 2014. "Forecasting tourism demand to Catalonia: Neural networks vs. time series models," Economic Modelling, Elsevier, vol. 36(C), pages 220-228.
    7. Ramazan Gencay & Ege Yazgan, 2017. "When Are Wavelets Useful Forecasters?," Working Papers 1704, The Center for Financial Studies (CEFIS), Istanbul Bilgi University.
    8. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2012. "Is there an Optimal Forecast Combination? A Stochastic Dominance Approach to Forecast Combination Puzzle," Working Paper series 17_12, Rimini Centre for Economic Analysis.
    9. Meriam BouAli & Adnen Ben Nasr & Abdelwahed Trabelsi, 2016. "A Nonlinear Approach for Modeling and Forecasting US Business Cycles," International Economic Journal, Taylor & Francis Journals, vol. 30(1), pages 39-74, March.
    10. Oscar Claveria & Salvador Torra, 2013. "“Forecasting Business surveys indicators: neural networks vs. time series models”," IREA Working Papers 201320, University of Barcelona, Research Institute of Applied Economics, revised Nov 2013.
    11. Oscar Claveria & Enric Monte & Salvador Torra, 2015. "“Self-organizing map analysis of agents’ expectations. Different patterns of anticipation of the 2008 financial crisis”," AQR Working Papers 201508, University of Barcelona, Regional Quantitative Analysis Group, revised Mar 2015.
    12. Souhaib Ben Taieb & Rob J Hyndman, 2014. "Boosting multi-step autoregressive forecasts," Monash Econometrics and Business Statistics Working Papers 13/14, Monash University, Department of Econometrics and Business Statistics.
    13. Shahid IQBAL & Maqbool H. SIAL, 2016. "Projections of Inflation Dynamics for Pakistan: GMDH Approach," Journal of Economics and Political Economy, KSP Journals, vol. 3(3), pages 536-559, September.

  30. Andrés González & Kirstin Hubrich & Timo Teräsvirta, 2009. "Forecasting inflation with gradual regime shifts and exogenous information," CREATES Research Papers 2009-03, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Barbara Rossi, 2011. "Advances in Forecasting Under Instability," Working Papers 11-20, Duke University, Department of Economics.
    2. Krüger Fabian & Pohlmeier Winfried & Mokinski Frieder, 2011. "Combining Survey Forecasts and Time Series Models: The Case of the Euribor," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 231(1), pages 63-81, February.
    3. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
    4. Kun Ho Kim, 2016. "Inference of the Trend in a Partially Linear Model with Locally Stationary Regressors," Econometric Reviews, Taylor & Francis Journals, vol. 35(7), pages 1194-1220, August.
    5. Faust, Jon & Wright, Jonathan H., 2013. "Forecasting Inflation," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 2-56, Elsevier.
    6. Matthew T. Holt & Timo Teräsvirta, 2017. "Global Hemispheric Temperatures and Co–Shifting: A Vector Shifting–Mean Autoregressive Analysis," CREATES Research Papers 2017-05, Department of Economics and Business Economics, Aarhus University.
    7. Dominique Guegan & Patrick Rakotomarolahy, 2009. "The Multivariate k-Nearest Neighbor Model for Dependent Variables : One-Sided Estimation and Forecasting," Post-Print halshs-00423871, HAL.
    8. Matthew T. Holt & Timo Teräsvirta, 2012. "Global Hemispheric Temperature Trends and Co–Shifting: A Shifting Mean Vector Autoregressive Analysis," CREATES Research Papers 2012-54, Department of Economics and Business Economics, Aarhus University.
    9. Emmanuel O. Akande & Elijah O. Akanni & Oyedamola F. Taiwo & Jeremiah D. Joshua & Abel Anthony, 2023. "Predicting inflation component drivers in Nigeria: a stacked ensemble approach," SN Business & Economics, Springer, vol. 3(1), pages 1-32, January.
    10. Belkhouja, Mustapha & Mootamri, Imene, 2016. "Long memory and structural change in the G7 inflation dynamics," Economic Modelling, Elsevier, vol. 54(C), pages 450-462.
    11. Baillie, Richard T. & Morana, Claudio, 2012. "Adaptive ARFIMA models with applications to inflation," Economic Modelling, Elsevier, vol. 29(6), pages 2451-2459.
    12. Claudio Morana, 2013. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks: New Insights on the US OIS SPreads Term Structure," Working Papers 233, University of Milano-Bicocca, Department of Economics, revised Feb 2013.
    13. Kulaksizoglu, Tamer, 2015. "Measuring the Core Inflation in Turkey with the SM-AR Model," MPRA Paper 62653, University Library of Munich, Germany.

  31. Annastiina Silvennoinen & Timo Teräsvirta, 2008. "Modelling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model," CREATES Research Papers 2008-05, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Aslanidis, Nektarios & Christiansen, Charlotte, 2012. "Smooth transition patterns in the realized stock–bond correlation," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 454-464.
    2. Aslanidis, Nektarios & Martínez Ibáñez, Óscar, 2012. "Modelling world investment markets using threshold conditional correlation models," Working Papers 2072/203167, Universitat Rovira i Virgili, Department of Economics.
    3. M.Fatih Oztek & Nadir Ocal, 2013. "Financial Crises, Financialization of Commodity Markets and Correlation of Agricultural Commodity Index with Precious Metal Index and S&P500," ERC Working Papers 1302, ERC - Economic Research Center, Middle East Technical University, revised Feb 2013.
    4. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    5. Asai Manabu & So Mike K.P., 2015. "Long Memory and Asymmetry for Matrix-Exponential Dynamic Correlation Processes," Journal of Time Series Econometrics, De Gruyter, vol. 7(1), pages 69-94, January.
    6. Thieu, Le Quyen, 2016. "Variance targeting estimation of the BEKK-X model," MPRA Paper 75572, University Library of Munich, Germany.
    7. Lee, Chien-Chiang & Chiu, Yi-Bin, 2016. "Globalization and insurance activity: Evidence on the industrial and emerging countries," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 328-349.
    8. Serra, Teresa, 2011. "Food scare crises and price volatility: The case of the BSE in Spain," Food Policy, Elsevier, vol. 36(2), pages 179-185, April.
    9. Gian Piero Aielli, 2011. "Dynamic Conditional Correlation: On properties and estimation," "Marco Fanno" Working Papers 0142, Dipartimento di Scienze Economiche "Marco Fanno".
    10. De Santis, Roberto A. & Stein, Michael, 2016. "Correlation changes between the risk-free rate and sovereign yields of euro area countries," Working Paper Series 1979, European Central Bank.
    11. Ahmed El Ghini & Youssef Saidi, 2015. "Financial market contagion during the global financial crisis: evidence from the Moroccan stock market," International Journal of Financial Markets and Derivatives, Inderscience Enterprises Ltd, vol. 4(1), pages 78-95.
    12. Aslanidis, Nektarios & Savva, Christos S., 2010. "Modelling Interbank Relations during the International Financial Crisis," Working Papers 2072/148475, Universitat Rovira i Virgili, Department of Economics.
    13. Chun-Pin Hsu & Chin-Wen Huang & Wan-Jiun Chiou, 2012. "Effectiveness of copula-extreme value theory in estimating value-at-risk: empirical evidence from Asian emerging markets," Review of Quantitative Finance and Accounting, Springer, vol. 39(4), pages 447-468, November.
    14. Dimitrios D. Thomakos & Fotis Papailias, 2013. "Covariance Averaging for Improved Estimation and Portfolio Allocation," Working Paper series 66_13, Rimini Centre for Economic Analysis.
    15. Christos Savva & Nektarios Aslanidis, 2010. "Stock market integration between new EU member states and the Euro-zone," Empirical Economics, Springer, vol. 39(2), pages 337-351, October.
    16. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008.
    17. Hira Aftab & A. B. M. Rabiul Alam Beg, 2021. "Does Time Varying Risk Premia Exist in the International Bond Market? An Empirical Evidence from Australian and French Bond Market," IJFS, MDPI, vol. 9(1), pages 1-13, January.
    18. Woraphon Yamaka & Paravee Maneejuk, 2020. "Analyzing the Causality and Dependence between Gold Shocks and Asian Emerging Stock Markets: A Smooth Transition Copula Approach," Mathematics, MDPI, vol. 8(1), pages 1-27, January.
    19. Chuffart, Thomas, 2022. "Interest in cryptocurrencies predicts conditional correlation dynamics," Finance Research Letters, Elsevier, vol. 46(PA).
    20. Charlot, Philippe & Darné, Olivier & Moussa, Zakaria, 2016. "Commodity returns co-movements: Fundamentals or “style” effect?," Journal of International Money and Finance, Elsevier, vol. 68(C), pages 130-160.
    21. Audrino, Francesco, 2014. "Forecasting correlations during the late-2000s financial crisis: The short-run component, the long-run component, and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 43-60.
    22. Christos S Savva, 2011. "Modeling interbank relations during the international financial crisis," Economics Bulletin, AccessEcon, vol. 31(1), pages 916-924.
    23. Anne Péguin-Feissolle & Bilel Sanhaji, 2015. "Testing the Constancy of Conditional Correlations in Multivariate GARCH-type Models (Extended Version with Appendix)," AMSE Working Papers 1516, Aix-Marseille School of Economics, France.
    24. Hussain, Saiful Izzuan & Nur-Firyal, R. & Ruza, Nadiah, 2022. "Linkage transitions between oil and the stock markets of countries with the highest COVID-19 cases," Journal of Commodity Markets, Elsevier, vol. 28(C).
    25. Aslanidis, Nektarios & Casas, Isabel, 2011. "Modelling asset correlations: A nonparametric approach," Working Papers 2011-01, University of Sydney, School of Economics.
    26. Manabu Asai, 2013. "Heterogeneous Asymmetric Dynamic Conditional Correlation Model with Stock Return and Range," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 32(5), pages 469-480, August.
    27. Chou, Ray Yeutien & Cai, Yijie, 2009. "Range-based multivariate volatility model with double smooth transition in conditional correlation," Global Finance Journal, Elsevier, vol. 20(2), pages 137-152.
    28. Christos S. Savva & Kyriakos C. Neanidis & Denise R. Osborn, 2007. "Business Cycle Synchronization of the Euro Area with the New and Negotiating Member Countries," Centre for Growth and Business Cycle Research Discussion Paper Series 91, Economics, The University of Manchester.
    29. Christian Conrad & Menelaos Karanasos, 2008. "Negative Volatility Spillovers in the Unrestricted ECCC-GARCH Model," KOF Working papers 08-189, KOF Swiss Economic Institute, ETH Zurich.
    30. Philippe Charlot & Vêlayoudom Marimoutou, 2011. "Hierarchical hidden Markov structure for dynamic correlations: the hierarchical RSDC model (version révisée)," Working Papers hal-00605965, HAL.
    31. Dark, Jonathan, 2024. "An adaptive long memory conditional correlation model," Journal of Empirical Finance, Elsevier, vol. 75(C).
    32. Chelley-Steeley, Patricia & Lambertides, Neophytos & Savva, Christos S., 2013. "Illiquidity shocks and the comovement between stocks: New evidence using smooth transition," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 1-15.
    33. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    34. Christian M. Hafner & Oliver Linton, 2009. "Efficient Estimation of a Multivariate Multiplicative Volatility Model," STICERD - Econometrics Paper Series 541, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    35. Dark, Jonathan, 2015. "Futures hedging with Markov switching vector error correction FIEGARCH and FIAPARCH," Journal of Banking & Finance, Elsevier, vol. 61(S2), pages 269-285.
    36. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with smooth transition in variances," Journal of Economic Dynamics and Control, Elsevier, vol. 84(C), pages 43-57.
    37. Takashi Isogai, 2015. "An Empirical Study of the Dynamic Correlation of Japanese Stock Returns," Bank of Japan Working Paper Series 15-E-7, Bank of Japan.
    38. Nektarios Aslanidis & Isabel Casas, 2010. "Modelling asset correlations during the recent FInancial crisis: A semiparametric approach," CREATES Research Papers 2010-71, Department of Economics and Business Economics, Aarhus University.
    39. Díaz-Hernández, Adán & Constantinou, Nick, 2019. "A multiple regime extension to the Heston–Nandi GARCH(1,1) model," Journal of Empirical Finance, Elsevier, vol. 53(C), pages 162-180.
    40. Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    41. Hussain, Saiful Izzuan & Li, Steven, 2018. "The dependence structure between Chinese and other major stock markets using extreme values and copulas," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 421-437.
    42. Henri Audigé, 2013. "A new approach of contagion based on smooth transition conditional correlation GARCH models: An empirical application to the Greek crisis," Working Papers hal-04141224, HAL.
    43. Park, Keehwan & Fang, Zhongzheng & Ho Ha, Young, 2019. "Stock and bond returns correlation in Korea: Local versus global risk during crisis periods," Journal of Asian Economics, Elsevier, vol. 65(C).
    44. Maria Kasch & Massimiliano Caporin, 2008. "Volatility Threshold Dynamic Conditional Correlations: An International Analysis," "Marco Fanno" Working Papers 0065, Dipartimento di Scienze Economiche "Marco Fanno".
    45. Philippe Charlot & Vêlayoudom Marimoutou, 2008. "Hierarchical hidden Markov structure for dynamic correlations: the hierarchical RSDC model," Working Papers halshs-00285866, HAL.
    46. Annastiina Silvennoinen & Susan Thorp, 2015. "Crude Oil and Agricultural Futures: An Analysis of Correlation Dynamics," NCER Working Paper Series 109, National Centre for Econometric Research.
    47. Cagliesi, Gabriella & Guidi, Francesco, 2021. "A three-tiered nested analytical approach to financial integration: The case of emerging and frontier equity markets," International Review of Financial Analysis, Elsevier, vol. 74(C).
    48. Manh Cuong Dong & Cathy W. S. Chen & Sangyoel Lee & Songsak Sriboonchitta, 2019. "How Strong is the Relationship Among Gold and USD Exchange Rates? Analytics Based on Structural Change Models," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 343-366, January.
    49. Dark, Jonathan, 2018. "Multivariate models with long memory dependence in conditional correlation and volatility," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 162-180.
    50. Van Dijk, Dick & Munandar, Haris & Hafner, Christian, 2011. "The Euro-introduction and non-Euro currencies," LIDAM Reprints ISBA 2011052, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    51. Stein, Michael & Islami, Mevlud & Lindemann, Jens, 2012. "Identifying time variability in stock and interest rate dependence," Discussion Papers 24/2012, Deutsche Bundesbank.
    52. Jose Arreola Hernandez & Sang Hoon Kang & Seong-Min Yoon, 2022. "Spillovers and portfolio optimization of precious metals and global/regional equity markets," Applied Economics, Taylor & Francis Journals, vol. 54(20), pages 2320-2342, April.
    53. Banerjee, Ameet Kumar & Sensoy, Ahmet & Goodell, John W., 2024. "Connectivity and spillover during crises: Highlighting the prominent and growing role of green energy," Energy Economics, Elsevier, vol. 129(C).
    54. Dungey, Mardi & Milunovich, George & Thorp, Susan & Yang, Minxian, 2015. "Endogenous crisis dating and contagion using smooth transition structural GARCH," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 71-79.
    55. M. Fatih Oztek & Nadir Ocal, 2012. "Integration of China Stock Markets with International Stock Markets: An application of Smooth Transition Conditional Correlation with Double Transition Functions," ERC Working Papers 1209, ERC - Economic Research Center, Middle East Technical University, revised Dec 2012.
    56. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    57. Cifarelli, Giulio & Paladino, Giovanna, 2020. "A non-linear analysis of the sovereign bank nexus in the EU," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    58. De Santis, Roberto A. & Stein, Michael, 2015. "Financial indicators signaling correlation changes in sovereign bond markets," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 86-102.
    59. Nurulkamal Masseran & Saiful Izzuan Hussain, 2020. "Copula Modelling on the Dynamic Dependence Structure of Multiple Air Pollutant Variables," Mathematics, MDPI, vol. 8(11), pages 1-15, October.
    60. Silvennoinen, Annastiina & Thorp, Susan, 2013. "Financialization, crisis and commodity correlation dynamics," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 42-65.
    61. Patricia Chelley‐Steeley & Neophytos Lambertides & Christos S. Savva, 2019. "Sentiment, order imbalance, and co‐movement: An examination of shocks to retail and institutional trading activity," European Financial Management, European Financial Management Association, vol. 25(1), pages 116-159, January.
    62. Dimitrios Thomakos & Johannes Klepsch & Dimitris N. Politis, 2020. "Model Free Inference on Multivariate Time Series with Conditional Correlations," Stats, MDPI, vol. 3(4), pages 1-26, November.
    63. Jin, Xin & Maheu, John M., 2016. "Modeling covariance breakdowns in multivariate GARCH," Journal of Econometrics, Elsevier, vol. 194(1), pages 1-23.
    64. Burda Martin, 2015. "Constrained Hamiltonian Monte Carlo in BEKK GARCH with Targeting," Journal of Time Series Econometrics, De Gruyter, vol. 7(1), pages 95-113, January.
    65. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2023. "Building Multivariate Time-Varying Smooth Transition Correlation GARCH Models, with an Application to the Four Largest Australian Banks," Econometrics, MDPI, vol. 11(1), pages 1-37, February.
    66. Pineda, Julián & Cortés, Lina M. & Perote, Javier, 2022. "Financial contagion drivers during recent global crises," Economic Modelling, Elsevier, vol. 117(C).
    67. Thieu, Le Quyen, 2016. "Equation by equation estimation of the semi-diagonal BEKK model with covariates," MPRA Paper 75582, University Library of Munich, Germany.
    68. Aslanidis, Nektarios & Casas, Isabel, 2013. "Nonparametric correlation models for portfolio allocation," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2268-2283.
    69. Harumi Ohmi & Tatsuyoshi Okimoto, 2016. "Trends in stock-bond correlations," Applied Economics, Taylor & Francis Journals, vol. 48(6), pages 536-552, February.
    70. Henri Audigé, 2013. "A new approach of contagion based on smooth transition conditional correlation GARCH models: An empirical application to the Greek crisis," EconomiX Working Papers 2013-2, University of Paris Nanterre, EconomiX.
    71. Adams, Zeno & Füss, Roland & Glück, Thorsten, 2017. "Are correlations constant? Empirical and theoretical results on popular correlation models in finance," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 9-24.
    72. Aslanidis, Nektarios & Dungey, Mardi & Savva, Christos S., 2008. "Progress Towards to Equity Market Integration in Eastern Europe," Working Papers 2072/13265, Universitat Rovira i Virgili, Department of Economics.
    73. Gkanoutas-Leventis, Angelos & Nesvetailova, Anastasia, 2015. "Financialisation, oil and the Great Recession," Energy Policy, Elsevier, vol. 86(C), pages 891-902.
    74. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2021. "Four Australian Banks and the Multivariate Time-Varying Smooth Transition Correlation GARCH model," CREATES Research Papers 2021-13, Department of Economics and Business Economics, Aarhus University.
    75. Nektarios Aslanidis & Denise R. Osborn & Marianne Sensier, 2010. "Co-movements between US and UK stock prices: the role of time-varying conditional correlations," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 366-380.
    76. Amer Ait Sidhoum & Teresa Serra, 2016. "Volatility Spillovers in the Spanish Food Marketing Chain: The Case of Tomato," Agribusiness, John Wiley & Sons, Ltd., vol. 32(1), pages 45-63, January.
    77. Haas, Markus & Liu, Ji-Chun, 2015. "Theory for a Multivariate Markov--switching GARCH Model with an Application to Stock Markets," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112855, Verein für Socialpolitik / German Economic Association.
    78. Demetris Koursaros & Nektarios Michail & Christos Savva, 2021. "Tell me where to stop: thresholds in the bank lending and output growth relationship," Empirical Economics, Springer, vol. 60(4), pages 1845-1873, April.
    79. Chelley-Steeley, Patricia & Lambertides, Neophytos & Savva, Christos S., 2015. "The effect of security and market order flow shocks on co-movement," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 136-155.
    80. Mehmet Fatih Öztek & Nadir Öcal, 2016. "The effects of domestic and international news and volatility on integration of Chinese stock markets with international stock markets," Empirical Economics, Springer, vol. 50(2), pages 317-360, March.
    81. Nicolas Koch, 2014. "Dynamic linkages among carbon, energy and financial markets: a smooth transition approach," Applied Economics, Taylor & Francis Journals, vol. 46(7), pages 715-729, March.

  32. Annastiina Silvennoinen & Timo Teräsvirta, 2008. "Multivariate GARCH models," CREATES Research Papers 2008-06, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Rasmus Søndergaard Pedersen & Anders Rahbek, 2012. "Multivariate Variance Targeting in the BEKK-GARCH Model," Discussion Papers 12-23, University of Copenhagen. Department of Economics.
    2. De Santis, Roberto A. & Sarno, Lucio, 2008. "Assessing the benefits of international portfolio diversification in bonds and stocks," Working Paper Series 883, European Central Bank.
    3. Tansuchat, R. & Chang, C-L. & McAleer, M.J., 2010. "Crude Oil Hedging Strategies Using Dynamic Multivariate GARCH," Econometric Institute Research Papers EI 2010-10, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. David Büttner & Bernd Hayo, 2009. "News and Correlations of CEEC-3 Financial Markets," MAGKS Papers on Economics 200944, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    5. João Caldeira & Guilherme Moura & André A.P. Santos, 2012. "Portfolio optimization using a parsimonious multivariate GARCH model: application to the Brazilian stock market," Economics Bulletin, AccessEcon, vol. 32(3), pages 1848-1857.
    6. Guochang Wang & Wai Keung Li & Ke Zhu, 2018. "New HSIC-based tests for independence between two stationary multivariate time series," Papers 1804.09866, arXiv.org.
    7. Neil Shephard & Kevin Sheppard & Robert F. Engle, 2008. "Fitting vast dimensional time-varying covariance models," Economics Series Working Papers 403, University of Oxford, Department of Economics.
    8. Virbickaitė, Audronė & Ausín, M. Concepción & Galeano, Pedro, 2016. "A Bayesian non-parametric approach to asymmetric dynamic conditional correlation model with application to portfolio selection," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 814-829.
    9. CARPANTIER, Jean - François, 2010. "Commodities inventory effect," LIDAM Discussion Papers CORE 2010040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Tsatsura, Oleg, 2010. "A Smooth Transition GARCH-M Model," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 17(1), pages 45-61.
    11. Jensen, Mark J. & Maheu, John M., 2013. "Bayesian semiparametric multivariate GARCH modeling," Journal of Econometrics, Elsevier, vol. 176(1), pages 3-17.
    12. Roberto Casarin & Marco Tronzano & Domenico Sartore, 2013. "Bayesian Markov Switching Stochastic Correlation Models," Working Papers 2013:11, Department of Economics, University of Venice "Ca' Foscari".
    13. Nick, Sebastian, 2013. "Price Formation and Intertemporal Arbitrage within a Low-Liquidity Framework: Empirical Evidence from European Natural Gas Markets," EWI Working Papers 2013-14, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
    14. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008.
    15. Philippe Charlot & Vêlayoudom Marimoutou, 2014. "On the relationship between the prices of oil and the precious metals: Revisiting with a multivariate regime-switching decision tree," Working Papers hal-00980125, HAL.
    16. Peri, Massimo & Vandone, Daniela & Baldi, Lucia, 2014. "Worldwide Evidences in the Relationships between Agriculture, Energy and Water Sectors," 2014 International European Forum, February 17-21, 2014, Innsbruck-Igls, Austria 199346, International European Forum on System Dynamics and Innovation in Food Networks.
    17. Massimiliano Caporin & Michael McAleer, 2013. "Ten Things You Should Know About DCC," Documentos de Trabajo del ICAE 2013-12, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    18. Jean-François Carpantier & Arnaud Dufays, 2012. "Commodities volatility and the theory of storage," Working Papers hal-01821149, HAL.
    19. Keith Pilbeam & Kjell Langeland, 2015. "Forecasting exchange rate volatility: GARCH models versus implied volatility forecasts," International Economics and Economic Policy, Springer, vol. 12(1), pages 127-142, March.
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    46. David Büttner & Bernd Hayo, 2009. "Determinants of European Stock Market Integration," MAGKS Papers on Economics 200932, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
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    50. Balaev, Alexey, 2014. "The copula based on multivariate t-distribution with vector of degrees of freedom," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 90-110.
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    54. Koenig, P., 2011. "Modelling Correlation in Carbon and Energy Markets," Cambridge Working Papers in Economics 1123, Faculty of Economics, University of Cambridge.
    55. Alan M. Rai, 2013. "The Impact of Policy Initiatives on Credit Spreads during the 2007-09 Financial Crisis," International Journal of Central Banking, International Journal of Central Banking, vol. 9(1), pages 45-104, March.
    56. VAN BELLEGEM, Sébastien, 2011. "Locally stationary volatility modelling," LIDAM Discussion Papers CORE 2011041, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    57. Kwan, Clarence C.Y., 2008. "Estimation error in the average correlation of security returns and shrinkage estimation of covariance and correlation matrices," Finance Research Letters, Elsevier, vol. 5(4), pages 236-244, December.
    58. Adam E Clements & Mark Doolan & Stan Hurn & Ralf Becker, 2012. "Selecting forecasting models for portfolio allocation," NCER Working Paper Series 85, National Centre for Econometric Research.
    59. Avarucci, Marco & Beutner, Eric & Zaffaroni, Paolo, 2013. "On Moment Conditions For Quasi-Maximum Likelihood Estimation Of Multivariate Arch Models," Econometric Theory, Cambridge University Press, vol. 29(3), pages 545-566, June.
    60. Annastiina Silvennoinen & Timo Teräsvirta, 2012. "Modelling conditional correlations of asset returns: A smooth transition approach," CREATES Research Papers 2012-09, Department of Economics and Business Economics, Aarhus University.
    61. Francq, Christian & Zakoian, Jean-Michel, 2010. "QML estimation of a class of multivariate GARCH models without moment conditions on the observed process," MPRA Paper 20779, University Library of Munich, Germany.
    62. Helmut Luetkepohl, 2011. "Vector Autoregressive Models," Economics Working Papers ECO2011/30, European University Institute.
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    64. Noureddine Benlagha & Wael Hemrit, 2018. "The Dynamic and Dependence of Takaful and Conventional Stock Return Behaviours: Evidence from the Insurance Industry in Saudi Arabia," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 25(4), pages 285-323, December.
    65. Gürtler, Marc & Rauh, Ronald, 2013. "Empirical studies in a multivariate non-stationary, nonparametric regression model for financial returns," Working Papers IF43V1, Technische Universität Braunschweig, Institute of Finance.
    66. Tihana ŠKRINJARIĆ & Lidija DEDI & Boško ŠEGO, 2021. "Return and Volatility Spillover between Stock Prices and Exchange Rates in Croatia: A Spillover Methodology Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 93-108, December.
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    68. Serra, Teresa, 2012. "Biofuel-related price volatility literature: a review and new approaches," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126057, International Association of Agricultural Economists.
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  33. Christina Amado & Timo Teräsvirta, 2008. "Modelling Conditional and Unconditional Heteroskedasticity with Smoothly Time-Varying Structure," CREATES Research Papers 2008-08, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Matteo Barigozzi & Christian T. Brownlees & Giampiero M. Gallo & David Veredas, 2010. "Disentangling Systematic and Idiosyncratic Risk for Large Panels of Assets," Econometrics Working Papers Archive wp2010_06, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    2. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    3. Claudio Morana, 2010. "Heteroskedastic Factor Vector Autoregressive Estimation of Persistent and Non Persistent Processes Subject to Structural Breaks," ICER Working Papers - Applied Mathematics Series 36-2010, ICER - International Centre for Economic Research.
    4. Claudio Morana, 2014. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks," Working Papers 273, University of Milano-Bicocca, Department of Economics, revised May 2014.
    5. Rohan, Neelabh, 2013. "A time varying GARCH(p,q) model and related statistical inference," Statistics & Probability Letters, Elsevier, vol. 83(9), pages 1983-1990.
    6. Frijns, Bart & Lehnert, Thorsten & Zwinkels, Remco C.J., 2011. "Modeling structural changes in the volatility process," Journal of Empirical Finance, Elsevier, vol. 18(3), pages 522-532, June.
    7. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    8. Cristina Amado & Timo Teräsvirta, 2012. "Modelling Changes in the Unconditional Variance of Long Stock Return Series," CREATES Research Papers 2012-07, Department of Economics and Business Economics, Aarhus University.
    9. Silvennoinen Annastiina & Teräsvirta Timo, 2016. "Testing constancy of unconditional variance in volatility models by misspecification and specification tests," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 347-364, September.
    10. Martínez-García Enrique, 2018. "Modeling time-variation over the business cycle (1960–2017): an international perspective," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-25, December.
    11. Adnen Ben Nasr & Ahdi N. Ajmi & Rangan Gupta, 2013. "Modeling the Volatility of the Dow Jones Islamic Market World Index Using a Fractionally Integrated Time Varying GARCH (FITVGARCH) Model," Working Papers 201357, University of Pretoria, Department of Economics.
    12. Alexandre, Fernando & Portela, Miguel & Sá, Carla, 2008. "Admission Conditions and Graduates' Employability," IZA Discussion Papers 3530, Institute of Labor Economics (IZA).
    13. BAUWENS, Luc & DUFAYS, Arnaud & DE BACKER, Bruno, 2011. "Estimating and forecasting structural breaks in financial time series," LIDAM Discussion Papers CORE 2011055, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    14. Mazur Błażej & Pipień Mateusz, 2018. "Time-varying asymmetry and tail thickness in long series of daily financial returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-21, December.
    15. Giampiero M. Gallo & Edoardo Otranto, 2018. "Combining sharp and smooth transitions in volatility dynamics: a fuzzy regime approach," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 67(3), pages 549-573, April.
    16. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    17. Amendola, Alessandra & Candila, Vincenzo & Gallo, Giampiero M., 2021. "Choosing the frequency of volatility components within the Double Asymmetric GARCH–MIDAS–X model," Econometrics and Statistics, Elsevier, vol. 20(C), pages 12-28.
    18. Amendola, A. & Candila, V. & Cipollini, F. & Gallo, G.M., 2024. "Doubly multiplicative error models with long- and short-run components," Socio-Economic Planning Sciences, Elsevier, vol. 91(C).
    19. Chen, Cathy W.S. & Gerlach, Richard & Lin, Edward M.H., 2014. "Bayesian estimation of smoothly mixing time-varying parameter GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 194-209.
    20. Philippe Charlot & Vêlayoudom Marimoutou, 2008. "Hierarchical hidden Markov structure for dynamic correlations: the hierarchical RSDC model," Working Papers halshs-00285866, HAL.
    21. Błażej Mazur & Mateusz Pipień, 2012. "On the Empirical Importance of Periodicity in the Volatility of Financial Returns - Time Varying GARCH as a Second Order APC(2) Process," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 4(2), pages 95-116, June.
    22. Paulo Bastos & Natália P. Monteiro, 2011. "Managers and Wage Policies," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 20(4), pages 957-984, December.
    23. Belkhouja, Mustapha & Mootamri, Imene, 2016. "Long memory and structural change in the G7 inflation dynamics," Economic Modelling, Elsevier, vol. 54(C), pages 450-462.
    24. Vincenzo Candila & Oguzhan Cepni & Giampiero M. Gallo & Rangan Gupta, 2024. "Influence of Local and Global Economic Policy Uncertainty on the Volatility of US State-Level Equity Returns: Evidence from a GARCH-MIDAS Approach with Shrinkage and Cluster Analysis," Working Papers 202437, University of Pretoria, Department of Economics.
    25. Toktam Valizadeh & Saeid Rezakhah & Ferdous Mohammadi Basatini, 2021. "On time‐varying amplitude HGARCH model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2538-2547, April.
    26. Francesco Battaglia & Mattheos K. Protopapas, 2011. "Time‐varying multi‐regime models fitting by genetic algorithms," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(3), pages 237-252, May.
    27. Belkhouja, Mustapha & Boutahary, Mohamed, 2011. "Modeling volatility with time-varying FIGARCH models," Economic Modelling, Elsevier, vol. 28(3), pages 1106-1116, May.
    28. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2017. "Modelling and forecasting WIG20 daily returns," CREATES Research Papers 2017-29, Department of Economics and Business Economics, Aarhus University.
    29. Cristina Amado & Timo Teräsvirta, 2017. "Specification and testing of multiplicative time-varying GARCH models with applications," Econometric Reviews, Taylor & Francis Journals, vol. 36(4), pages 421-446, April.
    30. Claudio Morana, 2013. "Factor Vector Autoregressive Estimation of Heteroskedastic Persistent and Non Persistent Processes Subject to Structural Breaks: New Insights on the US OIS SPreads Term Structure," Working Papers 233, University of Milano-Bicocca, Department of Economics, revised Feb 2013.
    31. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2021. "Four Australian Banks and the Multivariate Time-Varying Smooth Transition Correlation GARCH model," CREATES Research Papers 2021-13, Department of Economics and Business Economics, Aarhus University.
    32. Jian Kang & Johan Stax Jakobsen & Annastiina Silvennoinen & Timo Teräsvirta & Glen Wade, 2022. "A parsimonious test of constancy of a positive definite correlation matrix in a multivariate time-varying GARCH model," CREATES Research Papers 2022-01, Department of Economics and Business Economics, Aarhus University.
    33. BAUWENS, Luc & DE BACKER, Bruno & DUFAYS, Arnaud, 2014. "A Bayesian method of change-point estimation with recurrent regimes: application to GARCH models," LIDAM Reprints CORE 2641, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    34. Adnen Ben Nasr & Mohamed Boutahar & Abdelwahed Trabelsi, 2010. "Fractionally integrated time varying GARCH model," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 19(3), pages 399-430, August.
    35. Christian Conrad & Onno Kleen, 2020. "Two are better than one: Volatility forecasting using multiplicative component GARCH‐MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 19-45, January.

  34. Changli He & Annastiina Silvennoinen & Timo Teräsvirta, 2008. "Parameterizing unconditional skewness in models for financial time series," CREATES Research Papers 2008-07, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
    2. Xue, Wen-Jun & Zhang, Li-Wen, 2017. "Stock return autocorrelations and predictability in the Chinese stock market—Evidence from threshold quantile autoregressive models," Economic Modelling, Elsevier, vol. 60(C), pages 391-401.
    3. Syriopoulos, Theodore & Makram, Beljid & Boubaker, Adel, 2015. "Stock market volatility spillovers and portfolio hedging: BRICS and the financial crisis," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 7-18.
    4. Jeroen V.K. Rombouts & Lars Stentoft, 2009. "Bayesian Option Pricing Using Mixed Normal Heteroskedasticity Models," CREATES Research Papers 2009-07, Department of Economics and Business Economics, Aarhus University.
    5. Constantin ANGHELACHE & Janusz GRABARA & Alexandru MANOLE, 2016. "Using the Dynamic Model ARMA to Forecast the Macroeconomic Evolution," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(1), pages 3-13, January.
    6. Rodríguez, Mª José, 2009. "GARCH models with leverage effect : differences and similarities," DES - Working Papers. Statistics and Econometrics. WS ws090302, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Bent Jesper Christensen & Morten Ørregaard Nielsen & Jie Zhu, 2012. "The impact of financial crises on the risk-return tradeoff and the leverage effect," CREATES Research Papers 2012-19, Department of Economics and Business Economics, Aarhus University.
    8. Timo Terasvirta & Zhenfang Zhao, 2011. "Stylized facts of return series, robust estimates and three popular models of volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 21(1-2), pages 67-94.
    9. Bent Jesper Christensen & Jie Zhu & Morten Ø. Nielsen, 2009. "Long Memory In Stock Market Volatility And The Volatility-in-mean Effect: The Fiegarch-m Model," Working Paper 1207, Economics Department, Queen's University.
    10. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    11. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    12. Wen-Jun Xue & Li-Wen Zhang, 2016. "Stock Return Autocorrelations and Predictability in the Chinese Stock Market: Evidence from Threshold Quantile Autoregressive Models," Working Papers 1605, Florida International University, Department of Economics.
    13. Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    14. Carnero M. Angeles & Pérez Ana, 2021. "Outliers and misleading leverage effect in asymmetric GARCH-type models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(1), pages 1-19, February.
    15. Teräsvirta, Timo, 2006. "An introduction to univariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 646, Stockholm School of Economics.
    16. Nieto, María Rosa, 2008. "Measuring financial risk : comparison of alternative procedures to estimate VaR and ES," DES - Working Papers. Statistics and Econometrics. WS ws087326, Universidad Carlos III de Madrid. Departamento de Estadística.
    17. Carnero, M. Angeles & Pérez, Ana, 2019. "Leverage effect in energy futures revisited," Energy Economics, Elsevier, vol. 82(C), pages 237-252.
    18. Carnero, M. Angeles & León, Angel & Ñíguez, Trino-Manuel, 2023. "Skewness in energy returns: estimation, testing and retain-->implications for tail risk," The Quarterly Review of Economics and Finance, Elsevier, vol. 90(C), pages 178-189.
    19. María José Rodríguez & Esther Ruiz, 2012. "Revisiting Several Popular GARCH Models with Leverage Effect: Differences and Similarities," Journal of Financial Econometrics, Oxford University Press, vol. 10(4), pages 637-668, September.
    20. Morema, Kgotso & Bonga-Bonga, Lumengo, 2018. "The impact of oil and gold price fluctuations on the South African equity market: volatility spillovers and implications for portfolio management," MPRA Paper 87637, University Library of Munich, Germany.
    21. José‐María Montero & Gema Fernández‐Avilés & María‐Carmen García, 2010. "Estimation of Asymmetric Stochastic Volatility Models: Application to Daily Average Prices of Energy Products," International Statistical Review, International Statistical Institute, vol. 78(3), pages 330-347, December.

  35. Anne Péguin-Feissolle & Birgit Strikholm & Timo Teräsvirta, 2008. "Testing the Granger noncausality hypothesis in stationary nonlinear models of unknown functional form," CREATES Research Papers 2008-19, Department of Economics and Business Economics, Aarhus University.

    Cited by:

    1. D. Hristu-Varsakelis & C. Kyrtsou, 2008. "Evidence for Nonlinear Asymmetric Causality in US Inflation, Metal, and Stock Returns," Discrete Dynamics in Nature and Society, Hindawi, vol. 2008, pages 1-7, May.
    2. Daiki Maki & Yasushi Ota, 2019. "Robust tests for ARCH in the presence of the misspecified conditional mean: A comparison of nonparametric approches," Papers 1907.12752, arXiv.org, revised Sep 2019.
    3. Muhammad Abubakr Naeem & Saqib Farid & Safwan Mohd Nor & Syed Jawad Hussain Shahzad, 2021. "Spillover and Drivers of Uncertainty among Oil and Commodity Markets," Mathematics, MDPI, vol. 9(4), pages 1-26, February.
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    6. Saumya Ranjan Dash & Debasish Maitra & Byomakesh Debata & Jitendra Mahakud, 2021. "Economic policy uncertainty and stock market liquidity: Evidence from G7 countries," International Review of Finance, International Review of Finance Ltd., vol. 21(2), pages 611-626, June.
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    10. Dash, Saumya Ranjan & Maitra, Debasish, 2019. "The relationship between emerging and developed market sentiment: A wavelet-based time-frequency analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 22(C), pages 135-150.
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    13. Riza Demirer & Rangan Gupta & Hossein Hassani & Xu Huang, 2020. "Time-Varying Risk Aversion and the Profitability of Carry Trades: Evidence from the Cross-Quantilogram," Economies, MDPI, vol. 8(1), pages 1-12, March.
    14. Anne Péguin-Feissolle & Bilel Sanhaji, 2015. "Testing the Constancy of Conditional Correlations in Multivariate GARCH-type Models (Extended Version with Appendix)," AMSE Working Papers 1516, Aix-Marseille School of Economics, France.
    15. Albulescu, Claudiu Tiberiu & Demirer, Riza & Raheem, Ibrahim D. & Tiwari, Aviral Kumar, 2019. "Does the U.S. economic policy uncertainty connect financial markets? Evidence from oil and commodity currencies," Energy Economics, Elsevier, vol. 83(C), pages 375-388.
    16. François Benhmad, 2011. "A wavelet analysis of oil price volatility dynamic," Economics Bulletin, AccessEcon, vol. 31(1), pages 792-806.
    17. Sheue Li Ong & Chong Mun Ho, 2014. "Testing For Linear And Non-Linear Granger Non-Causality Hypothesis Between Stock And Bond: The Cases Of Malaysia And Singapore," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 59(05), pages 1-18.
    18. Goodwin, Barry K. & Holt, Matthew T. & Prestemon, Jeffrey P., 2019. "Nonlinear exchange rate pass-through in timber products: The case of oriented strand board in Canada and the United States," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    19. Zhang, Xiaoyu & Liu, Yongfu, 2020. "The dynamic impact of international agricultural commodity price fluctuation on Chinese agricultural commodity prices," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 23(3), August.
    20. Markku Lanne & Jani Luoto, 2014. "Noncausal Bayesian Vector Autoregression," CREATES Research Papers 2014-07, Department of Economics and Business Economics, Aarhus University.
    21. Hernandez, Jose Arreola & Shahzad, Syed Jawad Hussain & Sadorsky, Perry & Uddin, Gazi Salah & Bouri, Elie & Kang, Sang Hoon, 2022. "Regime specific spillovers across US sectors and the role of oil price volatility," Energy Economics, Elsevier, vol. 107(C).
    22. Chuffart Thomas & Flachaire Emmanuel & Péguin-Feissolle Anne, 2018. "Testing for misspecification in the short-run component of GARCH-type models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-17, December.
    23. Tiwari, Aviral Kumar & Dar, Arif Billah & Bhanja, Niyati, 2013. "Oil price and exchange rates: A wavelet based analysis for India," Economic Modelling, Elsevier, vol. 31(C), pages 414-422.
    24. Benhmad, François, 2012. "Modeling nonlinear Granger causality between the oil price and U.S. dollar: A wavelet based approach," Economic Modelling, Elsevier, vol. 29(4), pages 1505-1514.
    25. Muhammad Abubakr Naeem & Saqib Farid & Fiza Qureshi & Farhad Taghizadeh‐Hesary, 2023. "Global factors and the transmission between United States and emerging stock markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 3488-3510, October.
    26. Dash, Saumya Ranjan & Maitra, Debasish, 2018. "Does Shariah index hedge against sentiment risk? Evidence from Indian stock market using time–frequency domain approach," Journal of Behavioral and Experimental Finance, Elsevier, vol. 19(C), pages 20-35.
    27. Werner Kristjanpoller R. & Alejandro Sierra C., 2014. "Relationship between the dollar, the price of copper and the IPSA indifferent time scales: An approach through Wavelet," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 17(3), pages 56-85, December.
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    29. Tiwari, Aviral Kumar & Albulescu, Claudiu Tiberiu, 2016. "Oil price and exchange rate in India: Fresh evidence from continuous wavelet approach and asymmetric, multi-horizon Granger-causality tests," Applied Energy, Elsevier, vol. 179(C), pages 272-283.
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  36. Nakatani, Tomoaki & Teräsvirta, Timo, 2007. "Positivity Constraints on the Conditional Variances in the Family of Conditional Correlation GARCH Models," SSE/EFI Working Paper Series in Economics and Finance 675, Stockholm School of Economics, revised 14 Feb 2008.

    Cited by:

    1. Haas, Markus, 2010. "Covariance forecasts and long-run correlations in a Markov-switching model for dynamic correlations," Finance Research Letters, Elsevier, vol. 7(2), pages 86-97, June.
    2. Ngene, Geoffrey & Post, Jordin A. & Mungai, Ann N., 2018. "Volatility and shock interactions and risk management implications: Evidence from the U.S. and frontier markets," Emerging Markets Review, Elsevier, vol. 37(C), pages 181-198.
    3. Tomasz Wozniak, 2015. "Granger-causal analysis of GARCH models: a Bayesian approach," Department of Economics - Working Papers Series 1194, The University of Melbourne.
    4. Karanasos, Menelaos & Xu, Yongdeng & Yfanti, Stavroula, 2017. "Constrained QML Estimation for Multivariate Asymmetric MEM with Spillovers: The Practicality of Matrix Inequalities," Cardiff Economics Working Papers E2017/14, Cardiff University, Cardiff Business School, Economics Section.
    5. Chaudhuri, Kausik & Sen, Rituparna & Tan, Zheng, 2018. "Testing extreme dependence in financial time series," Economic Modelling, Elsevier, vol. 73(C), pages 378-394.
    6. Rasmus Søndergaard Pedersen, 2015. "Inference and testing on the boundary in extended constant conditional correlation GARCH models," Discussion Papers 15-10, University of Copenhagen. Department of Economics.
    7. Palandri, Alessandro, 2015. "Do negative and positive equity returns share the same volatility dynamics?," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 486-505.
    8. Conrad, Christian & Weber, Enzo, 2013. "Measuring Persistence in Volatility Spillovers," Working Papers 0543, University of Heidelberg, Department of Economics.
    9. Ngene, Geoffrey M. & Lee Kim, Yea & Wang, Jinghua, 2019. "Who poisons the pool? Time-varying asymmetric and nonlinear causal inference between low-risk and high-risk bonds markets," Economic Modelling, Elsevier, vol. 81(C), pages 136-147.
    10. M. Angeles Carnero Fernández & M. Hakan Eratalay, 2012. "Estimating VAR-MGARCH models in multiple steps," Working Papers. Serie AD 2012-10, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    11. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    12. Tomasz Wozniak, 2012. "Granger-causal analysis of VARMA-GARCH models," Economics Working Papers ECO2012/19, European University Institute.
    13. Rayadurgam, Vikram Chandramouli & Mangalagiri, Jayasree, 2023. "Does inclusion of GARCH variance in deep learning models improve financial contagion prediction?," Finance Research Letters, Elsevier, vol. 54(C).
    14. López Cabrera, Brenda & Schulz, Franziska, 2013. "Volatility linkages between energy and agricultural commodity prices," SFB 649 Discussion Papers 2013-042, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    15. Haas, Markus & Liu, Ji-Chun, 2015. "Theory for a Multivariate Markov--switching GARCH Model with an Application to Stock Markets," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112855, Verein für Socialpolitik / German Economic Association.

  37. Teräsvirta, Timo & Zhao, Zhenfang, 2007. "Stylized Facts of Return Series, Robust Estimates, and Three Popular Models of Volatility," SSE/EFI Working Paper Series in Economics and Finance 662, Stockholm School of Economics, revised 01 Aug 2007.

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    1. Leovardo Mata Mata & José Antonio Núñez Mora & Ramona Serrano Bautista, 2021. "Multivariate Distribution in the Stock Markets of Brazil, Russia, India, and China," SAGE Open, , vol. 11(2), pages 21582440211, April.
    2. Hanck, Christoph & Demetrescu, Matei & Kruse, Robinson, 2015. "Fixed-b Asymptotics for t-Statistics in the Presence of Time-Varying Volatility," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112916, Verein für Socialpolitik / German Economic Association.
    3. Cristina Amado & Timo Teräsvirta, 2011. "Modelling Volatility by Variance Decomposition," NIPE Working Papers 01/2011, NIPE - Universidade do Minho.
    4. Demetrescu, Matei & Kruse, Robinson, 2015. "Testing heteroskedastic time series for normality," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 113221, Verein für Socialpolitik / German Economic Association.
    5. Pascual, Lorenzo & Fresoli, Diego Eduardo, 2011. "Bootstrap forecast of multivariate VAR models without using the backward representation," DES - Working Papers. Statistics and Econometrics. WS ws113426, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. Christophe Chorro & Dominique Guegan & Florian Ielpo & Hanjarivo Lalaharison, 2014. "Testing for Leverage Effects in the Returns of US Equities," Documents de travail du Centre d'Economie de la Sorbonne 14022r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Jan 2017.
    7. Carnero Fernández, María Ángeles & Pérez, Ana, 2014. "Identification of asymmetric conditional heteroscedasticity in the presence of outliers," DES - Working Papers. Statistics and Econometrics. WS ws141912, Universidad Carlos III de Madrid. Departamento de Estadística.
    8. Christina Amado & Timo Teräsvirta, 2008. "Modelling Conditional and Unconditional Heteroskedasticity with Smoothly Time-Varying Structure," CREATES Research Papers 2008-08, Department of Economics and Business Economics, Aarhus University.
    9. Matei Demetrescu & Christoph Hanck & Robinson Kruse, 2016. "Fixed-b Inference in the Presence of Time-Varying Volatility," CREATES Research Papers 2016-01, Department of Economics and Business Economics, Aarhus University.
    10. Dalla, Violetta, 2015. "Power transformations of absolute returns and long memory estimation," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 1-18.
    11. Haas, Markus, 2009. "Persistence in volatility, conditional kurtosis, and the Taylor property in absolute value GARCH processes," Statistics & Probability Letters, Elsevier, vol. 79(15), pages 1674-1683, August.
    12. Carnero M. Angeles & Pérez Ana, 2021. "Outliers and misleading leverage effect in asymmetric GARCH-type models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 25(1), pages 1-19, February.
    13. Christophe Chorro & Dominique Guegan & Florian Ielpo & Hanjarivo Lalaharison, 2017. "Testing for Leverage Effects in the Returns of US Equities," Post-Print halshs-00973922, HAL.
    14. Li, Qi & Lian, Heng & Zhu, Fukang, 2016. "Robust closed-form estimators for the integer-valued GARCH (1,1) model," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 209-225.
    15. Lee, Eunhee & Han, Doo Bong & Ito, Shoichi & Rodolfo M. Nayga, Jr, 2015. "A common factor of stochastic volatilities between oil and commodity prices," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 205771, Agricultural and Applied Economics Association.
    16. Dave Cliff, 2021. "BBE: Simulating the Microstructural Dynamics of an In-Play Betting Exchange via Agent-Based Modelling," Papers 2105.08310, arXiv.org.
    17. García-Centeno, María del Carmen & Fernández-Avilés, Gema & Montero, José María, 2010. "Asymmetries in the Volatility of Precious Metals Returns: The TA-ARSV Modelling Strategy," The Journal of Economic Asymmetries, Elsevier, vol. 7(1), pages 23-41.
    18. Demetrescu, Matei & Rodrigues, Paulo M.M., 2022. "Residual-augmented IVX predictive regression," Journal of Econometrics, Elsevier, vol. 227(2), pages 429-460.
    19. Antonio Díaz & Gonzalo García-Donato & Andrés Mora-Valencia, 2017. "Risk quantification in turmoil markets," Risk Management, Palgrave Macmillan, vol. 19(3), pages 202-224, August.
    20. Laurie Davies & Walter Kraemer, 2016. "Stylized Facts and Simulating Long Range Financial Data," CESifo Working Paper Series 5796, CESifo.
    21. Carnero, M. Angeles & Pérez, Ana, 2019. "Leverage effect in energy futures revisited," Energy Economics, Elsevier, vol. 82(C), pages 237-252.
    22. Namid R. Stillman & Rory Baggott & Justin Lyon & Jianfei Zhang & Dingqiu Zhu & Tao Chen & Perukrishnen Vytelingum, 2023. "Deep Calibration of Market Simulations using Neural Density Estimators and Embedding Networks," Papers 2311.11913, arXiv.org, revised Nov 2023.
    23. Hachmi Ben Ameur & Zied Ftiti & Fredj Jawadi & Wael Louhichi, 2022. "Measuring extreme risk dependence between the oil and gas markets," Annals of Operations Research, Springer, vol. 313(2), pages 755-772, June.
    24. Christophe Chorro & Dominique Guegan & Florian Ielpo & Hanjarivo Lalaharison, 2014. "Testing for Leverage Effect in Financial Returns," Documents de travail du Centre d'Economie de la Sorbonne 14022, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    25. José‐María Montero & Gema Fernández‐Avilés & María‐Carmen García, 2010. "Estimation of Asymmetric Stochastic Volatility Models: Application to Daily Average Prices of Energy Products," International Statistical Review, International Statistical Institute, vol. 78(3), pages 330-347, December.

  38. Nakatani, Tomoaki & Teräsvirta, Timo, 2007. "Testing for Volatility Interactions in the Constant Conditional Correlation GARCH Model," SSE/EFI Working Paper Series in Economics and Finance 649, Stockholm School of Economics, revised 04 May 2008.

    Cited by:

    1. Haas, Markus, 2010. "Covariance forecasts and long-run correlations in a Markov-switching model for dynamic correlations," Finance Research Letters, Elsevier, vol. 7(2), pages 86-97, June.
    2. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    3. Syriopoulos, Theodore & Makram, Beljid & Boubaker, Adel, 2015. "Stock market volatility spillovers and portfolio hedging: BRICS and the financial crisis," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 7-18.
    4. Ngene, Geoffrey & Post, Jordin A. & Mungai, Ann N., 2018. "Volatility and shock interactions and risk management implications: Evidence from the U.S. and frontier markets," Emerging Markets Review, Elsevier, vol. 37(C), pages 181-198.
    5. Tomasz Wozniak, 2015. "Granger-causal analysis of GARCH models: a Bayesian approach," Department of Economics - Working Papers Series 1194, The University of Melbourne.
    6. Karanasos, Menelaos & Xu, Yongdeng & Yfanti, Stavroula, 2017. "Constrained QML Estimation for Multivariate Asymmetric MEM with Spillovers: The Practicality of Matrix Inequalities," Cardiff Economics Working Papers E2017/14, Cardiff University, Cardiff Business School, Economics Section.
    7. Djamel Kirat & Ibrahim Ahamada, 2009. "The impact of the European Union Emission Trading Scheme on electricity generation sectors," Post-Print halshs-00384496, HAL.
    8. Nakatani, Tomoaki & Teräsvirta, Timo, 2007. "Positivity Constraints on the Conditional Variances in the Family of Conditional Correlation GARCH Models," SSE/EFI Working Paper Series in Economics and Finance 675, Stockholm School of Economics, revised 14 Feb 2008.
    9. Paul Catani & Timo Teräsvirta & Meiqun Yin, 2017. "A Lagrange multiplier test for testing the adequacy of constant conditional correlation GARCH model," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 599-621, October.
    10. E. Otranto, 2024. "A Vector Multiplicative Error Model with Spillover Effects and Co-movements," Working Paper CRENoS 202404, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.
    11. Djamel Kirat & Ibrahim Ahamada, 2009. "The impact of the European Union Emission Trading Scheme on electricity generation sectors," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-00378317, HAL.
    12. Woźniak, Tomasz, 2015. "Testing causality between two vectors in multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 876-894.
    13. Djamel Kirat & Ibrahim Ahamada, 2009. "The impact of the European Union Emission Trading Scheme on electricity generation sectors," Working Papers hal-00378317, HAL.
    14. Agata Kliber, 2014. "The Dynamics of Sovereign Credit Default Swaps and the Evolution of the Financial Crisis in Selected Central European Economies," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 64(4), pages 330-350, September.
    15. Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2024. "Bitcoin halving and the integration of cryptocurrency and forex markets: An analysis of the higher-order moment spillovers," International Review of Economics & Finance, Elsevier, vol. 92(C), pages 302-315.
    16. Siemaszkiewicz Karolina, 2021. "Safe Haven Instruments – A Comparison Between the Global Financial Crisis and the Covid-19 Pandemic," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 25(4), pages 1-16, December.
    17. Rasmus Søndergaard Pedersen, 2015. "Inference and testing on the boundary in extended constant conditional correlation GARCH models," Discussion Papers 15-10, University of Copenhagen. Department of Economics.
    18. Wei, Zhaohao & Chai, Jian & Dong, Jichang & Lu, Quanying, 2022. "Understanding the linkage-dependence structure between oil and gas markets: A new perspective," Energy, Elsevier, vol. 257(C).
    19. Christian Conrad & Menelaos Karanasos, 2008. "Negative Volatility Spillovers in the Unrestricted ECCC-GARCH Model," KOF Working papers 08-189, KOF Swiss Economic Institute, ETH Zurich.
    20. Dahiru A. Balaa & Taro Takimotob, 2017. "Stock markets volatility spillovers during financial crises: A DCC-MGARCH with skewed-t density approach," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 17(1), pages 25-48, March.
    21. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2017. "The kidnapping of Europe: High-order moments' transmission between developed and emerging markets," Emerging Markets Review, Elsevier, vol. 31(C), pages 96-115.
    22. Yuanyuan Hao & Hong Chong Cho, 2022. "Research on the relationship between urban public infrastructure, CO2 emission and economic growth in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(5), pages 7361-7376, May.
    23. Ngene, Geoffrey M. & Lee Kim, Yea & Wang, Jinghua, 2019. "Who poisons the pool? Time-varying asymmetric and nonlinear causal inference between low-risk and high-risk bonds markets," Economic Modelling, Elsevier, vol. 81(C), pages 136-147.
    24. Nadine McCloud & Yongmiao Hong, 2011. "Testing The Structure Of Conditional Correlations In Multivariate Garch Models: A Generalized Cross‐Spectrum Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 991-1037, November.
    25. Xu, Yongdeng, 2024. "Extended multivariate EGARCH model: A model for zero†return and negative spillovers," Cardiff Economics Working Papers E2024/24, Cardiff University, Cardiff Business School, Economics Section.
    26. Yannick Hoga, 2023. "The Estimation Risk in Extreme Systemic Risk Forecasts," Papers 2304.10349, arXiv.org.
    27. N. Taylor & Y. Xu, 2017. "The logarithmic vector multiplicative error model: an application to high frequency NYSE stock data," Quantitative Finance, Taylor & Francis Journals, vol. 17(7), pages 1021-1035, July.
    28. Stavroula Yfanti & Georgios Chortareas & Menelaos Karanasos & Emmanouil Noikokyris, 2022. "A three‐dimensional asymmetric power HEAVY model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 2737-2761, July.
    29. Stahl, Gerhard & Wang, Shaohui & Wendt, Markus, 2011. "Validate Correlation of an ESG: Treasury Yields across," Hannover Economic Papers (HEP) dp-476, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    30. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    31. Fengler, Matthias R. & Herwartz, Helmut, 2015. "Measuring spot variance spillovers when (co)variances are time-varying - the case of multivariate GARCH models," MPRA Paper 72197, University Library of Munich, Germany, revised 10 Jun 2016.
    32. Rub'en Loaiza-Maya & Michael S. Smith & Worapree Maneesoonthorn, 2017. "Time Series Copulas for Heteroskedastic Data," Papers 1701.07152, arXiv.org.
    33. Tomasz Wozniak, 2012. "Granger-causal analysis of VARMA-GARCH models," Economics Working Papers ECO2012/19, European University Institute.
    34. Jose Fernandez & Bruce Morley, 2015. "Interdependence among Agricultural Commodity Markets, Macroeconomic Factors, Crude Oil and Commodity Index," Department of Economics Working Papers 42/15, University of Bath, Department of Economics.
    35. Francq, Christian & Zakoian, Jean-Michel, 2010. "QML estimation of a class of multivariate GARCH models without moment conditions on the observed process," MPRA Paper 20779, University Library of Munich, Germany.
    36. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2024. "Macro‐financial linkages in the high‐frequency domain: Economic fundamentals and the Covid‐induced uncertainty channel in US and UK financial markets," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(2), pages 1581-1608, April.
    37. Xu, Yongdeng, 2022. "The Exponential HEAVY Model: An Improved Approach to Volatility Modeling and Forecasting," Cardiff Economics Working Papers E2022/5, Cardiff University, Cardiff Business School, Economics Section.
    38. Anindya Chakrabarty & Anupam De & Gautam Bandyopadhyay, 2015. "A Wavelet-based MRA-EDCC-GARCH Methodology for the Detection of News and Volatility Spillover across Sectoral Indices—Evidence from the Indian Financial Market," Global Business Review, International Management Institute, vol. 16(1), pages 35-49, February.
    39. Paolella, Marc S. & Polak, Paweł, 2015. "ALRIGHT: Asymmetric LaRge-scale (I)GARCH with Hetero-Tails," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 282-297.
    40. López Cabrera, Brenda & Schulz, Franziska, 2013. "Volatility linkages between energy and agricultural commodity prices," SFB 649 Discussion Papers 2013-042, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    41. Ryuta Sakemoto, 2018. "The intertemporal relation between expected returns and conditional correlations between precious metals and the stock market," Economics and Business Letters, Oviedo University Press, vol. 7(1), pages 24-35.
    42. Aaron D. Smallwood, 2022. "Inference in Misspecified GARCH‐M Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 84(2), pages 334-355, April.
    43. Jiménez, Inés & Mora-Valencia, Andrés & Perote, Javier, 2023. "Multivariate dynamics between emerging markets and digital asset markets: An application of the SNP-DCC model," Emerging Markets Review, Elsevier, vol. 56(C).
    44. Arif Orçun Söylemez, 2013. "Stock Exchange Volatility Transmissions between Turkey and the Major Financial Centers," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 1(2), pages 27-32.
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    46. Niklas Ahlgren & Paul Catani, 2017. "Wild bootstrap tests for autocorrelation in vector autoregressive models," Statistical Papers, Springer, vol. 58(4), pages 1189-1216, December.
    47. Haas, Markus & Liu, Ji-Chun, 2015. "Theory for a Multivariate Markov--switching GARCH Model with an Application to Stock Markets," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112855, Verein für Socialpolitik / German Economic Association.
    48. Yfanti, Stavroula & Karanasos, Menelaos & Zopounidis, Constantin & Christopoulos, Apostolos, 2023. "Corporate credit risk counter-cyclical interdependence: A systematic analysis of cross-border and cross-sector correlation dynamics," European Journal of Operational Research, Elsevier, vol. 304(2), pages 813-831.
    49. M. Karanasos & S. Yfanti & A. Christopoulos, 2021. "The long memory HEAVY process: modeling and forecasting financial volatility," Annals of Operations Research, Springer, vol. 306(1), pages 111-130, November.
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  39. Teräsvirta, Timo, 2006. "An introduction to univariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 646, Stockholm School of Economics.

    Cited by:

    1. Jie Zhu, 2008. "FIEGARCH-M and and International Crises: A Cross-Country Analysis," CREATES Research Papers 2008-16, Department of Economics and Business Economics, Aarhus University.
    2. CARPANTIER, Jean - François, 2010. "Commodities inventory effect," LIDAM Discussion Papers CORE 2010040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Kee Tuan Teng & Siew Hwa Yen & Soo Y. Chua & Hooi Hooi Lean, 2016. "Time-Varying Linkages of Economic Activities in China and the Stock Markets in ASEAN-5," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 10(2), June.
    4. Sunil Kumar & Anand Prakash & Krishna M. Kushawaha, 2017. "What Explains Call Money Rate Spread in India?," Working Papers id:11975, eSocialSciences.
    5. Durrani, Agha & Ongena, Steven & Ponte Marques, Aurea, 2024. "Decoding market reactions: The certification role of EU-wide stress tests," Economic Modelling, Elsevier, vol. 139(C).
    6. Lean, Hooi Hooi & Teng, Kee Tuan, 2013. "Integration of world leaders and emerging powers into the Malaysian stock market: A DCC-MGARCH approach," Economic Modelling, Elsevier, vol. 32(C), pages 333-342.
    7. Grané, Aurea & Veiga, Helena, 2010. "Wavelet-based detection of outliers in financial time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2580-2593, November.
    8. Alizadeh, Amir H. & Gabrielsen, Alexandros, 2013. "Dynamics of credit spread moments of European corporate bond indexes," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3125-3144.
    9. Rubin, Ofir D. & Ihle, Rico & Kachel, Yael & Goodwin, Barry K., 2013. "The impact of violent political conflict on commodity prices: The Israeli food market," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150961, Agricultural and Applied Economics Association.

  40. Timo Terasvirta & Andrés González, 2006. "Modelling autoregressive processes with a shifting mean," Borradores de Economia 420, Banco de la Republica de Colombia.

    Cited by:

    1. Enders, Walter & Holt, Matthew T., 2011. "Breaks, bubbles, booms, and busts: the evolution of primary commodity price fundamentals," MPRA Paper 31461, University Library of Munich, Germany.
    2. Richard T. Baillie & Claudio Morana, 2007. "Modeling Long Memory and Structural Breaks in Conditional Variances: an Adaptive FIGARCH Approach," ICER Working Papers - Applied Mathematics Series 11-2007, ICER - International Centre for Economic Research.
    3. Strikholm, Birgit, 2006. "Determining the number of breaks in a piecewise linear regression model," SSE/EFI Working Paper Series in Economics and Finance 648, Stockholm School of Economics.
    4. Anders Bredahl Kock & Timo Teräsvirta, 2010. "Forecasting with nonlinear time series models," CREATES Research Papers 2010-01, Department of Economics and Business Economics, Aarhus University.
    5. Hubrich, Kirstin & González, Andrés & Teräsvirta, Timo, 2011. "Forecasting inflation with gradual regime shifts and exogenous information," Working Paper Series 1363, European Central Bank.
    6. Matthew T. Holt & Timo Teräsvirta, 2012. "Global Hemispheric Temperature Trends and Co–Shifting: A Shifting Mean Vector Autoregressive Analysis," CREATES Research Papers 2012-54, Department of Economics and Business Economics, Aarhus University.
    7. Mugera, Harriet & Gilbert, Christopher, 2015. "Structural Change in the Relationship Between Energy and Food Prices," 2015 Conference, August 9-14, 2015, Milan, Italy 212505, International Association of Agricultural Economists.
    8. Cushman, David O. & Michael, Nils, 2011. "Nonlinear trends in real exchange rates: A panel unit root test approach," Journal of International Money and Finance, Elsevier, vol. 30(8), pages 1619-1637.
    9. Friedrich, Marina & Lin, Yicong, 2024. "Sieve bootstrap inference for linear time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 239(1).
    10. Håvard Hungnes, 2012. "Testing for co-non-linearity," Discussion Papers 699, Statistics Norway, Research Department.
    11. Kulaksizoglu, Tamer, 2015. "Measuring the Core Inflation in Turkey with the SM-AR Model," MPRA Paper 62653, University Library of Munich, Germany.

  41. Teräsvirta, Timo, 2005. "Univariate nonlinear time series models," SSE/EFI Working Paper Series in Economics and Finance 593, Stockholm School of Economics.

    Cited by:

    1. Kurmaş Akdoğan, 2017. "Unemployment hysteresis and structural change in Europe," Empirical Economics, Springer, vol. 53(4), pages 1415-1440, December.

  42. González, Andrés & Teräsvirta, Timo, 2005. "Simulation-based finite-sample linearity test against smooth transition models," SSE/EFI Working Paper Series in Economics and Finance 603, Stockholm School of Economics.

    Cited by:

    1. Fracasso, Andrea & Vittucci Marzetti, Giuseppe, 2015. "International trade and R&D spillovers," Journal of International Economics, Elsevier, vol. 96(1), pages 138-149.
    2. Andrea Fracasso & Giuseppe Vittucci Marzetti, 2012. "International R&D spillovers, absorptive capacity and relative backwardness: a panel smooth transition regression model," Department of Economics Working Papers 1203, Department of Economics, University of Trento, Italia.
    3. Pavlidis Efthymios G & Paya Ivan & Peel David A, 2010. "Specifying Smooth Transition Regression Models in the Presence of Conditional Heteroskedasticity of Unknown Form," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(3), pages 1-40, May.
    4. Kadilli, Anjeza & Krishnakumar, Jaya, 2022. "Smooth Transition Simultaneous Equation Models," Journal of Economic Dynamics and Control, Elsevier, vol. 145(C).
    5. Waseem Khadim & Saddam Ilyas & Bilal Mehmood, 2016. "Of Inflation and Growth Nexus in BRIMC Economies," International Journal of Economics and Empirical Research (IJEER), The Economics and Social Development Organization (TESDO), vol. 4(1), pages 32-45, January.
    6. Giulio Cainelli & Andrea Fracasso & Giuseppe Vittucci Marzetti, 2012. "Spatial agglomeration and productivity in Italy: a panel smooth transition regression approach," Openloc Working Papers 1204, Public policies and local development.

  43. Strikholm, Birgit & Teräsvirta, Timo, 2005. "Determining the Number of Regimes in a Threshold Autoregressive Model Using Smooth Transition Autoregressions," SSE/EFI Working Paper Series in Economics and Finance 578, Stockholm School of Economics, revised 11 Feb 2005.

    Cited by:

    1. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    2. Chen, Yu-Lun & Yang, J. Jimmy, 2021. "Trader positions in VIX futures," Journal of Empirical Finance, Elsevier, vol. 61(C), pages 1-17.
    3. Birgit Strikholm & Timo Teräsvirta, 2006. "A sequential procedure for determining the number of regimes in a threshold autoregressive model," Econometrics Journal, Royal Economic Society, vol. 9(3), pages 472-491, November.
    4. Mohammad Mirbagherijam, 2014. "Thresholds Effect of Money Growth on Inflation in Iran," International Journal of Academic Research in Business and Social Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Business and Social Sciences, vol. 4(9), pages 319-329, September.
    5. Strikholm, Birgit, 2006. "Determining the number of breaks in a piecewise linear regression model," SSE/EFI Working Paper Series in Economics and Finance 648, Stockholm School of Economics.
    6. Emilio Zanetti Chini, 2013. "Generalizing smooth transition autoregressions," CEIS Research Paper 294, Tor Vergata University, CEIS, revised 25 Sep 2014.
    7. Michael ARTIS & Ana Beatriz C. GALVÃO & Massimiliano MARCELLINO, 2003. "The transmission mechanism in a changing world," Economics Working Papers ECO2003/18, European University Institute.
    8. Jens-Peter Loy & Dieter Pennerstorfer & Daniela Rroshi & Christoph Weiss & Biliana Yontcheva, 2019. "Consumer Information and Price Transmission: Empirical Evidence," Economics working papers 2019-20, Department of Economics, Johannes Kepler University Linz, Austria.
    9. Lazzarini, S. G. & Madalozzo, R. C & Artes, R. & Siqueira, J. O., 2004. "Measuring trust: An experiment in Brazil," Insper Working Papers wpe_42, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    10. Modena, Matteo, 2008. "The term structure and the expectations hypothesis: a threshold model," MPRA Paper 9611, University Library of Munich, Germany.
    11. Chang, Ya-Kai & Chen, Yu-Lun & Chou, Robin K. & Gau, Yin-Feng, 2013. "The effectiveness of position limits: Evidence from the foreign exchange futures markets," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4501-4509.
    12. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    13. Shahbaba Babak, 2009. "Discovering Hidden Structures Using Mixture Models: Application to Nonlinear Time Series Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(2), pages 1-21, May.
    14. Bilgili, Faik, 2012. "Linear and nonlinear TAR panel unit root analyses for solid biomass energy supply of European countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(9), pages 6775-6781.
    15. Ana Beatriz C. Galvao, 2006. "Structural break threshold VARs for predicting US recessions using the spread," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 463-487.
    16. Ana Beatriz C. Galvão, 2006. "Structural break threshold VARs for predicting US recessions using the spread," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 463-487, May.
    17. Jean-Marc Le Caillec, 2021. "Threshold autoregressive model blind identification based on array clustering," Post-Print hal-03210735, HAL.

  44. Silvennoinen, Annastiina & Teräsvirta, Timo, 2005. "Multivariate Autoregressive Conditional Heteroskedasticity with Smooth Transitions in Conditional Correlations," SSE/EFI Working Paper Series in Economics and Finance 577, Stockholm School of Economics, revised 01 Oct 2005.

    Cited by:

    1. Aslanidis, Nektarios & Martínez Ibáñez, Óscar, 2012. "Modelling world investment markets using threshold conditional correlation models," Working Papers 2072/203167, Universitat Rovira i Virgili, Department of Economics.
    2. M.Fatih Oztek & Nadir Ocal, 2013. "Financial Crises, Financialization of Commodity Markets and Correlation of Agricultural Commodity Index with Precious Metal Index and S&P500," ERC Working Papers 1302, ERC - Economic Research Center, Middle East Technical University, revised Feb 2013.
    3. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    4. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Modelling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH model," SSE/EFI Working Paper Series in Economics and Finance 0652, Stockholm School of Economics.
    5. Dalkir, Mehmet, 2009. "Revisiting stock market index correlations," Finance Research Letters, Elsevier, vol. 6(1), pages 23-33, March.
    6. Serra, Teresa, 2011. "Food scare crises and price volatility: The case of the BSE in Spain," Food Policy, Elsevier, vol. 36(2), pages 179-185, April.
    7. Gian Piero Aielli, 2011. "Dynamic Conditional Correlation: On properties and estimation," "Marco Fanno" Working Papers 0142, Dipartimento di Scienze Economiche "Marco Fanno".
    8. Abdelradi, Fadi & Serra, Teresa, 2015. "Food–energy nexus in Europe: Price volatility approach," Energy Economics, Elsevier, vol. 48(C), pages 157-167.
    9. De Santis, Roberto A. & Stein, Michael, 2016. "Correlation changes between the risk-free rate and sovereign yields of euro area countries," Working Paper Series 1979, European Central Bank.
    10. He, Changli & Kang, Jian & Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Long monthly temperature series and the Vector Seasonal Shifting Mean and Covariance Autoregressive model," Journal of Econometrics, Elsevier, vol. 239(1).
    11. Christos Savva & Nektarios Aslanidis, 2010. "Stock market integration between new EU member states and the Euro-zone," Empirical Economics, Springer, vol. 39(2), pages 337-351, October.
    12. Nakatani, Tomoaki & Teräsvirta, Timo, 2007. "Positivity Constraints on the Conditional Variances in the Family of Conditional Correlation GARCH Models," SSE/EFI Working Paper Series in Economics and Finance 675, Stockholm School of Economics, revised 14 Feb 2008.
    13. Chia-Hao Lee & Shuh-Chyi Doong & Pei-I Chou, 2011. "Dynamic correlation between stock prices and exchange rates," Applied Financial Economics, Taylor & Francis Journals, vol. 21(11), pages 789-800.
    14. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008.
    15. Tomoaki Nakatani & Timo Terasvirta, 2009. "Testing for volatility interactions in the Constant Conditional Correlation GARCH model," Econometrics Journal, Royal Economic Society, vol. 12(1), pages 147-163, March.
    16. Aslanidis, Nektarios & Casas, Isabel, 2011. "Modelling asset correlations: A nonparametric approach," Working Papers 2011-01, University of Sydney, School of Economics.
    17. Chou, Ray Yeutien & Cai, Yijie, 2009. "Range-based multivariate volatility model with double smooth transition in conditional correlation," Global Finance Journal, Elsevier, vol. 20(2), pages 137-152.
    18. Christos S. Savva & Kyriakos C. Neanidis & Denise R. Osborn, 2007. "Business Cycle Synchronization of the Euro Area with the New and Negotiating Member Countries," Centre for Growth and Business Cycle Research Discussion Paper Series 91, Economics, The University of Manchester.
    19. Philippe Charlot & Vêlayoudom Marimoutou, 2011. "Hierarchical hidden Markov structure for dynamic correlations: the hierarchical RSDC model (version révisée)," Working Papers hal-00605965, HAL.
    20. Chelley-Steeley, Patricia & Lambertides, Neophytos & Savva, Christos S., 2013. "Illiquidity shocks and the comovement between stocks: New evidence using smooth transition," Journal of Empirical Finance, Elsevier, vol. 23(C), pages 1-15.
    21. Teresa Serra & José M. Gil, 2013. "Price volatility in food markets: can stock building mitigate price fluctuations?," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 40(3), pages 507-528, July.
    22. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with smooth transition in variances," Journal of Economic Dynamics and Control, Elsevier, vol. 84(C), pages 43-57.
    23. Takashi Isogai, 2015. "An Empirical Study of the Dynamic Correlation of Japanese Stock Returns," Bank of Japan Working Paper Series 15-E-7, Bank of Japan.
    24. Nektarios Aslanidis & Isabel Casas, 2010. "Modelling asset correlations during the recent FInancial crisis: A semiparametric approach," CREATES Research Papers 2010-71, Department of Economics and Business Economics, Aarhus University.
    25. Bauwens, L. & Hafner, C. & Laurent, S., 2012. "Volatility Models," LIDAM Reprints ISBA 2012028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    26. Abdelkader Derbali & Slaheddine Hallara & Aida Sy, 2016. "Athen's game of chicken or the conditional dependence between the Greek banks," Post-Print hal-01696014, HAL.
    27. Bonga-Bonga, Lumengo & Nleya, Lebogang, 2016. "Assessing portfolio market risk in the BRICS economies: use of multivariate GARCH models," MPRA Paper 75809, University Library of Munich, Germany.
    28. Maria Kasch & Massimiliano Caporin, 2008. "Volatility Threshold Dynamic Conditional Correlations: An International Analysis," "Marco Fanno" Working Papers 0065, Dipartimento di Scienze Economiche "Marco Fanno".
    29. Philippe Charlot & Vêlayoudom Marimoutou, 2008. "Hierarchical hidden Markov structure for dynamic correlations: the hierarchical RSDC model," Working Papers halshs-00285866, HAL.
    30. Changli He & Jian Kang & Timo Teräsvirta & Shuhua Zhang, 2019. "Comparing long monthly Chinese and selected European temperature series using the Vector Seasonal Shifting Mean and Covariance Autoregressive model," CREATES Research Papers 2019-19, Department of Economics and Business Economics, Aarhus University.
    31. Cagliesi, Gabriella & Guidi, Francesco, 2021. "A three-tiered nested analytical approach to financial integration: The case of emerging and frontier equity markets," International Review of Financial Analysis, Elsevier, vol. 74(C).
    32. Nadine McCloud & Yongmiao Hong, 2011. "Testing The Structure Of Conditional Correlations In Multivariate Garch Models: A Generalized Cross‐Spectrum Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 991-1037, November.
    33. Van Dijk, Dick & Munandar, Haris & Hafner, Christian, 2011. "The Euro-introduction and non-Euro currencies," LIDAM Reprints ISBA 2011052, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    34. Stein, Michael & Islami, Mevlud & Lindemann, Jens, 2012. "Identifying time variability in stock and interest rate dependence," Discussion Papers 24/2012, Deutsche Bundesbank.
    35. M. Fatih Oztek & Nadir Ocal, 2012. "Integration of China Stock Markets with International Stock Markets: An application of Smooth Transition Conditional Correlation with Double Transition Functions," ERC Working Papers 1209, ERC - Economic Research Center, Middle East Technical University, revised Dec 2012.
    36. Dzanic, Enis & Omerbegovic, Sead, 2014. "Impact Of Volatility And Performance Of Major Stock Markets On Sarajevo Stock Exchange In 2008 – 2012 Period," MPRA Paper 70016, University Library of Munich, Germany.
    37. Serra, Teresa, 2011. "Volatility spillovers between food and energy markets: A semiparametric approach," Energy Economics, Elsevier, vol. 33(6), pages 1155-1164.
    38. Cifarelli, Giulio & Paladino, Giovanna, 2020. "A non-linear analysis of the sovereign bank nexus in the EU," The Journal of Economic Asymmetries, Elsevier, vol. 21(C).
    39. De Santis, Roberto A. & Stein, Michael, 2015. "Financial indicators signaling correlation changes in sovereign bond markets," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 86-102.
    40. Patricia Chelley‐Steeley & Neophytos Lambertides & Christos S. Savva, 2019. "Sentiment, order imbalance, and co‐movement: An examination of shocks to retail and institutional trading activity," European Financial Management, European Financial Management Association, vol. 25(1), pages 116-159, January.
    41. Long, Xiangdong & Su, Liangjun & Ullah, Aman, 2011. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 109-125.
    42. Hafner, C.M. & van Dijk, D.J.C. & Franses, Ph.H.B.F., 2005. "Semi-Parametric Modelling of Correlation Dynamics," Econometric Institute Research Papers EI 2005-26, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    43. Feng, Yuanhua, 2006. "A local dynamic conditional correlation model," MPRA Paper 1592, University Library of Munich, Germany.
    44. Aslanidis, Nektarios & Osborn, Denise R. & Sensier, Marianne, 2008. "Co-movements between US and UK stock prices: the roles of macroeconomic information and time-series varying conditional correlations," Working Papers 2072/8950, Universitat Rovira i Virgili, Department of Economics.
    45. Joseph, Nathan Lael & Lambertides, Neophytos & Savva, Christos S., 2015. "Short-horizon excess returns and exchange rate and interest rate effects," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 37(C), pages 54-76.
    46. Aslanidis, Nektarios & Casas, Isabel, 2013. "Nonparametric correlation models for portfolio allocation," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2268-2283.
    47. Cai, Yijie & Chou, Ray Yeutien & Li, Dan, 2009. "Explaining international stock correlations with CPI fluctuations and market volatility," Journal of Banking & Finance, Elsevier, vol. 33(11), pages 2026-2035, November.
    48. Idier, J., 2008. "Long term vs. short term comovements in stock markets: the use of Markov-switching multifractal models," Working papers 218, Banque de France.
    49. Aslanidis, Nektarios & Dungey, Mardi & Savva, Christos S., 2008. "Progress Towards to Equity Market Integration in Eastern Europe," Working Papers 2072/13265, Universitat Rovira i Virgili, Department of Economics.
    50. Eklund, Bruno & Terasvirta, Timo, 2007. "Testing constancy of the error covariance matrix in vector models," Journal of Econometrics, Elsevier, vol. 140(2), pages 753-780, October.
    51. Jian Kang & Johan Stax Jakobsen & Annastiina Silvennoinen & Timo Teräsvirta & Glen Wade, 2022. "A parsimonious test of constancy of a positive definite correlation matrix in a multivariate time-varying GARCH model," CREATES Research Papers 2022-01, Department of Economics and Business Economics, Aarhus University.
    52. Kosater, Peter, 2006. "Cross-city hedging with weather derivatives using bivariate DCC GARCH models," Discussion Papers in Econometrics and Statistics 2/06, University of Cologne, Institute of Econometrics and Statistics.
    53. Nektarios Aslanidis & Denise R. Osborn & Marianne Sensier, 2008. "Comovements between US and UK stock prices: the roles of macroeconomic information and timevarying conditional correlations," Economics Discussion Paper Series 0805, Economics, The University of Manchester.
    54. Nektarios Aslanidis & Denise R. Osborn & Marianne Sensier, 2010. "Co-movements between US and UK stock prices: the role of time-varying conditional correlations," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 366-380.
    55. Nektarios Aslanidis & Christos S. Savva, 2011. "Are There Still Portfolio Diversification Benefits In Eastern Europe? Aggregate Versus Sectoral Stock Market Data," Manchester School, University of Manchester, vol. 79(6), pages 1323-1352, December.
    56. Campos-Martins, Susana & Amado, Cristina, 2022. "Financial market linkages and the sovereign debt crisis," Journal of International Money and Finance, Elsevier, vol. 123(C).
    57. Chelley-Steeley, Patricia & Lambertides, Neophytos & Savva, Christos S., 2015. "The effect of security and market order flow shocks on co-movement," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 39(C), pages 136-155.
    58. Mehmet Fatih Öztek & Nadir Öcal, 2016. "The effects of domestic and international news and volatility on integration of Chinese stock markets with international stock markets," Empirical Economics, Springer, vol. 50(2), pages 317-360, March.
    59. Xiangdong Long & Liangjun Su & Aman Ullah, 2009. "Estimation and Forecasting of Dynamic Conditional Covariance: A Semiparametric Multivariate Model Variables with Econometric Applications," Working Papers 200908, University of California at Riverside, Department of Economics, revised Jul 2009.
    60. Yang, Jian & Zhou, Yinggang & Wang, Zijun, 2009. "The stock-bond correlation and macroeconomic conditions: One and a half centuries of evidence," Journal of Banking & Finance, Elsevier, vol. 33(4), pages 670-680, April.
    61. Nicolas Koch, 2014. "Dynamic linkages among carbon, energy and financial markets: a smooth transition approach," Applied Economics, Taylor & Francis Journals, vol. 46(7), pages 715-729, March.
    62. Demetris Koursaros & Nektarios A. Michail & Christos S. Savva, 2016. "Bank Lending to the Private Sector and GDP Growth: Thresholds and Returns," Working Papers 2016-2, Central Bank of Cyprus.

  45. Teräsvirta, Timo, 2005. "Forecasting economic variables with nonlinear models," SSE/EFI Working Paper Series in Economics and Finance 598, Stockholm School of Economics, revised 29 Dec 2005.

    Cited by:

    1. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    2. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2018. "Quantile forecast combination using stochastic dominance," Empirical Economics, Springer, vol. 55(4), pages 1717-1755, December.
    3. Exterkate, Peter & Groenen, Patrick J.F. & Heij, Christiaan & van Dijk, Dick, 2016. "Nonlinear forecasting with many predictors using kernel ridge regression," International Journal of Forecasting, Elsevier, vol. 32(3), pages 736-753.
    4. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
    5. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen Miller, 2010. "Forecasting Nevada Gross Gaming Revenue and Taxable Sales Using Coincident and Leading Employment Indexes," Working Papers 15-01, Eastern Mediterranean University, Department of Economics.
    6. Kurmaş Akdoğan, 2017. "Unemployment hysteresis and structural change in Europe," Empirical Economics, Springer, vol. 53(4), pages 1415-1440, December.
    7. Anders Bredahl Kock & Timo Teräsvirta, 2016. "Forecasting Macroeconomic Variables Using Neural Network Models and Three Automated Model Selection Techniques," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1753-1779, December.
    8. de Mello Luiz & Moccero Diego & Mogliani Matteo, 2013. "Do Latin American Central Bankers Behave Non-Linearly? The Experiences of Brazil, Chile, Colombia and Mexico," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(2), pages 141-165, April.
    9. Anders Bredahl Kock & Timo Teräsvirta, 2010. "Forecasting with nonlinear time series models," CREATES Research Papers 2010-01, Department of Economics and Business Economics, Aarhus University.
    10. Aiolfi Marco & Capistrán Carlos & Timmermann Allan, 2010. "Forecast Combinations," Working Papers 2010-04, Banco de México.
    11. Hubrich, Kirstin & González, Andrés & Teräsvirta, Timo, 2011. "Forecasting inflation with gradual regime shifts and exogenous information," Working Paper Series 1363, European Central Bank.
    12. Michel Fliess & Cédric Join, 2013. "Systematic and multifactor risk models revisited," Post-Print hal-00920175, HAL.
    13. Milena Hoyos & Mario Galindo, 2011. "Comparación de los modelos SETAR y STAR para el índice de empleo industrial colombiano," Documentos de Trabajo, Escuela de Economía 8347, Universidad Nacional de Colombia, FCE, CID.
    14. Kurmas Akdogan & Selen Baser & Meltem Gulenay Chadwick & Dilara Ertug & Timur Hulagu & Sevim Kosem & Fethi Ogunc & M. Utku Ozmen & Necati Tekatli, 2012. "Short-Term Inflation Forecasting Models For Turkey and a Forecast Combination Analysis," Working Papers 1209, Research and Monetary Policy Department, Central Bank of the Republic of Turkey.
    15. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2012. "Was the Recent Downturn in US GDP Predictable?," Working papers 2012-38, University of Connecticut, Department of Economics, revised Dec 2013.
    16. E Pavlidis & I Paya & D Peel, 2009. "Forecasting the Real Exchange Rate using a Long Span of Data. A Rematch: Linear vs Nonlinear," Working Papers 601190, Lancaster University Management School, Economics Department.
    17. Mehmet Pinar & Thanasis Stengos & M. Ege Yazgan, 2012. "Is there an Optimal Forecast Combination? A Stochastic Dominance Approach to Forecast Combination Puzzle," Working Paper series 17_12, Rimini Centre for Economic Analysis.
    18. Timmermann, Allan, 2008. "Elusive return predictability," International Journal of Forecasting, Elsevier, vol. 24(1), pages 1-18.
    19. Giancarlo Bruno, 2008. "Forecasting Using Functional Coefficients Autoregressive Models," ISAE Working Papers 98, ISTAT - Italian National Institute of Statistics - (Rome, ITALY).
    20. Gloria González-Rivera & Tae-Hwy Lee, 2007. "Nonlinear Time Series in Financial Forecasting," Working Papers 200803, University of California at Riverside, Department of Economics, revised Feb 2008.
    21. Acatrinei, Marius Cristian & Caraiani, Petre, 2011. "Modeling and Forecasting the Dynamics in Romanian Stock Market Indices Using Threshold Models," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 42-54, June.
    22. Yaya, OlaOluwa S & Ogbonna, Ephraim A & Furuoka, Fumitaka & Gil-Alana, Luis A., 2019. "A new unit root analysis for testing hysteresis in unemployment," MPRA Paper 96621, University Library of Munich, Germany.
    23. Albu, Lucian Liviu & Lupu, Radu & Calin, Cantemir, 2014. "A Nonlinear Model to Estimate the Long Term Correlation between Market Capitalization and GDP per capita in Eastern EU Countries," Working Papers of Institute for Economic Forecasting 141115, Institute for Economic Forecasting.
    24. Peter Exterkate, 2012. "Model Selection in Kernel Ridge Regression," CREATES Research Papers 2012-10, Department of Economics and Business Economics, Aarhus University.
    25. David Alan Peel & Pantelis Promponas, 2016. "Forecasting the nominal exchange rate movements in a changing world. The case of the U.S. and the U.K," Working Papers 144439514, Lancaster University Management School, Economics Department.
    26. Landajo, Manuel & Presno, María José, 2010. "Nonparametric pseudo-Lagrange multiplier stationarity testing," MPRA Paper 25659, University Library of Munich, Germany.
    27. Michel Fliess & C'edric Join, 2013. "Systematic and multifactor risk models revisited," Papers 1312.5271, arXiv.org.

  46. Malmsten, Hans & Teräsvirta, Timo, 2004. "Stylized Facts of Financial Time Series and Three Popular Models of Volatility," SSE/EFI Working Paper Series in Economics and Finance 563, Stockholm School of Economics, revised 03 Sep 2004.

    Cited by:

    1. Josu Arteche, 2012. "Standard and seasonal long memory in volatility: an application to Spanish inflation," Empirical Economics, Springer, vol. 42(3), pages 693-712, June.
    2. Manabu Asai & Michael McAleer & Marcelo C. Medeiros, 2011. "Modelling and Forecasting Noisy Realized Volatility," KIER Working Papers 758, Kyoto University, Institute of Economic Research.
    3. Georgios Bampinas & Konstantinos Ladopoulos & Theodore Panagiotidis, 2018. "A note on the estimated GARCH coefficients from the S&P1500 universe," Applied Economics, Taylor & Francis Journals, vol. 50(34-35), pages 3647-3653, July.
    4. Paulo Ferreira & Andreia Dionísio, "undated". "G7 Stock Markets, Who Is The First To Defeat The Dcca Correlation?," Review of Socio - Economic Perspectives 201605, Reviewsep.
    5. Oleg Korenok & Stanislav Radchenko, 2005. "The smooth transition autoregressive target zone model with the Gaussian stochastic volatility and TGARCH error terms with applications," Working Papers 0505, VCU School of Business, Department of Economics.
    6. Venier, Guido, 2007. "A new Model for Stock Price Movements," MPRA Paper 9146, University Library of Munich, Germany.
    7. Michael McAleer & Marcelo Cunha Medeiros, 2006. "Realized volatility: a review," Textos para discussão 531 Publication status: F, Department of Economics PUC-Rio (Brazil).
    8. Kovačić, Zlatko, 2007. "Forecasting volatility: Evidence from the Macedonian stock exchange," MPRA Paper 5319, University Library of Munich, Germany.
    9. Dalla, Violetta, 2015. "Power transformations of absolute returns and long memory estimation," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 1-18.
    10. Peter Nystrup & Henrik Madsen & Erik Lindstr�m, 2015. "Stylised facts of financial time series and hidden Markov models in continuous time," Quantitative Finance, Taylor & Francis Journals, vol. 15(9), pages 1531-1541, September.
    11. Haas, Markus, 2009. "Persistence in volatility, conditional kurtosis, and the Taylor property in absolute value GARCH processes," Statistics & Probability Letters, Elsevier, vol. 79(15), pages 1674-1683, August.
    12. Teräsvirta, Timo, 2006. "An introduction to univariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 646, Stockholm School of Economics.
    13. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    14. Matos, Paulo & Beviláqua, Giovanni & Filho, Jaime, 2012. "Previsão do câmbio real-dólar sob um arcabouço de apreçamento de ativos," Revista Brasileira de Economia - RBE, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil), vol. 66(3), October.
    15. Matei, Marius, 2011. "Non-Linear Volatility Modeling of Economic and Financial Time Series Using High Frequency Data," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 116-141, June.
    16. Mora Galán, Alberto & Pérez, Ana, 2004. "Stochastic volatility models and the Taylor effect," DES - Working Papers. Statistics and Econometrics. WS ws046315, Universidad Carlos III de Madrid. Departamento de Estadística.
    17. Stavros Stavroyiannis, 2016. "Value-at-Risk and backtesting with the APARCH model and the standardized Pearson type IV distribution," Papers 1602.05749, arXiv.org.
    18. María García Centeno & Román Mínguez Salido, 2009. "Estimation of Asymmetric Stochastic Volatility Models for Stock-Exchange Index Returns," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 15(1), pages 71-87, February.

  47. Meitz, Mika & Teräsvirta, Timo, 2004. "Evaluating models of autoregressive conditional duration," SSE/EFI Working Paper Series in Economics and Finance 557, Stockholm School of Economics, revised 13 Dec 2004.

    Cited by:

    1. Bodnar, Taras & Hautsch, Nikolaus, 2016. "Dynamic conditional correlation multiplicative error processes," Journal of Empirical Finance, Elsevier, vol. 36(C), pages 41-67.
    2. Marcelo Fernandes & Marcelo C. Medeiros & Alvaro Veiga, 2016. "A (Semi)Parametric Functional Coefficient Logarithmic Autoregressive Conditional Duration Model," Econometric Reviews, Taylor & Francis Journals, vol. 35(7), pages 1221-1250, August.
    3. Ng, F.C. & Li, W.K. & Yu, Philip L.H., 2016. "Diagnostic checking of the vector multiplicative error model," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 86-97.
    4. Hallin, Marc & La Vecchia, Davide, 2020. "A Simple R-estimation method for semiparametric duration models," Journal of Econometrics, Elsevier, vol. 218(2), pages 736-749.
    5. Chen, Fei & Diebold, Francis X. & Schorfheide, Frank, 2013. "A Markov-switching multifractal inter-trade duration model, with application to US equities," Journal of Econometrics, Elsevier, vol. 177(2), pages 320-342.
    6. BAUWENS, Luc & HAUTSCH, Nikolaus, 2009. "Modelling financial high frequency data using point processes," LIDAM Reprints CORE 2123, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Nowak, Sylwia & Anderson, Heather M., 2014. "How does public information affect the frequency of trading in airline stocks?," Journal of Banking & Finance, Elsevier, vol. 44(C), pages 26-38.
    8. Helton Saulo & Jeremias Leão & Víctor Leiva & Robert G. Aykroyd, 2019. "Birnbaum–Saunders autoregressive conditional duration models applied to high-frequency financial data," Statistical Papers, Springer, vol. 60(5), pages 1605-1629, October.
    9. Stanislav Anatolyev & Dmitry Shakin, 2006. "Trade intensity in the Russian stock market:dynamics, distribution and determinants," Working Papers w0070, New Economic School (NES).
    10. N. Balakrishna & H. L. Koul & M. Ossiander & L. Sakhanenko, 2019. "Fitting a pth Order Parametric Generalized Linear Autoregressive Multiplicative Error Model," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 81(1), pages 103-122, September.
    11. Zhang Zongxin & Zhang Xiao, 2011. "Trading duration, mutual funds behavior and stock market shock," China Finance Review International, Emerald Group Publishing Limited, vol. 1(3), pages 220-240, July.
    12. Anatolyev, Stanislav, 2009. "Dynamic modeling under linear-exponential loss," Economic Modelling, Elsevier, vol. 26(1), pages 82-89, January.
    13. Mika Meitz & Pentti Saikkonen & University of Helsinki, 2007. "Ergodicity, mixing, and existence of moments of a class of Markov models with applications to GARCH and ACD models," Economics Series Working Papers 327, University of Oxford, Department of Economics.
    14. De Luca, Giovanni & Zuccolotto, Paola, 2006. "Regime-switching Pareto distributions for ACD models," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2179-2191, December.
    15. Yi-Ting Chen, 2008. "A unified approach to standardized-residuals-based correlation tests for GARCH-type models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 111-133.
    16. Patrick W Saart & Jiti Gao & Nam Hyun Kim, 2014. "Econometric Time Series Specification Testing in a Class of Multiplicative Error Models," Monash Econometrics and Business Statistics Working Papers 1/14, Monash University, Department of Econometrics and Business Statistics.
    17. Fernandes, Marcelo & Medeiros, Marcelo C. & Veiga, Alvaro, 2013. "A (semi-)parametric functional coefficient autoregressive conditional duration model," Textos para discussão 343, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    18. Hira L. Koul & Indeewara Perera & Narayana Balakrishna, 2023. "A class of Minimum Distance Estimators in Markovian Multiplicative Error Models," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 87-115, May.
    19. Helton Saulo & Jeremias Leão, 2017. "On log-symmetric duration models applied to high frequency financial data," Economics Bulletin, AccessEcon, vol. 37(2), pages 1089-1097.
    20. Florian Ielpo & Dominique Gúegan, 2009. "Understanding the Importance of the Duration and Size of the Variations of Fed’s Target Rate," The IUP Journal of Monetary Economics, IUP Publications, vol. 0(3-4), pages 44-72, August.
    21. Wolfgang K. Härdle & Nikolaus Hautsch & Andrija Mihoci, 2015. "Local Adaptive Multiplicative Error Models for High‐Frequency Forecasts," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 30(4), pages 529-550, June.
    22. Monteiro, André A., 2009. "The econometrics of randomly spaced financial data: a survey," DES - Working Papers. Statistics and Econometrics. WS ws097924, Universidad Carlos III de Madrid. Departamento de Estadística.
    23. Pipat Wongsaart & Jiti Gao, 2011. "Nonparametric Kernel Testing in Semiparametric Autoregressive Conditional Duration Model," Monash Econometrics and Business Statistics Working Papers 18/11, Monash University, Department of Econometrics and Business Statistics.
    24. Gurgul Henryk & Machno Artur, 2017. "Trade Pattern on Warsaw Stock Exchange and Prediction of Number of Trades," Statistics in Transition New Series, Statistics Poland, vol. 18(1), pages 91-114, March.
    25. Lin, Edward M.H. & Chen, Cathy W.S. & Gerlach, Richard, 2012. "Forecasting volatility with asymmetric smooth transition dynamic range models," International Journal of Forecasting, Elsevier, vol. 28(2), pages 384-399.
    26. Perera, Indeewara & Koul, Hira L., 2017. "Fitting a two phase threshold multiplicative error model," Journal of Econometrics, Elsevier, vol. 197(2), pages 348-367.
    27. Guo, Bin & Li, Shuo, 2018. "Diagnostic checking of Markov multiplicative error models," Economics Letters, Elsevier, vol. 170(C), pages 139-142.
    28. Xiufeng Yan, 2021. "Autoregressive conditional duration modelling of high frequency data," Papers 2111.02300, arXiv.org.
    29. Patrick W. Saart & Jiti Gao & David E. Allen, 2015. "Semiparametric Autoregressive Conditional Duration Model: Theory and Practice," Econometric Reviews, Taylor & Francis Journals, vol. 34(6-10), pages 849-881, December.
    30. Yongmiao Hong & Yoon-Jin Lee, 2007. "Detecting Misspecifications in Autoregressive Conditional Duration Models," CAEPR Working Papers 2007-019, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    31. Henryk Gurgul & Robert Syrek & Christoph Mitterer, 2016. "Price duration versus trading volume in high-frequency data for selected DAX companies," Managerial Economics, AGH University of Science and Technology, Faculty of Management, vol. 17(2), pages 241-260.
    32. Filip Zikes & Vít Bubák, 2006. "Trading Intensity and Intraday Volatility on the Prague Stock Exchange: Evidence from an Autoregressive Conditional Duration Model (in English)," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 56(5-6), pages 223-245, May.
    33. Yong Shi & Wei Dai & Wen Long & Bo Li, 2021. "Improved ACD-based financial trade durations prediction leveraging LSTM networks and Attention Mechanism," Papers 2101.02736, arXiv.org.
    34. Bhatti, Chad R., 2010. "The Birnbaum–Saunders autoregressive conditional duration model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(10), pages 2062-2078.
    35. Ma, Boyuan & Chu, Tingjin & Jin, Zhuo, 2022. "Frequency and severity estimation of cyber attacks using spatial clustering analysis," Insurance: Mathematics and Economics, Elsevier, vol. 106(C), pages 33-45.
    36. Allen, David & Chan, Felix & McAleer, Michael & Peiris, Shelton, 2008. "Finite sample properties of the QMLE for the Log-ACD model: Application to Australian stocks," Journal of Econometrics, Elsevier, vol. 147(1), pages 163-185, November.
    37. Rodrigues, Bruno Dore & Souza, Reinaldo Castro & Stevenson, Maxwell J., 2012. "An analysis of intraday market behaviour before takeover announcements," International Review of Financial Analysis, Elsevier, vol. 21(C), pages 23-32.
    38. Ke, Rui & Lu, Wanbo & Jia, Jing, 2021. "Evaluating multiplicative error models: A residual-based approach," Computational Statistics & Data Analysis, Elsevier, vol. 153(C).
    39. Kalaitzoglou, Iordanis & Ibrahim, Boulis Maher, 2013. "Trading patterns in the European carbon market: The role of trading intensity and OTC transactions," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(4), pages 402-416.
    40. Herrera, Rodrigo & Schipp, Bernhard, 2011. "Extreme value models in a conditional duration intensity framework," SFB 649 Discussion Papers 2011-022, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    41. Bodnar, Taras & Hautsch, Nikolaus, 2013. "Copula-based dynamic conditional correlation multiplicative error processes," CFS Working Paper Series 2013/19, Center for Financial Studies (CFS).
    42. Hautsch, Nikolaus & Jeleskovic, Vahidin, 2008. "Modelling high-frequency volatility and liquidity using multiplicative error models," SFB 649 Discussion Papers 2008-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    43. Ielpo, Florian & Guégan, Dominique, 2006. "An econometric specification of monetary policy dark art," MPRA Paper 1004, University Library of Munich, Germany, revised 07 Oct 2006.
    44. Lee, Sangyeol & Oh, Haejune, 2015. "Entropy test and residual empirical process for autoregressive conditional duration models," Computational Statistics & Data Analysis, Elsevier, vol. 86(C), pages 1-12.
    45. Gao, Jiti & Kim, Nam Hyun & Saart, Patrick W., 2015. "A misspecification test for multiplicative error models of non-negative time series processes," Journal of Econometrics, Elsevier, vol. 189(2), pages 346-359.
    46. Chiang, Min-Hsien & Wang, Li-Min, 2011. "Volatility contagion: A range-based volatility approach," Journal of Econometrics, Elsevier, vol. 165(2), pages 175-189.

  48. Timo Terasvirta, 2004. "A Time Series Model for an Exchange Rate in a Target Zone with Applications," Econometric Society 2004 Australasian Meetings 340, Econometric Society.

    Cited by:

    1. Reitz Stefan & Taylor Mark P., 2013. "The Danish krone-euro exchange rate and Danmark Nationalbank intervention operations," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(3), pages 239-249, May.
    2. Reitz, Stefan & Ruelke, Jan C. & Taylor, Mark P., 2010. "On the nonlinear influence of Reserve Bank of Australia interventions on exchange rates," Discussion Paper Series 1: Economic Studies 2010,08, Deutsche Bundesbank.
    3. Feng, Liming & Jiang, Pingping & Wang, Yongjin, 2020. "Constant elasticity of variance models with target zones," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 537(C).
    4. Lera, Sandro Claudio & Sornette, Didier, 2016. "Quantitative modelling of the EUR/CHF exchange rate during the target zone regime of September 2011 to January 2015," Journal of International Money and Finance, Elsevier, vol. 63(C), pages 28-47.
    5. Donald W. K. Andrews & Xu Cheng, 2011. "Maximum Likelihood Estimation and Uniform Inference with Sporadic Identification Failure," Cowles Foundation Discussion Papers 1824R, Cowles Foundation for Research in Economics, Yale University, revised Oct 2012.
    6. Peter P. Carr & Zura Kakushadze, 2017. "FX options in target zones," Quantitative Finance, Taylor & Francis Journals, vol. 17(10), pages 1477-1486, October.
    7. Tian, Lei & Chen, Langnan, 2013. "A reinvestigation of the new RMB exchange rate regime," China Economic Review, Elsevier, vol. 24(C), pages 16-25.
    8. Fredj Jawadi & Ricardo M. Sousa, 2012. "Money Demand in the euro area, the US and the UK:Assessing the Role of Nonlinearity," NIPE Working Papers 22/2012, NIPE - Universidade do Minho.
    9. Reitz, Stefan & Taylor, Mark P., 2013. "Exchange rates in target zones: Evidence from the Danish Krone," Kiel Working Papers 1827, Kiel Institute for the World Economy (IfW Kiel).
    10. Oleg Korenok & Stanislav Radchenko, 2005. "The smooth transition autoregressive target zone model with the Gaussian stochastic volatility and TGARCH error terms with applications," Working Papers 0505, VCU School of Business, Department of Economics.
    11. Georg H. Strasser, 2010. "The Efficiency of the Global Markets for Final Goods and Productive Capabilities," Boston College Working Papers in Economics 766, Boston College Department of Economics, revised 31 Jan 2012.
    12. Emilio Zanetti Chini, 2013. "Generalizing smooth transition autoregressions," CEIS Research Paper 294, Tor Vergata University, CEIS, revised 25 Sep 2014.
    13. Emilio Zanetti Chini, 2018. "Forecasting dynamically asymmetric fluctuations of the U.S. business cycle," CREATES Research Papers 2018-13, Department of Economics and Business Economics, Aarhus University.
    14. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2012. "Unit roots, nonlinearities and structural breaks," CREATES Research Papers 2012-14, Department of Economics and Business Economics, Aarhus University.
    15. Jes??s Crespo-Cuaresma & Bal??zs ??gert & Ronald MacDonald, 2005. "Non-Linear Exchange Rate Dynamics in Target Zones: A Bumpy Road Towards A Honeymoon Some Evidence from the ERM, ERM2 and Selected New EU Member States," William Davidson Institute Working Papers Series wp771, William Davidson Institute at the University of Michigan.
    16. Yi-Ting Chen, 2008. "A unified approach to standardized-residuals-based correlation tests for GARCH-type models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 111-133.
    17. Oleg Korenok & Stanislav Radchenko, 2005. "Expectations Anchoring in Inflation Targeting Regimes," Working Papers 0503, VCU School of Business, Department of Economics.
    18. Pavlidis Efthymios G & Paya Ivan & Peel David A, 2010. "Specifying Smooth Transition Regression Models in the Presence of Conditional Heteroskedasticity of Unknown Form," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(3), pages 1-40, May.
    19. Hyginus Leon & Serineh Najarian, 2005. "Asymmetric adjustment and nonlinear dynamics in real exchange rates," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 10(1), pages 15-39.
    20. J. Isaac Miller, 2008. "Testing the Bounds: Empirical Behavior of Target Zone Fundamentals," Working Papers 0803, Department of Economics, University of Missouri, revised 15 Apr 2009.
    21. Jeffrey Frankel, 2023. "Estimation of Nonlinear Exchange Rate Dynamics in Evolving Regimes," CID Working Papers 429, Center for International Development at Harvard University.
    22. António Portugal Duarte & João Sousa Andrade & Adelaide Duarte, 2010. "Exchange Rate Target Zones: A Survey of the Literature," GEMF Working Papers 2010-14, GEMF, Faculty of Economics, University of Coimbra.
    23. Luke Lin & Chun I. Lee, 2016. "Central Bank Intervention, Exchange Rate Regime and the Purchasing Power Parity," The World Economy, Wiley Blackwell, vol. 39(8), pages 1256-1274, August.
    24. Viktors Ajevskis, 2011. "A target zone model with the terminal condition of joining a currency area," Applied Economics Letters, Taylor & Francis Journals, vol. 18(13), pages 1273-1278.
    25. Jean-Louis Arcand & Max-Olivier Hongler & Shekhar Hari Kumar & Daniele Rinaldo, 2020. "Can one hear the shape of a target zone?," Papers 2002.00948, arXiv.org, revised Jun 2022.
    26. Andreas Röthig, 2009. "Microeconomic Risk Management and Macroeconomic Stability," Lecture Notes in Economics and Mathematical Systems, Springer, number 978-3-642-01565-6, December.
    27. Kadilli, Anjeza & Krishnakumar, Jaya, 2022. "Smooth Transition Simultaneous Equation Models," Journal of Economic Dynamics and Control, Elsevier, vol. 145(C).
    28. Kevin C. Chua, 2018. "A Model Of Inflation Transmission In An Exchange Rate Target Zone," Bulletin of Economic Research, Wiley Blackwell, vol. 70(3), pages 285-297, July.
    29. Nektarios Aslanidis & Susana Iranzo, 2009. "Environment and development: is there a Kuznets curve for CO2 emissions?," Applied Economics, Taylor & Francis Journals, vol. 41(6), pages 803-810.
    30. Canepa, Alessandra & Chini, Emilio Zanetti, 2016. "Dynamic asymmetries in house price cycles: A generalized smooth transition model," Journal of Empirical Finance, Elsevier, vol. 37(C), pages 91-103.
    31. Stan Hurn & Nicholas Johnson & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Transition from the Taylor rule to the zero lower bound," CREATES Research Papers 2018-31, Department of Economics and Business Economics, Aarhus University.
    32. Kurmaş Akdoğan, 2015. "Asymmetric Behaviour of Inflation around the Target in Inflation-Targeting Countries," Scottish Journal of Political Economy, Scottish Economic Society, vol. 62(5), pages 486-504, November.
    33. Guangli Xu & Shiyu Song & Yongjin Wang, 2016. "The Valuation Of Options On Foreign Exchange Rate In A Target Zone," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 19(03), pages 1-19, May.
    34. Finger, Karl & Reitz, Stefan, 2012. "Effectiveness of central bank intervention on the foreign exchange market," Kiel Policy Brief 46, Kiel Institute for the World Economy (IfW Kiel).
    35. Yang, Jisheng & Wei, Jinbao & Cai, Biqing, 2022. "Quantile unit root inference for panel data with common shocks," Economics Letters, Elsevier, vol. 219(C).

  49. Teräsvirta, Timo & van Dijk, Dick & Medeiros, Marcelo, 2004. "Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination," SSE/EFI Working Paper Series in Economics and Finance 561, Stockholm School of Economics, revised 09 Nov 2004.

    Cited by:

    1. Aslanidis, Nektarios & Christiansen, Charlotte, 2012. "Smooth transition patterns in the realized stock–bond correlation," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 454-464.
    2. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    3. Longo, Luigi & Riccaboni, Massimo & Rungi, Armando, 2022. "A neural network ensemble approach for GDP forecasting," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    4. Teddy, S.D. & Ng, S.K., 2011. "Forecasting ATM cash demands using a local learning model of cerebellar associative memory network," International Journal of Forecasting, Elsevier, vol. 27(3), pages 760-776, July.
    5. Exterkate, Peter & Groenen, Patrick J.F. & Heij, Christiaan & van Dijk, Dick, 2016. "Nonlinear forecasting with many predictors using kernel ridge regression," International Journal of Forecasting, Elsevier, vol. 32(3), pages 736-753.
    6. Tanujit Chakraborty & Ashis Kumar Chakraborty & Munmun Biswas & Sayak Banerjee & Shramana Bhattacharya, 2021. "Unemployment Rate Forecasting: A Hybrid Approach," Computational Economics, Springer;Society for Computational Economics, vol. 57(1), pages 183-201, January.
    7. Kock, Anders Bredahl & Teräsvirta, Timo, 2014. "Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009," International Journal of Forecasting, Elsevier, vol. 30(3), pages 616-631.
    8. Lorenzo Fratoni & Susanna Levantesi & Massimiliano Menzietti, 2022. "Measuring Financial Sustainability and Social Adequacy of the Italian NDC Pension System under the COVID-19 Pandemic," Sustainability, MDPI, vol. 14(23), pages 1-23, December.
    9. Adam Richardson & Thomas van Florenstein Mulder & Tugrul Vehbi, 2018. "Nowcasting New Zealand GDP using machine learning algorithms," CAMA Working Papers 2018-47, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    10. Hinterlang, Natascha & Hollmayr, Josef, 2022. "Classification of monetary and fiscal dominance regimes using machine learning techniques," Journal of Macroeconomics, Elsevier, vol. 74(C).
    11. Medeiros, Marcelo C. & McAleer, Michael & Slottje, Daniel & Ramos, Vicente & Rey-Maquieira, Javier, 2008. "An alternative approach to estimating demand: Neural network regression with conditional volatility for high frequency air passenger arrivals," Journal of Econometrics, Elsevier, vol. 147(2), pages 372-383, December.
    12. Joseph V. Balagtas & Matthew T. Holt, 2009. "The Commodity Terms of Trade, Unit Roots, and Nonlinear Alternatives: A Smooth Transition Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 87-105.
    13. Canepa, Alessandra & Zanetti Chini, Emilio & Alqaralleh, Huthaifa, 2023. "Modelling and Forecasting Energy Market Cycles: A Generalized Smooth Transition Approach," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202318, University of Turin.
    14. Söhnke M. Bartram & Jürgen Branke & Mehrshad Motahari, 2020. "Artificial intelligence in asset management," Working Papers 20202001, Cambridge Judge Business School, University of Cambridge.
    15. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen Miller, 2010. "Forecasting Nevada Gross Gaming Revenue and Taxable Sales Using Coincident and Leading Employment Indexes," Working Papers 15-01, Eastern Mediterranean University, Department of Economics.
    16. Zuzanna Karolak, 2021. "Energy prices forecasting using nonlinear univariate models," Bank i Kredyt, Narodowy Bank Polski, vol. 52(6), pages 577-598.
    17. Ferrara, Laurent & Marcellino, Massimiliano & Mogliani, Matteo, 2015. "Macroeconomic forecasting during the Great Recession: The return of non-linearity?," International Journal of Forecasting, Elsevier, vol. 31(3), pages 664-679.
    18. Vijverberg, Chu-Ping C., 2009. "A time deformation model and its time-varying autocorrelation: An application to US unemployment data," International Journal of Forecasting, Elsevier, vol. 25(1), pages 128-145.
    19. Kurmaş Akdoğan, 2017. "Unemployment hysteresis and structural change in Europe," Empirical Economics, Springer, vol. 53(4), pages 1415-1440, December.
    20. Emilio Zanetti Chini, 2013. "Generalizing smooth transition autoregressions," CEIS Research Paper 294, Tor Vergata University, CEIS, revised 25 Sep 2014.
    21. Anders Bredahl Kock & Timo Teräsvirta, 2016. "Forecasting Macroeconomic Variables Using Neural Network Models and Three Automated Model Selection Techniques," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1753-1779, December.
    22. Vito Polito & Yunyi Zhang, 2021. "Tackling Large Outliers in Macroeconomic Data with Vector Artificial Neural Network Autoregression," CESifo Working Paper Series 9395, CESifo.
    23. Guidolin, Massimo & Hyde, Stuart & McMillan, David & Ono, Sadayuki, 2009. "Non-linear predictability in stock and bond returns: When and where is it exploitable?," International Journal of Forecasting, Elsevier, vol. 25(2), pages 373-399.
    24. Patrick T. kanda & Mehmet Balcilar & Pejman Bahramian & Rangan Gupta, 2014. "Forecasting South African Inflation Using Non-Linear Models: A Weighted Loss-Based Evaluation," Working Papers 201416, University of Pretoria, Department of Economics.
    25. Lasha Kavtaradze & Manouchehr Mokhtari, 2018. "Factor Models And Time†Varying Parameter Framework For Forecasting Exchange Rates And Inflation: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 32(2), pages 302-334, April.
    26. Francq, Christian & Horvath, Lajos & Zakoian, Jean-Michel, 2008. "Sup-tests for linearity in a general nonlinear AR(1) model when the supremum is taken over the full parameter space," MPRA Paper 16669, University Library of Munich, Germany.
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    Cited by:

    1. Tae-Hwy Lee & Weiping Yang, 2014. "Granger-Causality in Quantiles between Financial Markets: Using Copula Approach," Working Papers 201406, University of California at Riverside, Department of Economics.
    2. Dominique Guegan & Jing Zang, 2009. "Pricing bivariate option under GARCH-GH model with dynamic copula: application for Chinese market," The European Journal of Finance, Taylor & Francis Journals, vol. 15(7-8), pages 777-795.
    3. Fantazzini, Dean, 2008. "Econometric Analysis of Financial Data in Risk Management (continuation). Section III: Managing Operational Risk," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 11(3), pages 87-122.
    4. Kim, Gunky & Silvapulle, Mervyn J. & Silvapulle, Paramsothy, 2007. "Comparison of semiparametric and parametric methods for estimating copulas," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2836-2850, March.
    5. Jozef Barun'ik & Tobias Kley, 2015. "Quantile Coherency: A General Measure for Dependence between Cyclical Economic Variables," Papers 1510.06946, arXiv.org, revised Dec 2018.
    6. D. Guegan & J. Zhang, 2010. "Change analysis of a dynamic copula for measuring dependence in multivariate financial data," Quantitative Finance, Taylor & Francis Journals, vol. 10(4), pages 421-430.
    7. Matthias R. Fengler & Helmut Herwartz & Christian Werner, 2012. "A Dynamic Copula Approach to Recovering the Index Implied Volatility Skew," Journal of Financial Econometrics, Oxford University Press, vol. 10(3), pages 457-493, June.
    8. Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation of copula-based semiparametric time series models," Journal of Econometrics, Elsevier, vol. 130(2), pages 307-335, February.
    9. Dominique Guegan & Jing Zhang, 2010. "Change analysis of a dynamic copula for measuring dependence in multivariate financial data," Post-Print halshs-00368334, HAL.
    10. Miguel Carvalho & António Rua, 2014. "Extremal Dependence in International Output Growth: Tales from the Tails," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 76(4), pages 605-620, August.
    11. Dominique Guegan & Jing Zhang, 2009. "Pricing bivariate option under GARCH-GH model with dynamic copula: application for Chinese market," PSE-Ecole d'économie de Paris (Postprint) halshs-00368336, HAL.
    12. Carluccio Bianchi & Alessandro Carta & Dean Fantazzini & Maria Elena De Giuli & Mario A. Maggi, 2009. "A Copula-VAR-X Approach for Industrial Production Modelling and Forecasting," Quaderni di Dipartimento 105, University of Pavia, Department of Economics and Quantitative Methods.
    13. Power, Gabriel J. & Vedenov, Dmitry V., 2008. "The Shape of the Optimal Hedge Ratio: Modeling Joint Spot-Futures Prices using an Empirical Copula-GARCH Model," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37609, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    14. Pérez, Ana & Prieto-Alaiz, Mercedes, 2016. "A note on nonparametric estimation of copula-based multivariate extensions of Spearman’s rho," Statistics & Probability Letters, Elsevier, vol. 112(C), pages 41-50.
    15. Xiaohong Chen & Yanqin Fan & Victor Tsyrennifov, 2004. "Efficient Estimation of Semiparametric Multivariate Copula Models," Vanderbilt University Department of Economics Working Papers 0420, Vanderbilt University Department of Economics.
    16. Gong, Yuting & He, Zhongzhi & Xue, Wenjun, 2022. "EPU spillovers and stock return predictability: A cross-country study," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 78(C).
    17. Dominique Guegan & Jing Zhang, 2010. "Change analysis of a dynamic copula for measuring dependence in multivariate financial data," PSE-Ecole d'économie de Paris (Postprint) halshs-00368334, HAL.
    18. Cyril Caillault & Dominique Guegan, 2009. "Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy," PSE-Ecole d'économie de Paris (Postprint) halshs-00375765, HAL.
    19. Malo, Pekka, 2009. "Modeling electricity spot and futures price dependence: A multifrequency approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(22), pages 4763-4779.
    20. Fantazzini , Dean, 2009. "Econometric Analysis of Financial Data in Risk Management," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 14(2), pages 100-127.
    21. Manner, H. & Candelon, B., 2007. "Testing for asset market linkages: a new approach based on time-varying copulas," Research Memorandum 052, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    22. Param Silvapulle & Xibin Zhang, 2006. "Assessing Dependence Changes in the Asian Financial Market Returns Using Plots Based on Nonparametric Measures," Monash Econometrics and Business Statistics Working Papers 9/06, Monash University, Department of Econometrics and Business Statistics.
    23. Cyril Caillault & Dominique Guegan, 2009. "Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00375765, HAL.
    24. Xiaohong Chen & Yanqin Fan, 2004. "Estimation and Model Selection of Semiparametric Copula-Based Multivariate Dynamic Models under Copula Misspecification," Vanderbilt University Department of Economics Working Papers 0419, Vanderbilt University Department of Economics, revised Sep 2004.
    25. Guoxiang Xu & Wangfeng Gao, 2019. "Financial Risk Contagion in Stock Markets: Causality and Measurement Aspects," Sustainability, MDPI, vol. 11(5), pages 1-20, March.
    26. Wanat, Stanisław & Papież, Monika & Śmiech, Sławomir, 2014. "Causality in distribution between European stock markets and commodity prices: Using independence test based on the empirical copula," MPRA Paper 57706, University Library of Munich, Germany.
    27. Leonidas Tsiaras, 2010. "Dynamic Models of Exchange Rate Dependence Using Option Prices and Historical Returns," CREATES Research Papers 2010-35, Department of Economics and Business Economics, Aarhus University.
    28. Dominique Guegan & Jing Zhang, 2006. "Change analysis of dynamic copula for measuring dependence in multivariate financial data," Post-Print halshs-00189141, HAL.
    29. Dominique Guegan & Jing Zhang, 2009. "Pricing bivariate option under GARCH-GH model with dynamic copula: application for Chinese market," Post-Print halshs-00368336, HAL.
    30. Fantazzini, Dean, 2008. "Credit Risk Management," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 12(4), pages 84-137.
    31. Campbell, Rachel A.J. & Forbes, Catherine S. & Koedijk, Kees G. & Kofman, Paul, 2008. "Increasing correlations or just fat tails?," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 287-309, March.
    32. Xu Wang & Xueyan Wu & Yingying Zhou, 2022. "Conditional Dynamic Dependence and Risk Spillover between Crude Oil Prices and Foreign Exchange Rates: New Evidence from a Dynamic Factor Copula Model," Energies, MDPI, vol. 15(14), pages 1-21, July.
    33. Dominique Guegan & Jing Zhang, 2007. "Pricing bivariate option under GARCH-GH model with dynamic copula : application for Chinese market," Post-Print halshs-00188248, HAL.
    34. Fantazzini, Dean, 2010. "Three-stage semi-parametric estimation of T-copulas: Asymptotics, finite-sample properties and computational aspects," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2562-2579, November.
    35. Robert B. Durand & Markus Junker & Alex Szimayer, 2010. "The flight‐to‐quality effect: a copula‐based analysis," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 50(2), pages 281-299, June.
    36. Chollete, Loran & Ning, Cathy, 2012. "Asymmetric Dependence in the US Economy: Application to Money and the Phillips Curve," UiS Working Papers in Economics and Finance 2012/1, University of Stavanger.
    37. Michał Majsterek & Emilia Gosińska, 2020. "Structural Change in the Deterministic and Stochastic Part of VECM. I(1) and I(2) Case," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 12(4), pages 317-345, December.
    38. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    39. Manner, H., 2007. "Estimation and model selection of copulas with an application to exchange rates," Research Memorandum 056, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    40. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    41. Cyril Caillault & Dominique Guegan, 2009. "Forecasting VaR and Expected Shortfall using Dynamical Systems: A Risk Management Strategy," Post-Print halshs-00375765, HAL.
    42. Wang, Kehluh & Chen, Yi-Hsuan & Huang, Szu-Wei, 2011. "The dynamic dependence between the Chinese market and other international stock markets: A time-varying copula approach," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 654-664, October.

  51. Eklund, Bruno & Teräsvirta, Timo, 2003. "Testing constancy of the error covariance matrix in vector models," SSE/EFI Working Paper Series in Economics and Finance 549, Stockholm School of Economics, revised 18 Jan 2006.

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    1. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    2. Paul Catani & Timo Teräsvirta & Meiqun Yin, 2017. "A Lagrange multiplier test for testing the adequacy of constant conditional correlation GARCH model," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 599-621, October.
    3. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
    4. Tomoaki Nakatani & Timo Terasvirta, 2009. "Testing for volatility interactions in the Constant Conditional Correlation GARCH model," Econometrics Journal, Royal Economic Society, vol. 12(1), pages 147-163, March.
    5. YANG, Yukai, 2014. "Testing constancy of the error covariance matrix in vector models against parametric alternatives using a spectral decomposition," LIDAM Discussion Papers CORE 2014017, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Matthew T. Holt & Timo Teräsvirta, 2017. "Global Hemispheric Temperatures and Co–Shifting: A Vector Shifting–Mean Autoregressive Analysis," CREATES Research Papers 2017-05, Department of Economics and Business Economics, Aarhus University.
    7. Catani, P.S. & Ahlgren, N.J.C., 2017. "Combined Lagrange multiplier test for ARCH in vector autoregressive models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 62-84.
    8. Jian Kang & Johan Stax Jakobsen & Annastiina Silvennoinen & Timo Teräsvirta & Glen Wade, 2022. "A parsimonious test of constancy of a positive definite correlation matrix in a multivariate time-varying GARCH model," CREATES Research Papers 2022-01, Department of Economics and Business Economics, Aarhus University.

  52. He, Changli & Teräsvirta, Timo, 2002. "An application of the analogy between vector ARCH and vector random coefficient autoregressive models," SSE/EFI Working Paper Series in Economics and Finance 516, Stockholm School of Economics.

    Cited by:

    1. Nakatani, Tomoaki & Teräsvirta, Timo, 2007. "Positivity Constraints on the Conditional Variances in the Family of Conditional Correlation GARCH Models," SSE/EFI Working Paper Series in Economics and Finance 675, Stockholm School of Economics, revised 14 Feb 2008.
    2. Tomoaki Nakatani & Timo Terasvirta, 2009. "Testing for volatility interactions in the Constant Conditional Correlation GARCH model," Econometrics Journal, Royal Economic Society, vol. 12(1), pages 147-163, March.
    3. Bollerslev, Tim & Patton, Andrew J. & Quaedvlieg, Rogier, 2020. "Multivariate leverage effects and realized semicovariance GARCH models," Journal of Econometrics, Elsevier, vol. 217(2), pages 411-430.
    4. de Goeij, P. C. & Marquering, W., 2004. "Modeling the conditional covariance between stock and bond returns : A multivariate GARCH approach," Other publications TiSEM 94fe5ada-715a-4339-b94c-f, Tilburg University, School of Economics and Management.
    5. Luc Bauwens & Sébastien Laurent & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109, January.

  53. Granger, Clive W.J. & Teräsvirta, Timo & Patton, Andrew J, 2002. "Common Factors in Conditional Distributions," University of California at San Diego, Economics Working Paper Series qt3bd1n1x5, Department of Economics, UC San Diego.

    Cited by:

    1. Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation of copula-based semiparametric time series models," Journal of Econometrics, Elsevier, vol. 130(2), pages 307-335, February.
    2. Olmo, José, 2005. "Contagion versus flight to quality in financial markets," UC3M Working papers. Economics we051810, Universidad Carlos III de Madrid. Departamento de Economía.

  54. He, Changli & Teräsvirta, Timo & González, Andres, 2002. "Testing parameter constancy in stationary vector autoregressive models against continuous change," SSE/EFI Working Paper Series in Economics and Finance 507, Stockholm School of Economics, revised 11 Jul 2005.

    Cited by:

    1. Zsolt Darvas, 2012. "Monetary transmission in three central European economies- evidence from time-varying coefficient vector autoregressions," Bruegel Working Papers 722, Bruegel.
    2. Terasvirta, Timo & Yang, Yukai, 2014. "Linearity and misspecification tests for vector smooth transition regression models," LIDAM Discussion Papers CORE 2014061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Alejandro López-Vera & Andrés D. Pinchao-Rosero & Norberto Rodríguez-Niño, 2018. "Non-Linear Fiscal Multipliers for Public Expenditure and Tax Revenue in Colombia," Revista ESPE - Ensayos sobre Política Económica, Banco de la Republica de Colombia, vol. 36(85), pages 48-64, April.
    4. Andrés González & Hernán Rincón & Norberto Rodríguez, 2008. "La transmisión de los choques a la tasa de cambio sobre la inflación de los bienes importados en presencia de asimetrías," Borradores de Economia 532, Banco de la Republica de Colombia.
    5. Maertens Odria, Luís Ricardo & Castillo, Paul & Rodriguez, Gabriel, 2012. "Does the exchange rate pass-through into prices change when inflation targeting is adopted? The Peruvian case study between 1994 and 2007," Journal of Macroeconomics, Elsevier, vol. 34(4), pages 1154-1166.
    6. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
    7. Hernán Rincón-Castro & Norberto Rodríguez-Niño, 2018. "Nonlinear state and shock dependence of exchange rate pass through on prices," BIS Working Papers 690, Bank for International Settlements.
    8. Hernán Rincón-Castro & Norberto Rodríguez-Niño, 2016. "Nonlinear Pass-Through of Exchange Rate Shocks on Inflation: A Bayesian Smooth Transition VAR Approach," Borradores de Economia 14299, Banco de la Republica.
    9. Andrés González & Hernán Rincóm & Norberto Rodríguez, 2008. "La transmisión de los choques a la tasa de cambio sobre la inflación," Borradores de Economia 5089, Banco de la Republica.
    10. Hannu Koskinen, 2004. "Modelling of Structural Changes in Demand for Money Cointegration Relations," Finnish Economic Papers, Finnish Economic Association, vol. 17(2), pages 63-72, Autumn.
    11. Li, Dao & He, Changli, 2012. "Testing Common Nonlinear Features in Nonlinear Vector Autoregressive Models," Working Papers 2012:7, Örebro University, School of Business.
    12. Kinnunen, Jyri, 2017. "Dynamic cross-autocorrelation in stock returns," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 162-173.

  55. Medeiros, Marcelo C. & Teräsvirta, Timo & Rech, Gianluigi, 2002. "Building neural network models for time series: A statistical approach," SSE/EFI Working Paper Series in Economics and Finance 508, Stockholm School of Economics.

    Cited by:

    1. Philippe Goulet Coulombe & Maxime Leroux & Dalibor Stevanovic & Stéphane Surprenant, 2019. "How is Machine Learning Useful for Macroeconomic Forecasting?," CIRANO Working Papers 2019s-22, CIRANO.
    2. Michael McAleer & Marcelo Cunha Medeiros, 2010. "Forecasting Realized Volatility with Linear and Nonlinear Models," Textos para discussão 568, Department of Economics PUC-Rio (Brazil).
    3. Exterkate, Peter & Groenen, Patrick J.F. & Heij, Christiaan & van Dijk, Dick, 2016. "Nonlinear forecasting with many predictors using kernel ridge regression," International Journal of Forecasting, Elsevier, vol. 32(3), pages 736-753.
    4. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Working Papers 22-01, Chair in macroeconomics and forecasting, University of Quebec in Montreal's School of Management.
    5. Eduardo Mendes & Alvaro Veiga & MArcelo Cunha Medeiros, 2007. "Estimation And Asymptotic Theory For A New Class Of Mixture Models," Textos para discussão 538, Department of Economics PUC-Rio (Brazil).
    6. McAleer, Michael & Medeiros, Marcelo C. & Slottje, Daniel, 2008. "A neural network demand system with heteroskedastic errors," Journal of Econometrics, Elsevier, vol. 147(2), pages 359-371, December.
    7. Medeiros, Marcelo C. & McAleer, Michael & Slottje, Daniel & Ramos, Vicente & Rey-Maquieira, Javier, 2008. "An alternative approach to estimating demand: Neural network regression with conditional volatility for high frequency air passenger arrivals," Journal of Econometrics, Elsevier, vol. 147(2), pages 372-383, December.
    8. Marcelo Fernandes & Marco Aurélio dos Santos Rocha, 2006. "Are Price Limits on Futures Markets That Cool? Evidence from the Brazilian Mercantile and Futures Exchange," Working Papers 579, Queen Mary University of London, School of Economics and Finance.
    9. Terasvirta, Timo & van Dijk, Dick & Medeiros, Marcelo C., 2005. "Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination," International Journal of Forecasting, Elsevier, vol. 21(4), pages 755-774.
    10. Ari, Didem & Mizrak Ozfirat, Pinar, 2024. "Comparison of artificial neural networks and regression analysis for airway passenger estimation," Journal of Air Transport Management, Elsevier, vol. 115(C).
    11. Anders Bredahl Kock & Timo Teräsvirta, 2016. "Forecasting Macroeconomic Variables Using Neural Network Models and Three Automated Model Selection Techniques," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1753-1779, December.
    12. José Luis Aznarte & Marcelo Cunha Medeiros & José Manuel Benítez Sánchez, 2010. "Linearity Testing Against a Fuzzy Rule-based Model," Textos para discussão 566, Department of Economics PUC-Rio (Brazil).
    13. Vito Polito & Yunyi Zhang, 2021. "Tackling Large Outliers in Macroeconomic Data with Vector Artificial Neural Network Autoregression," CESifo Working Paper Series 9395, CESifo.
    14. Anders Bredahl Kock & Timo Teräsvirta, 2010. "Forecasting with nonlinear time series models," CREATES Research Papers 2010-01, Department of Economics and Business Economics, Aarhus University.
    15. Joel Corrêa da Rosa & Álvaro Veiga & Marcelo C. Medeiros, 2003. "Three-structured smooth transition regression models based on CART algorithm," Textos para discussão 469, Department of Economics PUC-Rio (Brazil).
    16. Arnerić Josip & Poklepović Tea & Teai Juin Wen, 2018. "Neural Network Approach in Forecasting Realized Variance Using High-Frequency Data," Business Systems Research, Sciendo, vol. 9(2), pages 18-34, July.
    17. Thomaidis, Nikolaos S. & Biskas, Pandelis N., 2021. "Fundamental pricing laws and long memory effects in the day-ahead power market," Energy Economics, Elsevier, vol. 100(C).
    18. Ricardo P. Masini & Marcelo C. Medeiros & Eduardo F. Mendes, 2023. "Machine learning advances for time series forecasting," Journal of Economic Surveys, Wiley Blackwell, vol. 37(1), pages 76-111, February.
    19. Mayte Suarez Farinãs & Carlos Eduardo Pedreira & Marcelo C. Medeiros, 2003. "Local-global neural networks: a new approach for nonlinear time series modelling," Textos para discussão 470, Department of Economics PUC-Rio (Brazil).
    20. Francesco Audrino & Marcelo C. Medeiros, 2008. "Smooth Regimes, Macroeconomic Variables, and Bagging for the Short-Term Interest Rate Process," University of St. Gallen Department of Economics working paper series 2008 2008-16, Department of Economics, University of St. Gallen.
    21. He, Changli & Kang, Jian & Teräsvirta, Timo & Zhang, Shuhua, 2019. "The shifting seasonal mean autoregressive model and seasonality in the Central England monthly temperature series, 1772–2016," Econometrics and Statistics, Elsevier, vol. 12(C), pages 1-24.
    22. Craig, Lee A. & Holt, Matthew T., 2008. "Mechanical refrigeration, seasonality, and the hog-corn cycle in the United States: 1870-1940," Explorations in Economic History, Elsevier, vol. 45(1), pages 30-50, January.
    23. M. Ali Choudhary, 2011. "Neural Network Models for Inflation Forecasting: An Appraisal," Post-Print hal-00704670, HAL.
    24. Soares, Lacir J. & Medeiros, Marcelo C., 2008. "Modeling and forecasting short-term electricity load: A comparison of methods with an application to Brazilian data," International Journal of Forecasting, Elsevier, vol. 24(4), pages 630-644.
    25. Souhaib Ben Taieb & Rob J Hyndman, 2014. "Boosting multi-step autoregressive forecasts," Monash Econometrics and Business Statistics Working Papers 13/14, Monash University, Department of Econometrics and Business Statistics.
    26. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    27. Erdem Doğan, 2020. "Analysis of the relationship between LSTM network traffic flow prediction performance and statistical characteristics of standard and nonstandard data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1213-1228, December.
    28. Anesti, Nikoleta & Kalamara, Eleni & Kapetanios, George, 2021. "Forecasting UK GDP growth with large survey panels," Bank of England working papers 923, Bank of England.
    29. Szafranek, Karol, 2019. "Bagged neural networks for forecasting Polish (low) inflation," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1042-1059.
    30. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Regional tourism demand forecasting with machine learning models: Gaussian process regression vs. neural network models in a multiple-input multiple-output setting”," AQR Working Papers 201701, University of Barcelona, Regional Quantitative Analysis Group, revised Jan 2017.
    31. Peter Exterkate, 2012. "Model Selection in Kernel Ridge Regression," CREATES Research Papers 2012-10, Department of Economics and Business Economics, Aarhus University.
    32. Lacir J. Soares & Marcelo Cunha Medeiros, 2005. "Modelling and forecasting short-term electricity load: a two step methodology," Textos para discussão 495, Department of Economics PUC-Rio (Brazil).
    33. Peter Exterkate, 2011. "Modelling Issues in Kernel Ridge Regression," Tinbergen Institute Discussion Papers 11-138/4, Tinbergen Institute.
    34. Philippe Goulet Coulombe, 2022. "A Neural Phillips Curve and a Deep Output Gap," Papers 2202.04146, arXiv.org, revised Oct 2024.
    35. Marcelo de Paiva Abreu, 2003. "The political economy of economic integration in the Americas: Latin American interests," Textos para discussão 468, Department of Economics PUC-Rio (Brazil).
    36. Vince Vella & Wing Lon Ng, 2015. "A Dynamic Fuzzy Money Management Approach for Controlling the Intraday Risk‐Adjusted Performance of AI Trading Algorithms," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 22(2), pages 153-178, April.
    37. Francesco Audrino & Marcelo C. Medeiros, 2011. "Modeling and forecasting short‐term interest rates: The benefits of smooth regimes, macroeconomic variables, and bagging," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 26(6), pages 999-1022, September.
    38. Myladis R. Cogollo & Gilberto González-Parra & Abraham J. Arenas, 2021. "Modeling and Forecasting Cases of RSV Using Artificial Neural Networks," Mathematics, MDPI, vol. 9(22), pages 1-20, November.
    39. Rodriguez, Nestor & Eales, James S., 2015. "Structural Change via Threshold Effects: Estimating U.S. Meat Demand Using Smooth Transition Functions and the Effects of More Women in the Labor Force," 2015 AAEA & WAEA Joint Annual Meeting, July 26-28, San Francisco, California 206522, Agricultural and Applied Economics Association.
    40. Martin Magris, 2019. "A Vine-copula extension for the HAR model," Papers 1907.08522, arXiv.org.
    41. Eric Hillebrand & Marcelo Cunha Medeiros, 2010. "Asymmetries, breaks, and long-range dependence: An estimation framework for daily realized volatility," Textos para discussão 578, Department of Economics PUC-Rio (Brazil).
    42. Rubio, Ginés & Pomares, Héctor & Rojas, Ignacio & Herrera, Luis Javier, 2011. "A heuristic method for parameter selection in LS-SVM: Application to time series prediction," International Journal of Forecasting, Elsevier, vol. 27(3), pages 725-739, July.
    43. da Rosa, Joel Correa & Veiga, Alvaro & Medeiros, Marcelo C., 2008. "Tree-structured smooth transition regression models," Computational Statistics & Data Analysis, Elsevier, vol. 52(5), pages 2469-2488, January.
    44. Tea Šestanović & Josip Arnerić, 2021. "Neural network structure identification in inflation forecasting," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 62-79, January.

  56. He, Changli & Teräsvirta, Timo, 2002. "An Extended Constant Conditional Correlation GARCH Model and Its Fourth-Moment Structure," SSE/EFI Working Paper Series in Economics and Finance 509, Stockholm School of Economics.

    Cited by:

    1. Haas, Markus, 2010. "Covariance forecasts and long-run correlations in a Markov-switching model for dynamic correlations," Finance Research Letters, Elsevier, vol. 7(2), pages 86-97, June.
    2. Markus Haas, 2018. "A note on the absolute moments of the bivariate normal distribution," Economics Bulletin, AccessEcon, vol. 38(1), pages 650-656.
    3. Yuta Kuroda & Takaki Sato & Yasumasa Matsuda, 2024. "The role of prosociality and social capital in changes in subjective well-being during the COVID-19 pandemic," DSSR Discussion Papers 142, Graduate School of Economics and Management, Tohoku University.
    4. Rasmus Søndergaard Pedersen, 2014. "Targeting estimation of CCC-Garch models with infinite fourth moments," Discussion Papers 14-04, University of Copenhagen. Department of Economics.
    5. Syriopoulos, Theodore & Makram, Beljid & Boubaker, Adel, 2015. "Stock market volatility spillovers and portfolio hedging: BRICS and the financial crisis," International Review of Financial Analysis, Elsevier, vol. 39(C), pages 7-18.
    6. Serge Darolles & Christian Francq & Sébastien Laurent, 2017. "Asymptotics of Cholesky GARCH models and time-varying conditional betas," Post-Print hal-04590471, HAL.
    7. Tomasz Wozniak, 2015. "Granger-causal analysis of GARCH models: a Bayesian approach," Department of Economics - Working Papers Series 1194, The University of Melbourne.
    8. Karanasos, Menelaos & Paraskevopoulos,Alexandros & Canepa, Alessandra, 2020. "Unified Theory for the Large Family of Time Varying Models with Arma Representations: One Solution Fits All," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202008, University of Turin.
    9. Karanasos, Menelaos & Xu, Yongdeng & Yfanti, Stavroula, 2017. "Constrained QML Estimation for Multivariate Asymmetric MEM with Spillovers: The Practicality of Matrix Inequalities," Cardiff Economics Working Papers E2017/14, Cardiff University, Cardiff Business School, Economics Section.
    10. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," SSE/EFI Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008.
    11. Christian Francq & Lajos Horváth & Jean-Michel Zakoïan, 2016. "Variance Targeting Estimation of Multivariate GARCH Models," Journal of Financial Econometrics, Oxford University Press, vol. 14(2), pages 353-382.
    12. Woźniak, Tomasz, 2015. "Testing causality between two vectors in multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 876-894.
    13. Eraslan, Sercan & Ali, Faek Menla, 2017. "Financial crises and the dynamic linkages between stock and bond returns," Discussion Papers 17/2017, Deutsche Bundesbank.
    14. Rasmus Søndergaard Pedersen, 2015. "Inference and testing on the boundary in extended constant conditional correlation GARCH models," Discussion Papers 15-10, University of Copenhagen. Department of Economics.
    15. Rei Iwafuchi & Yasumasa Matsuda, 2024. "Deep learning for multivariate volatility forecasting in high-dimensional financial time series," DSSR Discussion Papers 141, Graduate School of Economics and Management, Tohoku University.
    16. Chou, Ray Yeutien & Cai, Yijie, 2009. "Range-based multivariate volatility model with double smooth transition in conditional correlation," Global Finance Journal, Elsevier, vol. 20(2), pages 137-152.
    17. Christian Conrad & Menelaos Karanasos, 2008. "Negative Volatility Spillovers in the Unrestricted ECCC-GARCH Model," KOF Working papers 08-189, KOF Swiss Economic Institute, ETH Zurich.
    18. Caporin, Massimiliano & Malik, Farooq, 2020. "Do structural breaks in volatility cause spurious volatility transmission?," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 60-82.
    19. Boubacar Maïnassara, Y. & Kadmiri, O. & Saussereau, B., 2022. "Estimation of multivariate asymmetric power GARCH models," Journal of Multivariate Analysis, Elsevier, vol. 192(C).
    20. Conrad, Christian & Weber, Enzo, 2013. "Measuring Persistence in Volatility Spillovers," Working Papers 0543, University of Heidelberg, Department of Economics.
    21. Karanasos, Menelaos & Paraskevopoulos, Alexandros & Magdalinos, Anastasios & Canepa, Alessandra, 2024. "A Unified Theory for Arma Models with Varying Coefficients: One Solution Fits All," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202413, University of Turin.
    22. Christian Francq & Jean-Michel Zakoïan, 2016. "Estimating multivariate volatility models equation by equation," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 78(3), pages 613-635, June.
    23. Nadine McCloud & Yongmiao Hong, 2011. "Testing The Structure Of Conditional Correlations In Multivariate Garch Models: A Generalized Cross‐Spectrum Approach," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 52(4), pages 991-1037, November.
    24. Xu, Yongdeng, 2024. "Extended multivariate EGARCH model: A model for zero†return and negative spillovers," Cardiff Economics Working Papers E2024/24, Cardiff University, Cardiff Business School, Economics Section.
    25. Yannick Hoga, 2023. "The Estimation Risk in Extreme Systemic Risk Forecasts," Papers 2304.10349, arXiv.org.
    26. de Almeida, Daniel & Hotta, Luiz K. & Ruiz, Esther, 2018. "MGARCH models: Trade-off between feasibility and flexibility," International Journal of Forecasting, Elsevier, vol. 34(1), pages 45-63.
    27. Tomasz Wozniak, 2012. "Granger-causal analysis of VARMA-GARCH models," Economics Working Papers ECO2012/19, European University Institute.
    28. Silvennoinen, Annastiina & Teräsvirta, Timo, 2005. "Multivariate Autoregressive Conditional Heteroskedasticity with Smooth Transitions in Conditional Correlations," SSE/EFI Working Paper Series in Economics and Finance 577, Stockholm School of Economics, revised 01 Oct 2005.
    29. Timo Dimitriadis & Yannick Hoga, 2022. "Dynamic CoVaR Modeling and Estimation," Papers 2206.14275, arXiv.org, revised Jan 2025.
    30. Francq, Christian & Zakoian, Jean-Michel, 2010. "QML estimation of a class of multivariate GARCH models without moment conditions on the observed process," MPRA Paper 20779, University Library of Munich, Germany.
    31. Alhaj-Yaseen, Yaseen S. & Lam, Eddery & Barkoulas, John T., 2014. "Price discovery for cross-listed firms with foreign IPOs," International Review of Financial Analysis, Elsevier, vol. 31(C), pages 80-87.
    32. Anindya Chakrabarty & Anupam De & Gautam Bandyopadhyay, 2015. "A Wavelet-based MRA-EDCC-GARCH Methodology for the Detection of News and Volatility Spillover across Sectoral Indices—Evidence from the Indian Financial Market," Global Business Review, International Management Institute, vol. 16(1), pages 35-49, February.
    33. Robert Garthoff & Iryna Okhrin & Wolfgang Schmid, 2014. "Statistical surveillance of the mean vector and the covariance matrix of nonlinear time series," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(3), pages 225-255, July.
    34. Farhat Iqbal, 2013. "Robust estimation of the simplified multivariate GARCH model," Empirical Economics, Springer, vol. 44(3), pages 1353-1372, June.
    35. Neslihan Fidan Keçeci & Viktor Kuzmenko & Stan Uryasev, 2016. "Portfolios Dominating Indices: Optimization with Second-Order Stochastic Dominance Constraints vs. Minimum and Mean Variance Portfolios," JRFM, MDPI, vol. 9(4), pages 1-14, October.
    36. Arif Orçun Söylemez, 2013. "Stock Exchange Volatility Transmissions between Turkey and the Major Financial Centers," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 1(2), pages 27-32.
    37. Niklas Ahlgren & Paul Catani, 2017. "Wild bootstrap tests for autocorrelation in vector autoregressive models," Statistical Papers, Springer, vol. 58(4), pages 1189-1216, December.
    38. Haas, Markus & Liu, Ji-Chun, 2015. "Theory for a Multivariate Markov--switching GARCH Model with an Application to Stock Markets," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112855, Verein für Socialpolitik / German Economic Association.

  57. van Dijk, D.J.C. & Strikholm, B. & Terasvirta, T., 2001. "The effects of institutional and technological change and business cycle fluctiations on seasonal patterns in quarterly industrial production series," Econometric Institute Research Papers EI 2001-12, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. Siem Jan Koopman & Kai Ming Lee, 0000. "Seasonality with Trend and Cycle Interactions in Unobserved Components Models," Tinbergen Institute Discussion Papers 08-028/4, Tinbergen Institute.
    2. Craig, Lee & Holt, Matthew T., 2012. "The Role of Mechanical Refrigeration in Spatial and Temporal Price Dynamics for Regional U.S. Egg Markets, 1880–1911," MPRA Paper 39554, University Library of Munich, Germany.
    3. Wang, Yajie & Yu, Huan & Zhang, Hongda & Chen, Tianyu, 2021. "Non-linear analysis of effects of energy consumption on economic growth in China: Role of real exchange rate," Economic Modelling, Elsevier, vol. 104(C).
    4. Michael Funke & Marc Gronwald, 2008. "The Undisclosed Renminbi Basket: Are the Markets Telling us something about where the Renminbi – US Dollar Exchange Rate is Going?," CESifo Working Paper Series 2272, CESifo.
    5. Michael Dueker & Martin Sola & Fabio Spagnolo, 2007. "Contemporaneous Threshold Autoregressive Models: Estimation, Testing and Forecasting," Discussion Papers 5_2007, D.E.S. (Department of Economic Studies), University of Naples "Parthenope", Italy.
    6. Gnidchenko, Andrey, 2011. "Моделирование Технологических И Институциональных Эффектов В Макроэкономическом Прогнозировании [Technological and Institutional Effects Modeling in Macroeconomic Forecasting]," MPRA Paper 35484, University Library of Munich, Germany, revised May 2011.
    7. Nermeen Harb & Mamdouh Abdelmoula M. Abdelsalam, 2019. "Effect Of Oil Prices On Stock Markets: Evidence From New Generation Of Star Model," Bulletin of Economic Research, Wiley Blackwell, vol. 71(3), pages 466-482, July.
    8. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, January.
    9. B. Candelon & A. Dupuy & L. Gil-Alana, 2009. "The nature of occupational unemployment rates in the United States: hysteresis or structural?," Applied Economics, Taylor & Francis Journals, vol. 41(19), pages 2483-2493.
    10. Lazzarini, S. G. & Madalozzo, R. C & Artes, R. & Siqueira, J. O., 2004. "Measuring trust: An experiment in Brazil," Insper Working Papers wpe_42, Insper Working Paper, Insper Instituto de Ensino e Pesquisa.
    11. Matas-Mir, Antoni & Denise R Osborn, 2002. "Does Seasonality Change over the Business Cycle? An Investigation using Monthly Industrial Production Series," Royal Economic Society Annual Conference 2002 139, Royal Economic Society.
    12. Martelotte Marcela Cohen & Souza Reinaldo Castro & Silva Eduardo Antônio Barros da, 2017. "Design of Seasonal Adjustment Filter Robust to Variations in the Seasonal Behaviour of Time Series," Journal of Official Statistics, Sciendo, vol. 33(1), pages 155-186, March.
    13. He, Changli & Kang, Jian & Teräsvirta, Timo & Zhang, Shuhua, 2019. "The shifting seasonal mean autoregressive model and seasonality in the Central England monthly temperature series, 1772–2016," Econometrics and Statistics, Elsevier, vol. 12(C), pages 1-24.
    14. Matthew T. Holt & Timo Teräsvirta, 2017. "Global Hemispheric Temperatures and Co–Shifting: A Vector Shifting–Mean Autoregressive Analysis," CREATES Research Papers 2017-05, Department of Economics and Business Economics, Aarhus University.
    15. Siem Jan Koopman & Marius Ooms & Irma Hindrayanto, 2009. "Periodic Unobserved Cycles in Seasonal Time Series with an Application to US Unemployment," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 71(5), pages 683-713, October.
    16. Craig, Lee A. & Holt, Matthew T., 2008. "Mechanical refrigeration, seasonality, and the hog-corn cycle in the United States: 1870-1940," Explorations in Economic History, Elsevier, vol. 45(1), pages 30-50, January.
    17. Matthew T. Holt & Timo Teräsvirta, 2012. "Global Hemispheric Temperature Trends and Co–Shifting: A Shifting Mean Vector Autoregressive Analysis," CREATES Research Papers 2012-54, Department of Economics and Business Economics, Aarhus University.
    18. Walter Enders & Matthew T. Holt, 2014. "The Evolving Relationships between Agricultural and Energy Commodity Prices: A Shifting-Mean Vector Autoregressive Analysis," NBER Chapters, in: The Economics of Food Price Volatility, pages 135-187, National Bureau of Economic Research, Inc.
    19. Franses, Ph.H.B.F. & van Dijk, D.J.C., 2001. "The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production," Econometric Institute Research Papers EI 2001-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    20. D R Osborn & A Matas-Mir, 2003. "The Extent of Seasonal/Business Cycle Interactions in European Industrial Production," Centre for Growth and Business Cycle Research Discussion Paper Series 38, Economics, The University of Manchester.
    21. Ahdi Ajmi & Adnen Ben Nasr & Mohamed Boutahar, 2008. "Seasonal Nonlinear Long Memory Model for the US Inflation Rates," Computational Economics, Springer;Society for Computational Economics, vol. 31(3), pages 243-254, April.
    22. João Paulo Martin Faleiros & Denisard Cnéio de Oliveira Alves, 2006. "Não Linearidade Nos Ciclos De Negócios: Modelo Auto-Regressivo “Smooth Transition” Para O Índice Geral De Produção Industrial Brasileiro E Bens De Capital," Anais do XXXIV Encontro Nacional de Economia [Proceedings of the 34th Brazilian Economics Meeting] 10, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    23. Ana Beatriz C. Galvão, 2006. "Structural break threshold VARs for predicting US recessions using the spread," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(4), pages 463-487, May.
    24. Kumawat, Lokendra, 2010. "Effect of Rainfall on Seasonals in Indian Manufacturing Production: Evidence from Sectoral Data," MPRA Paper 25300, University Library of Munich, Germany.
    25. Dalu Zhang & Peter Moffatt, 2013. "Time series non-linearity in the real growth / recession-term spread relationship," University of East Anglia Applied and Financial Economics Working Paper Series 047, School of Economics, University of East Anglia, Norwich, UK..
    26. João Paulo Martin Faleiros & Denisard Cnéio de Oliveira Alves, 2008. "Modelo de Crescimento Baseado nas Exportações: Evidências empíricas para Chile, Brasil e México, em uma perspectiva Não Linear," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807170923500, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].

  58. van Dijk, D.J.C. & Terasvirta, T. & Franses, Ph.H.B.F., 2000. "Smooth transition autoregressive models - A survey of recent developments," Econometric Institute Research Papers EI 2000-23/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.

    Cited by:

    1. JamesR. Lothian & MarkP. Taylor, 2008. "Real Exchange Rates Over the Past Two Centuries: How Important is the Harrod-Balassa-Samuelson Effect?," Economic Journal, Royal Economic Society, vol. 118(532), pages 1742-1763, October.
    2. Agnello, Luca & Castro, Vítor & Sousa, Ricardo M., 2012. "How does fiscal policy react to wealth composition and asset prices?," Journal of Macroeconomics, Elsevier, vol. 34(3), pages 874-890.
    3. Yang Fuyu & Leon-Gonzalez Roberto, 2010. "Bayesian Estimation and Model Selection in the Generalized Stochastic Unit Root Model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-38, September.
    4. Libman, Emiliano, 2017. "Asymmetric Monetary and Exchange Rate Policies in Latin America," MPRA Paper 78864, University Library of Munich, Germany.
    5. Param Silvapulle & Titi Kanti Lestari & Jae Kim, 2004. "Nonlinear Modelling of Purchasing Power Parity in Indonesia," Econometric Society 2004 Australasian Meetings 316, Econometric Society.
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    Cited by:

    1. Felix Chan & Michael McAleer, 2001. "Estimating Smooth Transition Autoregressive Models with GARCH Errors in the Presence of Extreme Observations and Outliers," ISER Discussion Paper 0539, Institute of Social and Economic Research, Osaka University.
    2. Luis Eduardo Arango & Luis Fernando Melo, 2001. "Expansions and Contractions in Some Latin American Countries: A View Throught Non- Linear Models," Borradores de Economia 2691, Banco de la Republica.
    3. Mohamed Chikhi & Claude Diebolt, 2019. "Testing Nonlinearity through a Logistic Smooth Transition AR Model with Logistic Smooth Transition GARCH Errors," Working Papers 03-19, Association Française de Cliométrie (AFC).
    4. Felix Chan & Michael McAleer, 2002. "Maximum likelihood estimation of STAR and STAR-GARCH models: theory and Monte Carlo evidence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 509-534.

  60. Lundbergh, Stefan & Teräsvirta, Timo & van Dijk, Dick, 2000. "Time-Varying Smooth Transition Autoregressive Models," SSE/EFI Working Paper Series in Economics and Finance 376, Stockholm School of Economics.

    Cited by:

    1. JamesR. Lothian & MarkP. Taylor, 2008. "Real Exchange Rates Over the Past Two Centuries: How Important is the Harrod-Balassa-Samuelson Effect?," Economic Journal, Royal Economic Society, vol. 118(532), pages 1742-1763, October.
    2. Andres Gonzalez & Timo Terasvirta & Dick van Dijk, 2005. "Panel Smooth Transition Regression Models," Research Paper Series 165, Quantitative Finance Research Centre, University of Technology, Sydney.
    3. van Dijk, Dick & Strikholm, Birgit & Teräsvirta, Timo, 2001. "The effects of institutional and technological change and business cycle fluctuations on seasonal patterns in quarterly industrial production series," SSE/EFI Working Paper Series in Economics and Finance 0429, Stockholm School of Economics, revised 01 Jun 2004.
    4. Tolga Omay & Furkan Emirmahmutoglu & Mubariz Hasanov, 2018. "Structural break, nonlinearity and asymmetry: a re-examination of PPP proposition," Applied Economics, Taylor & Francis Journals, vol. 50(12), pages 1289-1308, March.
    5. Marcelo C. Medeiros & Alvaro Veiga, 2003. "Diagnostic Checking in a Flexible Nonlinear Time Series Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(4), pages 461-482, July.
    6. Luis Eduardo Arango & Andrés González & Carlos Esteban Posada, 2001. "Returns and Interest Rate: A Nonlinear Relationship in the Bogotá Stock Market," Borradores de Economia 169, Banco de la Republica de Colombia.
    7. M Sensier & D van Dijk, 2001. "Short-term Volatility versus Long-term Growth: Evidence in US Macroeconomic Time Series," Centre for Growth and Business Cycle Research Discussion Paper Series 08, Economics, The University of Manchester.
    8. Hasanli, Mübariz, 2024. "Re-examining crude oil and natural gas price relationship: Evidence from time-varying regime-switching models," Energy Economics, Elsevier, vol. 133(C).
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    10. Oleg Korenok & Stanislav Radchenko, 2005. "The smooth transition autoregressive target zone model with the Gaussian stochastic volatility and TGARCH error terms with applications," Working Papers 0505, VCU School of Business, Department of Economics.
    11. Dominique Guegan, 2005. "How can we Define the Concept of Long Memory? An Econometric Survey," Econometric Reviews, Taylor & Francis Journals, vol. 24(2), pages 113-149.
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    13. Maertens Odria, Luís Ricardo & Castillo, Paul & Rodriguez, Gabriel, 2012. "Does the exchange rate pass-through into prices change when inflation targeting is adopted? The Peruvian case study between 1994 and 2007," Journal of Macroeconomics, Elsevier, vol. 34(4), pages 1154-1166.
    14. Mubariz Hasanov, 2014. "Testing for a unit root in the presence of a nonlinear trend: The case of Australian Reel Exchange Rate," Econometrics Letters, Bilimsel Mektuplar Organizasyonu (Scientific letters), vol. 1(1), pages 10-17.
    15. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    16. Joseph V. Balagtas & Matthew T. Holt, 2009. "The Commodity Terms of Trade, Unit Roots, and Nonlinear Alternatives: A Smooth Transition Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 87-105.
    17. Canepa, Alessandra & Zanetti Chini, Emilio & Alqaralleh, Huthaifa, 2023. "Modelling and Forecasting Energy Market Cycles: A Generalized Smooth Transition Approach," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202318, University of Turin.
    18. Tolga Omay & Mübariz Hasanov & Yongcheol Shin, 2018. "Testing for Unit Roots in Dynamic Panels with Smooth Breaks and Cross-Sectionally Dependent Errors," Computational Economics, Springer;Society for Computational Economics, vol. 52(1), pages 167-193, June.
    19. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
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    22. Remzi Uctum, 2007. "Econométrie des modèles à changements de régimes: un essai de synthèse," Post-Print halshs-00174034, HAL.
    23. Emilio Zanetti Chini, 2013. "Generalizing smooth transition autoregressions," CEIS Research Paper 294, Tor Vergata University, CEIS, revised 25 Sep 2014.
    24. Daiki Maki & Yasushi Ota, 2021. "Testing for Time-Varying Properties Under Misspecified Conditional Mean and Variance," Computational Economics, Springer;Society for Computational Economics, vol. 57(4), pages 1167-1182, April.
    25. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, January.
    26. Emilio Zanetti Chini, 2018. "Forecasting dynamically asymmetric fluctuations of the U.S. business cycle," CREATES Research Papers 2018-13, Department of Economics and Business Economics, Aarhus University.
    27. Huang, Alex YiHou & Hu, Wen-Cheng, 2012. "Regime switching dynamics in credit default swaps: Evidence from smooth transition autoregressive model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(4), pages 1497-1508.
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    30. Rickard Sandberg, 2016. "Testing for unit roots in nonlinear heterogeneous panels with smoothly changing trends: an application to Scandinavian unemployment rates," Empirical Economics, Springer, vol. 51(3), pages 1053-1083, November.
    31. Omay, Tolga & Öznur Kan, Elif, 2010. "Re-examining the threshold effects in the inflation-growth nexus with cross-sectionally dependent non-linear panel: Evidence from six industrialized economies," Economic Modelling, Elsevier, vol. 27(5), pages 996-1005, September.
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    33. Bo Zhang & Joshua C.C. Chan & Jamie L. Cross, 2018. "Stochastic volatility models with ARMA innovations: An application to G7 inflation forecasts," CAMA Working Papers 2018-32, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    34. Goodwin, Barry K. & Holt, Matthew T. & Prestemon, Jeffrey P., 2019. "Nonlinear exchange rate pass-through in timber products: The case of oriented strand board in Canada and the United States," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    35. Ayşen SİVRİKAYA & Mübariz HASANOV, 2019. "Time-Varying and Asymmetric Relationship between Energy Use and Macroeconomic Activity," Sosyoekonomi Journal, Sosyoekonomi Society.
    36. Piergallini, Alessandro & Postigliola, Michele, 2013. "Non-linear budgetary policies: Evidence from 150 years of Italian public finance," Economics Letters, Elsevier, vol. 121(3), pages 495-498.
    37. Li, Wenying & Dorfman, Jeffrey H., 2019. "The implications of heterogeneous habit in consumer beverage purchases on soda and sin taxes," Food Policy, Elsevier, vol. 84(C), pages 111-120.
    38. Emediegwu, Lotanna Ernest, 2023. "Assessing the (a)symmetric effect of global climate anomalies on food prices: Evidence from local prices," 97th Annual Conference, March 27-29, 2023, Warwick University, Coventry, UK 334555, Agricultural Economics Society - AES.
    39. Raputsoane, Leroi, 2015. "The lean versus clean debate and monetary policy in South Africa," MPRA Paper 68123, University Library of Munich, Germany.
    40. Mübariz Hasanov & Tolga Omay & Vasif Abioglu, 2024. "Re-examining the real interest rate parity hypothesis under temporary gradual breaks and nonlinear convergence," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 23(3), pages 355-382, September.
    41. Zhu, Yichen & Ghoshray, Atanu, 2021. "Climate Anomalies and Its Impact on U.S. Corn and Soybean Prices," 2021 Conference, August 17-31, 2021, Virtual 315271, International Association of Agricultural Economists.
    42. Reginaldo P. Nogueira Junior & Miguel Leon-Ledesma, 2008. "Exchange Rate Pass-Through Into Inflation: The Role of Asymmetries and NonLinearities," Studies in Economics 0801, School of Economics, University of Kent.
    43. Francesco Battaglia & Mattheos Protopapas, 2012. "An analysis of global warming in the Alpine region based on nonlinear nonstationary time series models," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 21(3), pages 315-334, August.
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    55. Joshy Easaw & Atanu Ghoshray & Saeed Heravi, 2014. "Households' Forming Subjective Expectations Using Perceived News: Do Shocks to ‘Good’ News Matter More Than ‘Bad’ News?," Manchester School, University of Manchester, vol. 82(1), pages 1-16, January.
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    59. Hernán Rincón & Norberto Rodríguez, 2014. "Reestimación del grado de transmisión de la tasa de cambio del peso sobre la inflación de los bienes importados," Borradores de Economia 12302, Banco de la Republica.
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    62. Rahbar , Farhad & Behzadi Soufiani , Mohsen, 2021. "The Impact of Macroeconomic and Banking Variables on Non-Performing Loans in Oil Cycles: Evidence from Iran," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 16(2), pages 135-164, June.
    63. Boriss Siliverstovs, 2005. "The Bi-parameter Smooth Transition Autoregressive model," Economics Bulletin, AccessEcon, vol. 3(23), pages 1-11.
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    65. Giorgio Canarella & Stephen M. Miller, 2016. "Did Okun's Law Die after the Great Recession?," Working papers 2016-10, University of Connecticut, Department of Economics.
    66. Pede, Valerien O. & Florax, Raymond J.G.M. & Lambert, Dayton M., 2014. "Spatial econometric STAR models: Lagrange multiplier tests, Monte Carlo simulations and an empirical application," Regional Science and Urban Economics, Elsevier, vol. 49(C), pages 118-128.
    67. Mr. Chorng-Huey Wong & Mr. Eric V. Clifton & Mr. Gene L. Leon, 2001. "Inflation Targeting and the Unemployment-Inflation Trade-off," IMF Working Papers 2001/166, International Monetary Fund.
    68. Bopjun Gwak, 2020. "Long-term Inflation Expectations and Central Bank Credibility," Economics Bulletin, AccessEcon, vol. 40(3), pages 2320-2335.
    69. Franses, Ph.H.B.F. & van Dijk, D.J.C., 2001. "The forecasting performance of various models for seasonality and nonlinearity for quarterly industrial production," Econometric Institute Research Papers EI 2001-14, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    70. Sigl-Grüb, C. & Schiereck, D., 2010. "Speculation and Nonlinear Price Dynamics in Commodity Futures Markets," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 56603, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    71. Balagtas, Joseph Valdes & Holt, Matthew T., 2006. "Unit Roots, TV-STARs, and the Commodity Terms of Trade: A Further Assessment of the Prebisch-Singer Hypothesis," 2006 Annual meeting, July 23-26, Long Beach, CA 21405, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    72. David Ubilava, 2018. "The Role of El Niño Southern Oscillation in Commodity Price Movement and Predictability," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(1), pages 239-263.
    73. Clements, Michael P., 2024. "Do professional forecasters believe in the Phillips curve?," International Journal of Forecasting, Elsevier, vol. 40(3), pages 1238-1254.
    74. Stracca, Livio & Musso, Alberto & van Dijk, Dick, 2007. "Instability and nonlinearity in the euro area Phillips curve," Working Paper Series 811, European Central Bank.
    75. Xie, Zixiong & Chen, Shyh-Wei & Hsieh, Chun-Kuei, 2021. "Facing up to the polysemy of purchasing power parity: New international evidence," Economic Modelling, Elsevier, vol. 98(C), pages 247-265.
    76. Venetis, Ioannis A. & Paya, Ivan & Peel, David A., 2003. "Re-examination of the predictability of economic activity using the yield spread: a nonlinear approach," International Review of Economics & Finance, Elsevier, vol. 12(2), pages 187-206.
    77. Sandberg, Rickard, 2016. "Trends, unit roots, structural changes, and time-varying asymmetries in U.S. macroeconomic data: the Stock and Watson data re-examined," Economic Modelling, Elsevier, vol. 52(PB), pages 699-713.
    78. Lotanna E. Emediegwu, 2024. "Assessing the Asymmetric Effect of Global Climate Anomalies on Food Prices: Evidence from Local Prices," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 87(10), pages 2743-2772, October.
    79. Muhammad Akram GILAL* & Muhammad AJMAIR** & Sohail FAROOQ***, 2019. "Structural Changes And Economic Growth In Pakistan," Pakistan Journal of Applied Economics, Applied Economics Research Centre, vol. 29(1), pages 35-51.
    80. Efthymios Pavlidis & Nicos Pavlidis, 2012. "Dynamic Estimation of Trade Costs from Real Exchange Rates," Working Papers 21883757, Lancaster University Management School, Economics Department.
    81. Francesco Battaglia & Mattheos Protopapas, 2012. "Multi–regime models for nonlinear nonstationary time series," Computational Statistics, Springer, vol. 27(2), pages 319-341, June.
    82. Wang, Zheng-Xin & Jv, Yue-Qi, 2022. "A smooth difference-in-differences model for assessing gradual policy effects: Revisiting the impact of banking deregulation on income distribution," Finance Research Letters, Elsevier, vol. 50(C).
    83. Banu Kurtaran, 2015. "Re-examining the PPP Hypothesis via Nonlinearity and Smooth Breaks," Econometrics Letters, Bilimsel Mektuplar Organizasyonu (Scientific letters), vol. 2(1), pages 1-21.
    84. David G. McMillan, 2010. "Level‐shifts and non‐linearity in US financial ratios," Review of Accounting and Finance, Emerald Group Publishing Limited, vol. 9(2), pages 189-207, May.
    85. Yunus Aksoy & Miguel A. Leon-Ledesma, 2007. "Non-linearities and Unit Roots in G7 Macroeconomic Variables," Birkbeck Working Papers in Economics and Finance 0710, Birkbeck, Department of Economics, Mathematics & Statistics.
    86. Koo, Chao, 2018. "Essays on functional coefficient models," Other publications TiSEM ba87b8a5-3c55-40ec-967d-9, Tilburg University, School of Economics and Management.
    87. Hasanov, Mübariz & Telatar, Erdinc, 2011. "A re-examination of stationarity of energy consumption: Evidence from new unit root tests," Energy Policy, Elsevier, vol. 39(12), pages 7726-7738.
    88. Mr. Gene L. Leon & Serineh Najarian, 2003. "Asymmetric Adjustment and Nonlinear Dynamics in Real Exchange Rates," IMF Working Papers 2003/159, International Monetary Fund.
    89. Wali, Muammer & Chan, Felix & Manzur, Meher, 2017. "Nonlinear dependence in exchange rate returns: How do emerging Asian currencies compare with major currencies?," Journal of Asian Economics, Elsevier, vol. 50(C), pages 62-72.
    90. Gary Koop & Simon M. Potter, 2007. "A flexible approach to parametric inference in nonlinear time series models," Staff Reports 285, Federal Reserve Bank of New York.
    91. Shu-Chen Chang, 2008. "Asymmetric cointegration relationship among Asian exchange rates," Economic Change and Restructuring, Springer, vol. 41(2), pages 125-141, June.
    92. D R Osborn & M Sensier, 2004. "Modelling UK Inflation: Persistence, Seasonality and Monetary Policy," Centre for Growth and Business Cycle Research Discussion Paper Series 46, Economics, The University of Manchester.
    93. Zhao, Zifeng & Zhang, Zhengjun & Chen, Rong, 2018. "Modeling maxima with autoregressive conditional Fréchet model," Journal of Econometrics, Elsevier, vol. 207(2), pages 325-351.
    94. Dalu Zhang & Peter Moffatt, 2013. "Time series non-linearity in the real growth / recession-term spread relationship," University of East Anglia Applied and Financial Economics Working Paper Series 047, School of Economics, University of East Anglia, Norwich, UK..
    95. Mehrara , Mohsen & Behzadi Soufiani , Mohsen, 2015. "The Threshold Impact of Fiscal and Monetary Policies on Inflation: Threshold Model Approach," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 10(4), pages 1-27, October.
    96. Holt, Matthew T. & Craig, Lee A., 2006. "AJAE Appendix: Nonlinear Dynamics and Structural Change in the U.S. Hog-Corn Ratio: A Time-Varying Star Approach," American Journal of Agricultural Economics APPENDICES, Agricultural and Applied Economics Association, vol. 88(01), pages 1-16, February.
    97. Sayar Karmakar & Marek Chudy & Wei Biao Wu, 2020. "Long-term prediction intervals with many covariates," Papers 2012.08223, arXiv.org, revised Sep 2021.
    98. Dayton M. Lambert & Wan Xu & Raymond J. G. M. Florax, 2014. "Partial Adjustment Analysis of Income and Jobs, and Growth Regimes in the Appalachian Region with Smooth Transition Spatial Process Models," International Regional Science Review, , vol. 37(3), pages 328-364, July.

  61. Stefan Lundbergh & Timo Teräsvirta, 1999. "Modelling Economic High-Frequency Time Series," Tinbergen Institute Discussion Papers 99-009/4, Tinbergen Institute.

    Cited by:

    1. Mawuli Segnon & Rangan Gupta & Keagile Lesame & Mark E. Wohar, 2019. "High-Frequency Volatility Forecasting of US Housing Markets," Working Papers 201977, University of Pretoria, Department of Economics.
    2. Felix Chan & Michael McAleer, 2001. "Estimating Smooth Transition Autoregressive Models with GARCH Errors in the Presence of Extreme Observations and Outliers," ISER Discussion Paper 0539, Institute of Social and Economic Research, Osaka University.
    3. Dominique Guegan & Bertrand K. Hassani, 2019. "Risk Measurement," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02119256, HAL.
    4. Murat Midilic, 2016. "Estimation Of Star-Garch Models With Iteratively Weighted Least Squares," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 16/918, Ghent University, Faculty of Economics and Business Administration.
    5. Mawuli Segnon & Stelios Bekiros & Bernd Wilfling, 2018. "Forecasting Inflation Uncertainty in the G7 Countries," CQE Working Papers 7118, Center for Quantitative Economics (CQE), University of Muenster.
    6. Stein, Michael & Islami, Mevlud & Lindemann, Jens, 2012. "Identifying time variability in stock and interest rate dependence," Discussion Papers 24/2012, Deutsche Bundesbank.

  62. Peguin-Feissolle, A. & Terasvirta, T., 1999. "A General Framework for Testing the Granger Noncausality Hypothesis," G.R.E.Q.A.M. 99a42, Universite Aix-Marseille III.

    Cited by:

    1. Ruist, Erik, 2007. "The choice between two hypothesis tests," SSE/EFI Working Paper Series in Economics and Finance 667, Stockholm School of Economics.
    2. Muhammad Abubakr Naeem & Saqib Farid & Safwan Mohd Nor & Syed Jawad Hussain Shahzad, 2021. "Spillover and Drivers of Uncertainty among Oil and Commodity Markets," Mathematics, MDPI, vol. 9(4), pages 1-26, February.
    3. Prasad Bal, Debi & Narayan Rath, Badri, 2015. "Nonlinear causality between crude oil price and exchange rate: A comparative study of China and India," Energy Economics, Elsevier, vol. 51(C), pages 149-156.
    4. Dash, Saumya Ranjan & Maitra, Debasish, 2019. "The relationship between emerging and developed market sentiment: A wavelet-based time-frequency analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 22(C), pages 135-150.
    5. Rothman, P. & van Dijk, D.J.C. & Franses, Ph.H.B.F., 1999. "A multivariate STAR analysis of the relationship between money and output," Econometric Institute Research Papers EI 9945-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. Ahmad Zubaidi Baharumshah & Venus Khim-Sen Liew & Evan Lau, 2003. "Nonlinear Mean Reversion in Real Exchange Rates: Evidence from the ASEAN-5," International Trade 0308001, University Library of Munich, Germany.
    7. Tiwari, Aviral Kumar & Dar, Arif Billah & Bhanja, Niyati, 2013. "Oil price and exchange rates: A wavelet based analysis for India," Economic Modelling, Elsevier, vol. 31(C), pages 414-422.
    8. Dash, Saumya Ranjan & Maitra, Debasish, 2018. "Does Shariah index hedge against sentiment risk? Evidence from Indian stock market using time–frequency domain approach," Journal of Behavioral and Experimental Finance, Elsevier, vol. 19(C), pages 20-35.
    9. Werner Kristjanpoller R. & Alejandro Sierra C., 2014. "Relationship between the dollar, the price of copper and the IPSA indifferent time scales: An approach through Wavelet," Journal Economía Chilena (The Chilean Economy), Central Bank of Chile, vol. 17(3), pages 56-85, December.
    10. Chen, Show-Lin & Tsai, Li-Ju & Wu, Jyh-Lin, 2004. "A revisit to liquidity effects--evidence from a non-linear approach," Journal of Macroeconomics, Elsevier, vol. 26(3), pages 501-517, September.
    11. João Paulo Martin Faleiros & Denisard Cnéio de Oliveira Alves, 2008. "Modelo de Crescimento Baseado nas Exportações: Evidências empíricas para Chile, Brasil e México, em uma perspectiva Não Linear," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807170923500, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].

  63. Persson, Anna & Teräsvirta, Timo, 1999. "The Net Barter Terms Of Trade : A Smooth Transition Approach," SSE/EFI Working Paper Series in Economics and Finance 335, Stockholm School of Economics.

    Cited by:

    1. Joseph V. Balagtas & Matthew T. Holt, 2009. "The Commodity Terms of Trade, Unit Roots, and Nonlinear Alternatives: A Smooth Transition Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 87-105.
    2. Manuel Landajo & Mar'ia Jos'e Presno, 2024. "The prices of renewable commodities: A robust stationarity analysis," Papers 2402.01005, arXiv.org.
    3. Manuel Landajo & María José Presno, 2022. "The prices of renewable commodities: a robust stationarity analysis," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 66(2), pages 447-470, April.
    4. Boris Petkov, 2018. "Natural Resource Abundance: Is it a Blessing or is it a Curse," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 43(3), pages 25-56, September.
    5. Balagtas, Joseph Valdes & Holt, Matthew T., 2006. "Unit Roots, TV-STARs, and the Commodity Terms of Trade: A Further Assessment of the Prebisch-Singer Hypothesis," 2006 Annual meeting, July 23-26, Long Beach, CA 21405, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Kulaksizoglu, Tamer & Kulaksizoglu, Sebnem, 2009. "The U.S. Excess Money Growth and Inflation Relation in the Long-Run: A Nonlinear Analysis," MPRA Paper 23780, University Library of Munich, Germany.
    7. Hany Fahmy, 2014. "Modelling nonlinearities in commodity prices using smooth transition regression models with exogenous transition variables," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 23(4), pages 577-600, November.
    8. G. K. Randolph TAN, 2004. "Long Memory in Import and Export Price Inflation and Persistence of Shocks to the Terms of Trade," Econometric Society 2004 Far Eastern Meetings 732, Econometric Society.

  64. He, Changli & Teräsvirta, Timo & Malmsten, Hans, 1999. "Fourth Moment Structure of a Family of First-Order Exponential GARCH Models," SSE/EFI Working Paper Series in Economics and Finance 345, Stockholm School of Economics.

    Cited by:

    1. Paolo Girardello & Orietta Nicolis & Giovanni Tondini, 2003. "Comparing Conditional Variance Models: Theory and Empirical Evidence," Multinational Finance Journal, Multinational Finance Journal, vol. 7(3-4), pages 177-206, September.
    2. Niklas Ahlgren & Alexander Back & Timo Terasvirta, 2024. "A new GARCH model with a deterministic time-varying intercept," Papers 2410.03239, arXiv.org, revised Oct 2024.
    3. FERNANDES, Marcelo & GRAMMIG, Joachim, 2001. "A family of autoregressive conditional duration models," LIDAM Discussion Papers CORE 2001036, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Menelaos Karanasos, "undated". "The Covariance Structure of Mixed ARMA Models," Discussion Papers 00/11, Department of Economics, University of York.
    5. P. Girardello & Orietta Nicolis & Giovanni Tondini, 2002. "Comparing conditional variance models: Theory and empirical evidence," Departmental Working Papers 2002-08, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    6. Antonis Demos, 2002. "Moments and dynamic structure of a time-varying parameter stochastic volatility in mean model," Econometrics Journal, Royal Economic Society, vol. 5(2), pages 345-357, June.
    7. Pasquale Tridico & Riccardo Pariboni, 2017. "Structural Change, Aggregate Demand And The Decline Of Labour Productivity: A Comparative Perspective," Departmental Working Papers of Economics - University 'Roma Tre' 0221, Department of Economics - University Roma Tre.
    8. BAUWENS, Luc & GALLi, Fausto & GIOT, Pierre, 2009. "The moments of Log-ACD models," LIDAM Reprints CORE 2023, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Carnero, María Ángeles, 2001. "Outliers and conditional autoregressive heteroscedasticity in time series," DES - Working Papers. Statistics and Econometrics. WS ws010704, Universidad Carlos III de Madrid. Departamento de Estadística.
    10. Shelton Peiris & Tim Swartz, 2020. "Revisiting the Kurtosis of Stationary Processes with Applications to Volatility Models," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(2), pages 1-1.
    11. Davide De Gaetano, 2017. "A Bootstrap Bias Correction Of Long Run Fourth Order Moment Estimation In The Cusum Of Squares Test," Departmental Working Papers of Economics - University 'Roma Tre' 0220, Department of Economics - University Roma Tre.
    12. Murat Midiliç, 2020. "Estimation of STAR–GARCH Models with Iteratively Weighted Least Squares," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 87-117, January.

  65. Rech, Gianluigi & Teräsvirta, Timo & Tschernig, Rolf, 1999. "A simple variable selection technique for nonlinear models," SSE/EFI Working Paper Series in Economics and Finance 296, Stockholm School of Economics, revised 06 Apr 2000.

    Cited by:

    1. Marcelo C. Medeiros & Alvaro Veiga, 2003. "Diagnostic Checking in a Flexible Nonlinear Time Series Model," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(4), pages 461-482, July.
    2. Marcelo Cunha Medeiros & Álvaro Veiga & Carlos Eduardo Pedreira, 2000. "Modelling exchange rates: smooth transitions, neural networks, and linear models," Textos para discussão 432, Department of Economics PUC-Rio (Brazil).
    3. Marie Lebreton & Katia Melnik, 2009. "Voluntary Participation as a Determinant of Social Capital in France : Allowing for Parameter Heterogeneity," Working Papers halshs-00410530, HAL.
    4. Eduardo Mendes & Alvaro Veiga & MArcelo Cunha Medeiros, 2007. "Estimation And Asymptotic Theory For A New Class Of Mixture Models," Textos para discussão 538, Department of Economics PUC-Rio (Brazil).
    5. Henrik Amilon, 2003. "A neural network versus Black-Scholes: a comparison of pricing and hedging performances," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 22(4), pages 317-335.
    6. Barrera, Carlos R., 2010. "Redes neuronales para predecir el tipo de cambio diario," Working Papers 2010-001, Banco Central de Reserva del Perú.
    7. Lebreton, Marie, 2005. "The NCSTAR model as an alternative to the GWR model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 77-84.
    8. Terasvirta, Timo & van Dijk, Dick & Medeiros, Marcelo C., 2005. "Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination," International Journal of Forecasting, Elsevier, vol. 21(4), pages 755-774.
    9. Timo Teräsvirta & Marcelo C. Medeiros & Gianluigi Rech, 2006. "Building neural network models for time series: a statistical approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 49-75.
    10. Marcelo C. Medeiros & Eduardo F. Mendes, 2015. "l1-Regularization of High-Dimensional Time-Series Models with Flexible Innovations," Textos para discussão 636, Department of Economics PUC-Rio (Brazil).
    11. Anne Péguin-Feissolle & Birgit Strikholm & Timo Teräsvirta, 2008. "Testing the Granger noncausality hypothesis in stationary nonlinear models of unknown functional form," CREATES Research Papers 2008-19, Department of Economics and Business Economics, Aarhus University.
    12. Mayte Suarez Farinãs & Carlos Eduardo Pedreira & Marcelo C. Medeiros, 2003. "Local-global neural networks: a new approach for nonlinear time series modelling," Textos para discussão 470, Department of Economics PUC-Rio (Brazil).
    13. Murat Midilic, 2016. "Estimation Of Star-Garch Models With Iteratively Weighted Least Squares," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 16/918, Ghent University, Faculty of Economics and Business Administration.
    14. Medeiros, Marcelo & Veiga, Alvaro, 2000. "A Flexible Coefficient Smooth Transition Time Series Model," SSE/EFI Working Paper Series in Economics and Finance 360, Stockholm School of Economics, revised 29 Apr 2004.
    15. Marcelo C. Medeiros & Eduardo F. Mendes, 2012. "Estimating High-Dimensional Time Series Models," CREATES Research Papers 2012-37, Department of Economics and Business Economics, Aarhus University.
    16. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    17. Leila Ali & Marie Lebreton, 2013. "The Fall of Bretton Woods: Which Geography Matters?," Economics Bulletin, AccessEcon, vol. 33(2), pages 1396-1419.

  66. He, Changli & Teräsvirta, Timo, 1999. "Higher-order dependence in the general Power ARCH process and a special case," SSE/EFI Working Paper Series in Economics and Finance 315, Stockholm School of Economics.

    Cited by:

    1. Peter S. Sephton, 2009. "Fractional integration in agricultural futures price volatilities revisited," Agricultural Economics, International Association of Agricultural Economists, vol. 40(1), pages 103-111, January.
    2. GIOT, Pierre & LAURENT, Sébastien, 2004. "Modelling daily Value-at-Risk using realized volatility and ARCH type models," LIDAM Reprints CORE 1708, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. GIOT, Pierre & LAURENT, Sébastien, 2003. "Value-at-Risk for long and short trading positions," LIDAM Reprints CORE 1707, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Abdou Kâ Diongue & Dominique Guegan, 2007. "The Stationary Seasonal Hyperbolic Asymmetric Power ARCH model," Post-Print halshs-00179275, HAL.
    5. van Mierlo, J.G.A., 2001. "Over de verhouding tussen overheid, marktwerking en privatisering. Een economische meta-analyse," Research Memorandum 014, Maastricht University, Maastricht Research School of Economics of Technology and Organization (METEOR).
    6. Tak Siu & John Lau & Hailiang Yang, 2007. "On Valuing Participating Life Insurance Contracts with Conditional Heteroscedasticity," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 14(3), pages 255-275, September.
    7. Diamandis, Panayiotis F. & Drakos, Anastassios A. & Kouretas, Georgios P. & Zarangas, Leonidas, 2011. "Value-at-risk for long and short trading positions: Evidence from developed and emerging equity markets," International Review of Financial Analysis, Elsevier, vol. 20(3), pages 165-176, June.

  67. Lundbergh, Stefan & Teräsvirta, Timo, 1998. "Modelling economic high-frequency time series with STAR-STGARCH models," SSE/EFI Working Paper Series in Economics and Finance 291, Stockholm School of Economics.

    Cited by:

    1. Stefan Reitz & Frank Westerhoff, 2007. "Commodity price cycles and heterogeneous speculators: a STAR–GARCH model," Empirical Economics, Springer, vol. 33(2), pages 231-244, September.
    2. Westerhoff Frank H. & Reitz Stefan, 2003. "Nonlinearities and Cyclical Behavior: The Role of Chartists and Fundamentalists," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(4), pages 1-15, December.
    3. Alagidede, Paul & Panagiotidis, Theodore, 2009. "Modelling stock returns in Africa's emerging equity markets," Stirling Economics Discussion Papers 2009-04, University of Stirling, Division of Economics.
    4. Asmara Jamaleh, 2002. "Explaining and forecasting the euro/dollar exchange rate through a non-linear threshold model," The European Journal of Finance, Taylor & Francis Journals, vol. 8(4), pages 422-448.
    5. Ito, Hiro, 2003. "Was Japan’s Real Interest Rate Really Too High During the 1990s? The Role of the Zero Interest Rate Bound and Other Factors," Santa Cruz Center for International Economics, Working Paper Series qt48k5q6vd, Center for International Economics, UC Santa Cruz.
    6. Areosa, Waldyr Dutra & McAleer, Michael & Medeiros, Marcelo C., 2011. "Moment-based estimation of smooth transition regression models with endogenous variables," Journal of Econometrics, Elsevier, vol. 165(1), pages 100-111.
    7. Chen, Cathy W.S. & Gerlach, Richard H. & Tai, Amanda P.J., 2008. "Testing for nonlinearity in mean and volatility for heteroskedastic models," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 489-499.
    8. van Dijk, Dick & Franses, Philip Hans & Paap, Richard, 2002. "A nonlinear long memory model, with an application to US unemployment," Journal of Econometrics, Elsevier, vol. 110(2), pages 135-165, October.
    9. Rothman, P. & van Dijk, D.J.C. & Franses, Ph.H.B.F., 1999. "A multivariate STAR analysis of the relationship between money and output," Econometric Institute Research Papers EI 9945-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
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    116. Francisco Lasso-Valderrama & Héctor M. Zárate-Solano, 2019. "Forecasting the Colombian Unemployment Rate Using Labour Force Flows," Borradores de Economia 1073, Banco de la Republica de Colombia.
    117. Korhonen Marko & Puhakka Mikko, 2021. "The Behavior of Divorce Rates: A Smooth Transition Regression Approach," Journal of Time Series Econometrics, De Gruyter, vol. 13(1), pages 1-19, January.
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    Cited by:

    1. LanFen Chu & Michael McAleer & Chi-Chung Chen, 2011. "How Volatile is ENSO?," Documentos de Trabajo del ICAE 2011-21, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.
    2. Röthig, Andreas & Chiarella, Carl, 2006. "Investigating nonlinear speculation in cattle, corn, and hog futures markets using logistic smooth transition regression models," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 36774, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. David Ubilava & Matt Holt, 2013. "El Niño southern oscillation and its effects on world vegetable oil prices: assessing asymmetries using smooth transition models," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 57(2), pages 273-297, April.
    4. David Ubilava, 2012. "Modeling Nonlinearities in the U.S. Soybean‐to‐Corn Price Ratio: A Smooth Transition Autoregression Approach," Agribusiness, John Wiley & Sons, Ltd., vol. 28(1), pages 29-41, January.
    5. David Ubilava, 2012. "El Niño, La Niña, and world coffee price dynamics," Agricultural Economics, International Association of Agricultural Economists, vol. 43(1), pages 17-26, January.
    6. Ubilava, David & Helmers, Claes Gustav, 2011. "The ENSO Impact on Predicting World Cocoa Prices," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103528, Agricultural and Applied Economics Association.
    7. Po-Chin Wu & Chia-Jui Chang, 2017. "Nonlinear impacts of debt ratio and term spread on inward FDI performance persistence," Economia Politica: Journal of Analytical and Institutional Economics, Springer;Fondazione Edison, vol. 34(3), pages 369-388, December.
    8. Daniel Parra-Amado & Davinson Stev Abril-Salcedo & Luis Fernando Melo-Velandia, 2016. "Impactos de los fenómenos climáticos sobre el precio de los alimentos en Colombia," Revista ESPE - Ensayos Sobre Política Económica, Banco de la República, vol. 34(80), pages 146-158, June.
    9. Joseph V. Balagtas & Matthew T. Holt, 2009. "The Commodity Terms of Trade, Unit Roots, and Nonlinear Alternatives: A Smooth Transition Approach," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 91(1), pages 87-105.
    10. Tack, Jesse B. & Ubilava, David, 2013. "El Ni˜no Southern Oscillation Impacts on Crop Insurance," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 151429, Agricultural and Applied Economics Association.
    11. Chu, L. & McAleer, M.J. & Chen, C-C., 2012. "How Volatile is ENSO for Global Greenhouse Gas Emissions and the Global Economy?," Econometric Institute Research Papers EI 2012-28, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    12. Tack, Jesse B. & Ubilava, David, 2012. "The Effect of the El Nino Southern Oscillation on U.S. Corn Production and Downside Risk," 2012 Annual Meeting, February 4-7, 2012, Birmingham, Alabama 119785, Southern Agricultural Economics Association.
    13. Ubilava, David, 2013. "El Niño Southern Oscillation and Primary Agricultural Commodity Prices: Causal Inferences from Smooth Transition Models," 2013 Conference (57th), February 5-8, 2013, Sydney, Australia 152202, Australian Agricultural and Resource Economics Society.
    14. Li, Yushu & Shukur, Ghazi, 2009. "Testing for Unit Root against LSTAR Model: Wavelet Improvement under GARCH Distortion," CAFO Working Papers 2009:6, Linnaeus University, Centre for Labour Market Policy Research (CAFO), School of Business and Economics.
    15. Yue-Jun Zhang & Ting Yao & Zi-Yi Wang, 2015. "The bubble process of international crude oil futures prices: empirical evidence from the STAR model," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 38(1/2/3), pages 109-125.
    16. Ubilava, David, 2017. "The ENSO Effect and Asymmetries in Wheat Price Dynamics," World Development, Elsevier, vol. 96(C), pages 490-502.
    17. Balagtas, Joseph Valdes & Holt, Matthew T., 2006. "Unit Roots, TV-STARs, and the Commodity Terms of Trade: A Further Assessment of the Prebisch-Singer Hypothesis," 2006 Annual meeting, July 23-26, Long Beach, CA 21405, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    18. Ubilava, David & Helmers, C Gustav, 2012. "Forecasting ENSO with a smooth transition autoregressive model," MPRA Paper 36890, University Library of Munich, Germany.
    19. David Ubilava, 2018. "The Role of El Niño Southern Oscillation in Commodity Price Movement and Predictability," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 100(1), pages 239-263.
    20. Smith, Sarah C. & Ubilava, David, 2017. "The El Niño Southern Oscillation and Economic Growth in the Developing World," Working Papers 2017-11, University of Sydney, School of Economics, revised May 2017.

  70. Granger, Clive W.J. & Teräsvirta, Timo, 1998. "A simple nonlinear time series model with misleading linear properties," SSE/EFI Working Paper Series in Economics and Finance 237, Stockholm School of Economics.

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    1. Christian Gourieroux & Joann Jasiak, 1999. "Nonlinear Persistence and Copersistence," Working Papers 2000_1, York University, Department of Economics.
    2. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
    3. Chen, Xiaohong & Hansen, Lars Peter & Carrasco, Marine, 2008. "Nonlinearity and Temporal Dependence," Working Papers 48, Yale University, Department of Economics.
    4. Charfeddine, Lanouar & Guégan, Dominique, 2012. "Breaks or long memory behavior: An empirical investigation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5712-5726.
    5. Grace Lee Ching Yap, 2020. "Optimal Filter Approximations for Latent Long Memory Stochastic Volatility," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 547-568, August.
    6. Pierre Perron & Zhongjun Qu, 2008. "Long-Memory and Level Shifts in the Volatility of Stock Market Return Indices," Boston University - Department of Economics - Working Papers Series wp2008-004, Boston University - Department of Economics.
    7. Valadkhani, Abbas, 2023. "Asymmetric downside risk across different sectors of the US equity market," Global Finance Journal, Elsevier, vol. 57(C).
    8. Simone Alfarano & Thomas Lux, 2007. "A Minimal Noise Trader Model with Realistic Time Series Properties," Springer Books, in: Gilles Teyssière & Alan P. Kirman (ed.), Long Memory in Economics, pages 345-361, Springer.
    9. Bertram, William K. & Peiris, M. Shelton, 2007. "An example of a misclassification problem applied to Australian equity data," Computational Statistics & Data Analysis, Elsevier, vol. 51(8), pages 3627-3630, May.
    10. Melike Bildirici & Nilgun Guler Bayazit & Yasemen Ucan, 2020. "Analyzing Crude Oil Prices under the Impact of COVID-19 by Using LSTARGARCHLSTM," Energies, MDPI, vol. 13(11), pages 1-18, June.
    11. Silvestro Di Sanzo, 2007. "Forecasting Time Series with Long Memory and Level Shifts, A Bayesian Approach," Working Papers 2007_03, Department of Economics, University of Venice "Ca' Foscari".
    12. McMillan, David G., 2009. "Are share prices still too high?," Research in International Business and Finance, Elsevier, vol. 23(3), pages 223-232, September.
    13. Lux, Thomas & Kaizoji, Taisei, 2006. "Forecasting volatility and volume in the Tokyo stock market: Long memory, fractality and regime switching," Economics Working Papers 2006-13, Christian-Albrechts-University of Kiel, Department of Economics.
    14. Robinson Kruse & Philipp Sibbertsen, 2010. "Long memory and changing persistence," CREATES Research Papers 2010-42, Department of Economics and Business Economics, Aarhus University.
    15. Lux, Thomas & Morales-Arias, Leonardo, 2010. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2676-2692, November.
    16. Charfeddine, Lanouar, 2016. "Breaks or long range dependence in the energy futures volatility: Out-of-sample forecasting and VaR analysis," Economic Modelling, Elsevier, vol. 53(C), pages 354-374.
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    25. Lux, Thomas & Morales-Arias, Leonardo, 2009. "Forecasting volatility under fractality, regime-switching, long memory and student-t innovations," Kiel Working Papers 1532, Kiel Institute for the World Economy (IfW Kiel).
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    36. Lux, Thomas & Morales-Arias, Leonardo & Sattarhoff, Cristina, 2011. "A Markov-switching multifractal approach to forecasting realized volatility," Kiel Working Papers 1737, Kiel Institute for the World Economy (IfW Kiel).
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    42. Mawuli Segnon & Thomas Lux & Rangan Gupta, 2015. "Modeling and Forecasting Carbon Dioxide Emission Allowance Spot Price Volatility: Multifractal vs. GARCH-Type Volatility Models," Working Papers 201550, University of Pretoria, Department of Economics.
    43. Yoon, Gawon, 2009. "Is high real interest rate persistence an intrinsic characteristic of industrialized economies?," Economic Modelling, Elsevier, vol. 26(2), pages 359-363, March.
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    105. Leschinski, Christian & Sibbertsen, Philipp, 2017. "Origins of Spurious Long Memory," Hannover Economic Papers (HEP) dp-595, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    106. Leschinski, Christian & Sibbertsen, Philipp, 2018. "The Periodogram of Spurious Long-Memory Processes," Hannover Economic Papers (HEP) dp-632, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    107. Assaf, Ata, 2015. "Long memory and level shifts in REITs returns and volatility," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 172-182.
    108. Mawuli Segnon & Stelios Bekiros, 2019. "Forecasting Volatility in Cryptocurrency Markets," CQE Working Papers 7919, Center for Quantitative Economics (CQE), University of Muenster.

  71. Teräsvirta, Timo & Eliasson, Ann-Charlotte, 1998. "Nonlinear error-correction and the UK demand for broad money, 1878-1993," SSE/EFI Working Paper Series in Economics and Finance 265, Stockholm School of Economics, revised 30 Nov 1998.

    Cited by:

    1. Luis E. Arango & Andrés González, 2000. "A Nonlinear Specification of Demand for Cash in Colombia," Money Affairs, CEMLA, vol. 0(2), pages 207-226, July-Dece.
    2. Luis Eduardo Arango & Andrés González, 1999. "A Nonlinear Specification Of Demand For Narrow Money In Colombia," Borradores de Economia 1894, Banco de la Republica.
    3. Zenón Quispe, 2000. "Monetary Policy in a Dollarized Economy: the Case of Peru," Money Affairs, CEMLA, vol. 0(2), pages 167-206, July-Dece.
    4. Agustín G. Cartens & Alejandro M. Werner, 2000. "Mexico's Monetary Policy Framework Under a Floating Exchange Rate Regime," Money Affairs, CEMLA, vol. 0(2), pages 113-165, July-Dece.

  72. Lundbergh, Stefan & Teräsvirta, Timo, 1998. "Evaluating GARCH models," SSE/EFI Working Paper Series in Economics and Finance 292, Stockholm School of Economics, revised 03 Oct 2001.

    Cited by:

    1. Luis Fernando Melo Velandia & Oscar Reinaldo Becerra Camargo, 2005. "Medidas De Riesgo, Caracteristicas Y Técnicas De Medición: Una Aplicación Del Var Y El Es A La Tasa Interbancaria De Colombia," Borradores de Economia 3198, Banco de la Republica.
    2. Elena Andreou, 2004. "The Impact of Sampling Frequency and Volatility Estimators on Change-Point Tests," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 290-318.
    3. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    4. Eduardo Lima & Benjamin Tabak, 2009. "Tests of Random Walk: A Comparison of Bootstrap Approaches," Computational Economics, Springer;Society for Computational Economics, vol. 34(4), pages 365-382, November.
    5. Alagidede, Paul & Panagiotidis, Theodore, 2009. "Modelling stock returns in Africa's emerging equity markets," Stirling Economics Discussion Papers 2009-04, University of Stirling, Division of Economics.
    6. Herwartz, Helmut, 2017. "Stock return prediction under GARCH — An empirical assessment," International Journal of Forecasting, Elsevier, vol. 33(3), pages 569-580.
    7. Ahdi N. Ajmi & Vassilios Babalos & Fotini Economou & Rangan Gupta, 2014. "Real Estate Markets and Uncertainty Shocks: A Variance Causality Approach," Working Papers 201436, University of Pretoria, Department of Economics.
    8. Carlos Escanciano, J., 2008. "Joint and marginal specification tests for conditional mean and variance models," Journal of Econometrics, Elsevier, vol. 143(1), pages 74-87, March.
    9. Mika Meitz & Pentti Saikkonen & University of Helsinki, 2007. "Stability of nonlinear AR-GARCH models," Economics Series Working Papers 328, University of Oxford, Department of Economics.
    10. Tsatsura, Oleg, 2010. "A Smooth Transition GARCH-M Model," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 17(1), pages 45-61.
    11. Sofiane Aboura & Julien Chevallier, 2014. "Cross-Market Spillovers with ‘Volatility Surprise’," EconomiX Working Papers 2014-46, University of Paris Nanterre, EconomiX.
    12. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    13. Conrad, Christian & Schienle, Melanie, 2019. "Testing for an omitted multiplicative long-term component in GARCH models," Working Paper Series in Economics 121, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    14. Paul Catani & Timo Teräsvirta & Meiqun Yin, 2017. "A Lagrange multiplier test for testing the adequacy of constant conditional correlation GARCH model," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 599-621, October.
    15. Andreou, Elena & Werker, Bas J.M., 2015. "Residual-based rank specification tests for AR–GARCH type models," Journal of Econometrics, Elsevier, vol. 185(2), pages 305-331.
    16. Zhongjun Qu & Yi-Ting Chen, 2010. "M Tests with a New Normalization Matrix," Boston University - Department of Economics - Working Papers Series WP2010-050, Boston University - Department of Economics.
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    18. Berben, Robert-Paul & Jansen, W. Jos, 2005. "Comovement in international equity markets: A sectoral view," Journal of International Money and Finance, Elsevier, vol. 24(5), pages 832-857, September.
    19. Dominique Guegan & Bertrand K. Hassani, 2019. "Risk Measurement," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02119256, HAL.
    20. Christina Amado & Timo Teräsvirta, 2008. "Modelling Conditional and Unconditional Heteroskedasticity with Smoothly Time-Varying Structure," CREATES Research Papers 2008-08, Department of Economics and Business Economics, Aarhus University.
    21. Adnen Ben Nasr & Ahdi N. Ajmi & Rangan Gupta, 2013. "Modeling the Volatility of the Dow Jones Islamic Market World Index Using a Fractionally Integrated Time Varying GARCH (FITVGARCH) Model," Working Papers 201357, University of Pretoria, Department of Economics.
    22. Mika Meitz & Pentti Saikkonen, 2008. "Parameter estimation in nonlinear AR-GARCH models," Economics Series Working Papers 396, University of Oxford, Department of Economics.
    23. Hafner, Christian M. & Herwartz, Helmut, 2006. "A Lagrange multiplier test for causality in variance," Economics Letters, Elsevier, vol. 93(1), pages 137-141, October.
    24. Steffen Henzel & Malte Rengel, 2013. "Dimensions of macroeconomic uncertainty: A common factor analysis," ifo Working Paper Series 167, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    25. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, January.
    26. Wasel Shadat, 2011. "On the Nonparametric Tests of Univariate GARCH Regression Models," Economics Discussion Paper Series 1115, Economics, The University of Manchester.
    27. Ginny ju-ann Yang & Koyin Chang & Yung-Hsiang Ying & Chen-hsun Lee, 2014. "Spillover Effects of Chinese Stock Markets," Economics Bulletin, AccessEcon, vol. 34(1), pages 200-205.
    28. Timo Terasvirta & Zhenfang Zhao, 2011. "Stylized facts of return series, robust estimates and three popular models of volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 21(1-2), pages 67-94.
    29. Evangelos Vasileiou, 2022. "Inaccurate Value at Risk Estimations: Bad Modeling or Inappropriate Data?," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1155-1171, March.
    30. Mika Meitz & Pentti Saikkonen & University of Helsinki, 2007. "Ergodicity, mixing, and existence of moments of a class of Markov models with applications to GARCH and ACD models," Economics Series Working Papers 327, University of Oxford, Department of Economics.
    31. Andreou, E. & Werker, B.J.M., 2004. "An Alternative Asymptotic Analysis of Residual-Based Statistics," Discussion Paper 2004-56, Tilburg University, Center for Economic Research.
    32. Yi-Ting Chen, 2008. "A unified approach to standardized-residuals-based correlation tests for GARCH-type models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 23(1), pages 111-133.
    33. Day Yang Liu & Ming Chen Chun & Yi Kai Su, 2021. "The impacts of Covid-19 pandemic on the smooth transition dynamics of stock market index volatilities for the Four Asian Tigers and Japan," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 10(4), pages 183-194, June.
    34. Lütkepohl,Helmut & Krätzig,Markus (ed.), 2004. "Applied Time Series Econometrics," Cambridge Books, Cambridge University Press, number 9780521547871, January.
    35. Bouri, Elie & Chen, Qian & Lien, Donald & Lv, Xin, 2017. "Causality between oil prices and the stock market in China: The relevance of the reformed oil product pricing mechanism," International Review of Economics & Finance, Elsevier, vol. 48(C), pages 34-48.
    36. Day-Yang Liu & Chun-Ming Chen & Yi-Kai Su, 2020. "The Impact of COVID-19 Pandemic on the Smooth Transition Dynamics of Broad-based Indices Volatilities in Taiwan," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 10(5), pages 1-14.
    37. Wong, Woon K. & Tu, Anthony H., 2009. "Market imperfections and the information content of implied and realized volatility," Pacific-Basin Finance Journal, Elsevier, vol. 17(1), pages 58-79, January.
    38. Omay, Tolga & Iren, Perihan, 2019. "Behavior of foreign investors in the Malaysian stock market in times of crisis: A nonlinear approach," Journal of Asian Economics, Elsevier, vol. 60(C), pages 85-100.
    39. Meitz, Mika & Terasvirta, Timo, 2006. "Evaluating Models of Autoregressive Conditional Duration," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 104-124, January.
    40. Chuffart Thomas & Flachaire Emmanuel & Péguin-Feissolle Anne, 2018. "Testing for misspecification in the short-run component of GARCH-type models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-17, December.
    41. Yi-Ting Chen, 2016. "Testing for Granger Causality in Moments," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 78(2), pages 265-288, April.
    42. Lundbergh, Stefan & Terasvirta, Timo, 2006. "A time series model for an exchange rate in a target zone with applications," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 579-609.
    43. Conrad, Christian & Schienle, Melanie, 2015. "Misspecification Testing in GARCH-MIDAS Models," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112919, Verein für Socialpolitik / German Economic Association.
    44. Chen, Yi-Ting, 2012. "A simple approach to standardized-residuals-based higher-moment tests," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 427-453.
    45. Malmsten, Hans & Teräsvirta, Timo, 2004. "Stylized Facts of Financial Time Series and Three Popular Models of Volatility," SSE/EFI Working Paper Series in Economics and Finance 563, Stockholm School of Economics, revised 03 Sep 2004.
    46. Christian Conrad & Robert F. Engle, 2021. "Modelling Volatility Cycles: The (MF)2 GARCH Model," Working Paper series 21-05, Rimini Centre for Economic Analysis.
    47. Stavroula Yfanti & Georgios Chortareas & Menelaos Karanasos & Emmanouil Noikokyris, 2022. "A three‐dimensional asymmetric power HEAVY model," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 2737-2761, July.
    48. Carlos Velasco & Xuexin Wang, 2015. "A Joint Portmanteau Test For Conditional Mean And Variance Time-Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(1), pages 39-60, January.
    49. Berkes, Istvan & Horváth, Lajos & Kokoszka, Piotr, 2004. "Testing for parameter constancy in GARCH(p,q) models," Statistics & Probability Letters, Elsevier, vol. 70(4), pages 263-273, December.
    50. Belkhouja, Mustapha & Mootamri, Imene, 2016. "Long memory and structural change in the G7 inflation dynamics," Economic Modelling, Elsevier, vol. 54(C), pages 450-462.
    51. Catani, P.S. & Ahlgren, N.J.C., 2017. "Combined Lagrange multiplier test for ARCH in vector autoregressive models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 62-84.
    52. McAleer, Michael & Medeiros, Marcelo C., 2008. "A multiple regime smooth transition Heterogeneous Autoregressive model for long memory and asymmetries," Journal of Econometrics, Elsevier, vol. 147(1), pages 104-119, November.
    53. Sofiane Aboura & Julien Chevallier, 2015. "Volatility returns with vengeance: Financial markets vs. commodities," Post-Print hal-01529747, HAL.
    54. Hsiang-Hsi Liu & Chun-Chou Wu & Yi Kai Su, 2012. "The influence of direct cross-straits shipping on the smooth transition dynamics of stock volatilities of shipping companies," Applied Financial Economics, Taylor & Francis Journals, vol. 22(16), pages 1331-1342, August.
    55. Bhatti, Chad R., 2010. "The Birnbaum–Saunders autoregressive conditional duration model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(10), pages 2062-2078.
    56. Andreou, E. & Werker, B.J.M., 2004. "An Alternative Asymptotic Analysis of Residual-Based Statistics," Other publications TiSEM 93fe16c1-9f21-4dab-9b73-4, Tilburg University, School of Economics and Management.
    57. Belkhouja, Mustapha & Boutahary, Mohamed, 2011. "Modeling volatility with time-varying FIGARCH models," Economic Modelling, Elsevier, vol. 28(3), pages 1106-1116, May.
    58. Bouri, Elie, 2015. "Oil volatility shocks and the stock markets of oil-importing MENA economies: A tale from the financial crisis," Energy Economics, Elsevier, vol. 51(C), pages 590-598.
    59. Malmsten, Hans, 2004. "Evaluating exponential GARCH models," SSE/EFI Working Paper Series in Economics and Finance 564, Stockholm School of Economics, revised 03 Sep 2004.
    60. Fredj Jawadi & Mohamed Hedi Arouri & Duc Khuong Nguyen, 2010. "Global financial crisis, liquidity pressure in stock markets and efficiency of central bank interventions," Applied Financial Economics, Taylor & Francis Journals, vol. 20(8), pages 669-680.
    61. Xu, Ke-Li, 2013. "Powerful tests for structural changes in volatility," Journal of Econometrics, Elsevier, vol. 173(1), pages 126-142.
    62. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2017. "Modelling and forecasting WIG20 daily returns," CREATES Research Papers 2017-29, Department of Economics and Business Economics, Aarhus University.
    63. Halunga, Andreea G. & Orme, Chris D., 2009. "First-Order Asymptotic Theory For Parametric Misspecification Tests Of Garch Models," Econometric Theory, Cambridge University Press, vol. 25(2), pages 364-410, April.
    64. Wasel Shadat & Chris Orme, 2011. "An investigation of parametric tests of CCC assumption," Economics Discussion Paper Series 1109, Economics, The University of Manchester.
    65. Cristina Amado & Timo Teräsvirta, 2017. "Specification and testing of multiplicative time-varying GARCH models with applications," Econometric Reviews, Taylor & Francis Journals, vol. 36(4), pages 421-446, April.
    66. Sofiane Aboura & Julien Chevallier, 2014. "Cross-Market Spillovers with ‘Volatility Surprise’," Working Papers hal-04141310, HAL.
    67. Haipeng Xing & Hongsong Yuan & Sichen Zhou, 2017. "A Mixtured Localized Likelihood Method for GARCH Models with Multiple Change-points," Review of Economics & Finance, Better Advances Press, Canada, vol. 8, pages 44-60, May.
    68. Daniel Smith, 2008. "Testing for structural breaks in GARCH models," Applied Financial Economics, Taylor & Francis Journals, vol. 18(10), pages 845-862.
    69. Conrad, Christian & Schienle, Melanie, 2015. "Misspecification Testing in GARCH-MIDAS Models," Working Papers 0597, University of Heidelberg, Department of Economics.
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    Cited by:

    1. SAIBU, Olufemi Muibi & FAKANBI, KEHINDE Ernest & AGBOOLA, Olawode Wasiu, 2011. "Political dispensation and macroeconomic performance in Nigeria (1970-2009)," MPRA Paper 34821, University Library of Munich, Germany.
    2. Lütkepohl, Helmut & Schlaak, Thore, 2019. "Bootstrapping impulse responses of structural vector autoregressive models identified through GARCH," Journal of Economic Dynamics and Control, Elsevier, vol. 101(C), pages 41-61.
    3. HAFNER, Christian, 2001. "Fourth moments of multivariate GARCH processes," LIDAM Discussion Papers CORE 2001046, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    4. Caporale, Guglielmo Maria & Ntantamis, Christos & Pantelidis, Theologos & Pittis, Nikitas, 2004. "The BDS Test as a Test for the Adequacy of a GARCH(1,1) Specification. A Monte Carlo Study," Economics Series 156, Institute for Advanced Studies.
    5. Menelaos Karanasos & Zacharias Psaradakis & Martin Sola, "undated". "Cross-Sectional Aggregation and Persistence in Conditional Variance," Discussion Papers 00/09, Department of Economics, University of York.
    6. Changli He & Annastiina Silvennoinen & Timo Teräsvirta, 2008. "Parameterizing unconditional skewness in models for financial time series," CREATES Research Papers 2008-07, Department of Economics and Business Economics, Aarhus University.
    7. He, Changli & Teräsvirta, Timo, 1997. "Properties of Moments of a Family of GARCH Processes," SSE/EFI Working Paper Series in Economics and Finance 198, Stockholm School of Economics.
    8. Thavaneswaran, A. & Appadoo, S.S. & Peiris, S., 2005. "Forecasting volatility," Statistics & Probability Letters, Elsevier, vol. 75(1), pages 1-10, November.
    9. Feng, Yuanhua, 2002. "Modelling Different Volatility Components," CoFE Discussion Papers 02/18, University of Konstanz, Center of Finance and Econometrics (CoFE).
    10. Menelaos Karanasos, "undated". "Some Exact Formulae for the Constant Correlation and Diagonal M - Garch Models," Discussion Papers 00/14, Department of Economics, University of York.
    11. Theologos Pantelidis & Nikitas Pittis, 2009. "Estimation and forecasting in first-order vector autoregressions with near to unit roots and conditional heteroscedasticity," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 28(7), pages 612-630.
    12. Biao Wu, Wei & Min, Wanli, 2005. "On linear processes with dependent innovations," Stochastic Processes and their Applications, Elsevier, vol. 115(6), pages 939-958, June.
    13. Niklas Ahlgren & Alexander Back & Timo Terasvirta, 2024. "A new GARCH model with a deterministic time-varying intercept," Papers 2410.03239, arXiv.org, revised Oct 2024.
    14. Ling, Shiqing & McAleer, Michael, 2002. "Stationarity and the existence of moments of a family of GARCH processes," Journal of Econometrics, Elsevier, vol. 106(1), pages 109-117, January.
    15. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521817707, January.
    16. W. K. Li & Shiqing Ling & Michael McAleer, 2001. "A Survey of Recent Theoretical Results for Time Series Models with GARCH Errors," ISER Discussion Paper 0545, Institute of Social and Economic Research, Osaka University.
    17. Antonis Demos, 2002. "Moments and dynamic structure of a time-varying parameter stochastic volatility in mean model," Econometrics Journal, Royal Economic Society, vol. 5(2), pages 345-357, June.
    18. Pasquale Tridico & Riccardo Pariboni, 2017. "Structural Change, Aggregate Demand And The Decline Of Labour Productivity: A Comparative Perspective," Departmental Working Papers of Economics - University 'Roma Tre' 0221, Department of Economics - University Roma Tre.
    19. Stelios Arvanitis & Antonis Demos, 2004. "Time Dependence and Moments of a Family of Time‐Varying Parameter Garch in Mean Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(1), pages 1-25, January.
    20. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654, January.
    21. Alexander, Carol & Lazar, Emese & Stanescu, Silvia, 2021. "Analytic moments for GJR-GARCH (1, 1) processes," International Journal of Forecasting, Elsevier, vol. 37(1), pages 105-124.
    22. Alessandra Canepa, & Karanasos, Menelaos & Paraskevopoulos, Athanasios & Chini, Emilio Zanetti, 2022. "Forecasting Ination: A GARCH-in-Mean-Level Model with Time Varying Predictability," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202212, University of Turin.
    23. Andreou, Elena & Ghysels, Eric, 2006. "Monitoring disruptions in financial markets," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 77-124.
    24. Murat Midilic, 2016. "Estimation Of Star-Garch Models With Iteratively Weighted Least Squares," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 16/918, Ghent University, Faculty of Economics and Business Administration.
    25. Robert Engle, 2002. "New frontiers for arch models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 425-446.
    26. Feng, Yuanhua & Beran, Jan & Yu, Keming, 2007. "Modelling financial time series with SEMIFAR-GARCH model," CoFE Discussion Papers 07/14, University of Konstanz, Center of Finance and Econometrics (CoFE).
    27. Giraitis, Liudas & Surgailis, Donatas, 0. "ARCH-type bilinear models with double long memory," Stochastic Processes and their Applications, Elsevier, vol. 100(1-2), pages 275-300, July.
    28. Feng, Yuanhua & Härdle, Wolfgang Karl, 2020. "A data-driven P-spline smoother and the P-Spline-GARCH models," IRTG 1792 Discussion Papers 2020-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    29. Han, Heejoon & Park, Joon Y., 2012. "ARCH/GARCH with persistent covariate: Asymptotic theory of MLE," Journal of Econometrics, Elsevier, vol. 167(1), pages 95-112.
    30. Feng, Yuanhua & McNeil, Alexander J., 2008. "Modelling of scale change, periodicity and conditional heteroskedasticity in return volatility," Economic Modelling, Elsevier, vol. 25(5), pages 850-867, September.
    31. Alistair Mees & Berndt Pilgram, 2000. "Non-Linear Markov Modelling Using Canonical Variate Analysis: Forecasting Exchange Rate Volatility," Econometric Society World Congress 2000 Contributed Papers 1162, Econometric Society.
    32. Carol Alexander & Emese Lazar & Silvia Stanescu, 2010. "Analytic Moments for GARCH Processes," ICMA Centre Discussion Papers in Finance icma-dp2011-07, Henley Business School, University of Reading, revised Apr 2011.
    33. Felix Chan & Michael McAleer, 2002. "Maximum likelihood estimation of STAR and STAR-GARCH models: theory and Monte Carlo evidence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 509-534.
    34. Malmsten, Hans & Teräsvirta, Timo, 2004. "Stylized Facts of Financial Time Series and Three Popular Models of Volatility," SSE/EFI Working Paper Series in Economics and Finance 563, Stockholm School of Economics, revised 03 Sep 2004.
    35. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    36. Shelton Peiris & Tim Swartz, 2020. "Revisiting the Kurtosis of Stationary Processes with Applications to Volatility Models," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(2), pages 1-1.
    37. Peter A. Zadrozny, 2005. "Necessary and Sufficient Restrictions for Existence of a Unique Fourth Moment of a Univariate GARCH(p,q) Process," CESifo Working Paper Series 1505, CESifo.
    38. Davide De Gaetano, 2017. "A Bootstrap Bias Correction Of Long Run Fourth Order Moment Estimation In The Cusum Of Squares Test," Departmental Working Papers of Economics - University 'Roma Tre' 0220, Department of Economics - University Roma Tre.
    39. Kazakevicius, Vytautas & Leipus, Remigijus & Viano, Marie-Claude, 2004. "Stability of random coefficient ARCH models and aggregation schemes," Journal of Econometrics, Elsevier, vol. 120(1), pages 139-158, May.
    40. Karanasos, Menelaos & Kim, Jinki, 2006. "A re-examination of the asymmetric power ARCH model," Journal of Empirical Finance, Elsevier, vol. 13(1), pages 113-128, January.
    41. Wilfredo Palma & Mauricio Zevallos, 2004. "Analysis of the correlation structure of square time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(4), pages 529-550, July.
    42. Shiqing Ling & Michael McAleer, 2001. "Necessary and Sufficient Moment Conditions for the GARCH(r,s) and Asymmetric Power GARCH(r,s) Models," ISER Discussion Paper 0534, Institute of Social and Economic Research, Osaka University.
    43. Murat Midiliç, 2020. "Estimation of STAR–GARCH Models with Iteratively Weighted Least Squares," Computational Economics, Springer;Society for Computational Economics, vol. 55(1), pages 87-117, January.
    44. Pantelidis, Theologos & Pittis, Nikitas, 2004. "Testing for Granger causality in variance in the presence of causality in mean," Economics Letters, Elsevier, vol. 85(2), pages 201-207, November.
    45. Park, Joon Y., 2002. "Nonstationary nonlinear heteroskedasticity," Journal of Econometrics, Elsevier, vol. 110(2), pages 383-415, October.
    46. Anatolyev Stanislav, 2019. "Volatility filtering in estimation of kurtosis (and variance)," Dependence Modeling, De Gruyter, vol. 7(1), pages 1-23, February.
    47. Menelaos Karanasos & J. Kim, "undated". "Alternative GARCH in Mean Models: An Application to the Korean Stock Market," Discussion Papers 00/25, Department of Economics, University of York.
    48. Bai, Xuezheng & Russell, Jeffrey R. & Tiao, George C., 2003. "Kurtosis of GARCH and stochastic volatility models with non-normal innovations," Journal of Econometrics, Elsevier, vol. 114(2), pages 349-360, June.
    49. Alessandra Canepa, & Menelaos G. Karanasos & Alexandros G. Paraskevopoulos,, 2019. "Second Order Time Dependent Inflation Persistence in the United States: a GARCH-in-Mean Model with Time Varying Coefficients," Department of Economics and Statistics Cognetti de Martiis. Working Papers 201911, University of Turin.

  74. He, Changli & Teräsvirta, Timo, 1997. "Properties of the Autocorrelation Function of Squared Observations for Second Order GARCH Processes under Two Sets of Parameter Constraints," SSE/EFI Working Paper Series in Economics and Finance 169, Stockholm School of Economics.

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    1. Georgios Bampinas & Konstantinos Ladopoulos & Theodore Panagiotidis, 2018. "A note on the estimated GARCH coefficients from the S&P1500 universe," Applied Economics, Taylor & Francis Journals, vol. 50(34-35), pages 3647-3653, July.
    2. Jurgen A. Doornik & Marius Ooms, 2003. "Multimodality in the GARCH Regression Model," Economics Papers 2003-W20, Economics Group, Nuffield College, University of Oxford.
    3. Feng, Yuanhua & Beran, Jan & Yu, Keming, 2007. "Modelling financial time series with SEMIFAR-GARCH model," CoFE Discussion Papers 07/14, University of Konstanz, Center of Finance and Econometrics (CoFE).

  75. He, Changli & Teräsvirta, Timo, 1997. "Statistical Properties of the Asymmetric Power ARCH Process," SSE/EFI Working Paper Series in Economics and Finance 199, Stockholm School of Economics, revised 30 Sep 1997.

    Cited by:

    1. Christian Gourieroux & Joann Jasiak, 1999. "Nonlinear Persistence and Copersistence," Working Papers 2000_1, York University, Department of Economics.
    2. He, Changli & Teräsvirta, Timo, 1997. "Properties of Moments of a Family of GARCH Processes," SSE/EFI Working Paper Series in Economics and Finance 198, Stockholm School of Economics.
    3. Javed Farrukh & Podgórski Krzysztof, 2017. "Tail Behavior and Dependence Structure in the APARCH Model," Journal of Time Series Econometrics, De Gruyter, vol. 9(2), pages 1-48, July.
    4. Carnero, María Ángeles, 2001. "Outliers and conditional autoregressive heteroscedasticity in time series," DES - Working Papers. Statistics and Econometrics. WS ws010704, Universidad Carlos III de Madrid. Departamento de Estadística.

  76. He, Changli & Teräsvirta, Timo, 1997. "Properties of Moments of a Family of GARCH Processes," SSE/EFI Working Paper Series in Economics and Finance 198, Stockholm School of Economics.

    Cited by:

    1. Haas Markus, 2010. "Skew-Normal Mixture and Markov-Switching GARCH Processes," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-56, September.
    2. H. Peter Boswijk & Giuseppe Cavaliere & Anders Rahbek & A. M. Robert Taylor, 2013. "Inference on Co-integration Parameters in Heteroskedastic Vector Autoregressions," Tinbergen Institute Discussion Papers 13-187/III, Tinbergen Institute.
    3. Haas, Markus, 2010. "Covariance forecasts and long-run correlations in a Markov-switching model for dynamic correlations," Finance Research Letters, Elsevier, vol. 7(2), pages 86-97, June.
    4. Kilian, Lutz & Gonçalves, Sílvia, 2002. "Bootstrapping Autoregressions with Conditional Heteroskedasticity of Unknown Form," Discussion Paper Series 1: Economic Studies 2002,26, Deutsche Bundesbank.
    5. Herwartz, Helmut, 2017. "Stock return prediction under GARCH — An empirical assessment," International Journal of Forecasting, Elsevier, vol. 33(3), pages 569-580.
    6. Broto, Carmen, 2003. "Unobserved component models with asymmetric conditional variances," DES - Working Papers. Statistics and Econometrics. WS ws032003, Universidad Carlos III de Madrid. Departamento de Estadística.
    7. Audrone Virbickaite & M. Concepción Ausín & Pedro Galeano, 2015. "Bayesian Inference Methods For Univariate And Multivariate Garch Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 76-96, February.
    8. Stan Hurn & Ralf Becker, 2006. "Testing for nonlinearity in mean in the presence of heteroskedasticity," Stan Hurn Discussion Papers 2006-02, School of Economics and Finance, Queensland University of Technology.
    9. Li, Ming-Yuan Leon, 2008. "Clarifying the dynamics of the relationship between option and stock markets using the threshold vector error correction model," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(3), pages 511-520.
    10. Felix Chan & Dora Marinova & Michael McAleer, 2004. "Trends and volatilities in foreign patents registered in the USA," Applied Economics, Taylor & Francis Journals, vol. 36(6), pages 585-592.
    11. Karanasos, Menelaos & Xu, Yongdeng & Yfanti, Stavroula, 2017. "Constrained QML Estimation for Multivariate Asymmetric MEM with Spillovers: The Practicality of Matrix Inequalities," Cardiff Economics Working Papers E2017/14, Cardiff University, Cardiff Business School, Economics Section.
    12. Pitt, M.K. & Walker, S.G., 2001. "Construction of Stationary Time Series via the Giggs Sampler with Application to Volatility Models," The Warwick Economics Research Paper Series (TWERPS) 595, University of Warwick, Department of Economics.
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    14. Rodríguez, Mª José, 2009. "GARCH models with leverage effect : differences and similarities," DES - Working Papers. Statistics and Econometrics. WS ws090302, Universidad Carlos III de Madrid. Departamento de Estadística.
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    47. Watkins, Clinton & McAleer, Michael, 2005. "Related commodity markets and conditional correlations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 68(5), pages 567-579.
    48. Baye Matar Kandji, 2023. "On the growth rate of superadditive processes and the stability of functional GARCH models," Working Papers 2023-07, Center for Research in Economics and Statistics.
    49. He, Changli & Teräsvirta, Timo, 1999. "Higher-order dependence in the general Power ARCH process and a special case," SSE/EFI Working Paper Series in Economics and Finance 315, Stockholm School of Economics.
    50. Carlos Velasco & Ignacio N. Lobato, 2004. "A simple and general test for white noise," Econometric Society 2004 Latin American Meetings 112, Econometric Society.
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    53. Kirt C. Butler & Katsushi Okada, 2008. "Higher-Order Terms in Bivariate Returns to International Stock Market Indices," Multinational Finance Journal, Multinational Finance Journal, vol. 12(1-2), pages 127-155, March-Jun.
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    81. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2023. "Building Multivariate Time-Varying Smooth Transition Correlation GARCH Models, with an Application to the Four Largest Australian Banks," Econometrics, MDPI, vol. 11(1), pages 1-37, February.
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    90. Tarek Bouazizi & Zouhaier Hadhek & Fatma Mrad & Mosbah Lafi, 2021. "Changes in Demand for Crude Oil and its Correlation with Crude Oil and Stock Market Returns Volatilities: Evidence from Three Asian Oil Importing Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 11(3), pages 27-43.
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    Cited by:

    1. Eklund, Bruno, 2005. "Estimating confidence regions over bounded domains," Computational Statistics & Data Analysis, Elsevier, vol. 49(2), pages 349-360, April.
    2. Behmiri, Niaz Bashiri & Manera, Matteo, 2015. "The role of outliers and oil price shocks on volatility of metal prices," Resources Policy, Elsevier, vol. 46(P2), pages 139-150.
    3. Grané, Aurea & Veiga, Helena, 2010. "Wavelet-based detection of outliers in financial time series," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2580-2593, November.
    4. Franses, Philip Hans & Ghijsels, Hendrik, 1999. "Additive outliers, GARCH and forecasting volatility," International Journal of Forecasting, Elsevier, vol. 15(1), pages 1-9, February.

  78. Skalin, Joakim & Teräsvirta, Timo, 1996. "Another Look at Swedish Business Cycles, 1861-1988," SSE/EFI Working Paper Series in Economics and Finance 130, Stockholm School of Economics.

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    1. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
    2. Nidhaleddine Ben Cheikh & Sami Ben Naceur & Oussama Kanaan & Christophe Rault, 2018. "Oil Prices and GCC Stock Markets: New Evidence from Smooth Transition Models," CESifo Working Paper Series 7072, CESifo.
    3. Juan Carlos Cuestas & Estefanía Mourelle, 2009. "Inflation persistence and asymmetries: evidence for African countries," NBS Discussion Papers in Economics 2009/2, Economics, Nottingham Business School, Nottingham Trent University.
    4. Röthig, Andreas & Chiarella, Carl, 2006. "Investigating nonlinear speculation in cattle, corn, and hog futures markets using logistic smooth transition regression models," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 36774, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    5. van Dijk, D.J.C. & Franses, Ph.H.B.F., 1997. "Modelling Multiple Regimes in the Business Cycle," Econometric Institute Research Papers EI 9734/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    6. P Mejía-Reyes & D R Osborn & M Sensier, 2004. "Modelling Real Exchange Rate Effects on Output Performance in Latin America," Centre for Growth and Business Cycle Research Discussion Paper Series 35, Economics, The University of Manchester.
    7. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2012. "The Out-of-Sample Forecasting Performance of Non-Linear Models of Regional Housing Prices in the US," Working papers 2012-12, University of Connecticut, Department of Economics.
    8. Zheng Guihuan & Shang Yan & Wu Ying & Wang Jue, 2014. "A Study on the Asymmetry in the Role of Monetary Policy by Using STR model," Journal of Systems Science and Information, De Gruyter, vol. 2(3), pages 236-243, June.
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    105. Krishnamurthy, Vikram & Leoff, Elisabeth & Sass, Jörn, 2018. "Filterbased stochastic volatility in continuous-time hidden Markov models," Econometrics and Statistics, Elsevier, vol. 6(C), pages 1-21.
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    107. Emmanuel Numapau Gyamfi & Kwabena A. Kyei, 2016. "Modeling Stock Market Returns under Self-exciting Threshold Autoregressive Model: Evidence from West Africa," International Journal of Economics and Financial Issues, Econjournals, vol. 6(3), pages 1194-1199.
    108. Zolotoy, L., 2008. "Empirical essays on the information transfer between and the informational efficiency of stock markets," Other publications TiSEM 2a2652c6-1060-4622-8721-8, Tilburg University, School of Economics and Management.
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    111. Nektarios Aslanidis, 2002. "Regime-switching behaviour in European," Working Papers 0202, University of Crete, Department of Economics.
    112. Emilio Cardona & Andrés Mora-Valencia & Daniel Velásquez-Gaviria, 2019. "Testing expected shortfall: an application to emerging market stock indices," Risk Management, Palgrave Macmillan, vol. 21(3), pages 153-182, September.
    113. Focardi, Sergio M. & Fabozzi, Frank J. & Mazza, Davide, 2019. "Modeling local trends with regime shifting models with time-varying probabilities," International Review of Financial Analysis, Elsevier, vol. 66(C).
    114. Li, Chenxing, 2022. "A multivariate GARCH model with an infinite hidden Markov mixture," MPRA Paper 112792, University Library of Munich, Germany.
    115. Demian Pouzo & Zacharias Psaradakis & Martín Sola, 2024. "On the Robustness of Mixture Models in the Presence of Hidden Markov Regimes with Covariate-Dependent Transition Probabilities," Department of Economics Working Papers 2024_04, Universidad Torcuato Di Tella.
    116. Kristian Gundersen & Timothée Bacri & Jan Bulla & Sondre Hølleland & Antonello Maruotti & Bård Støve, 2024. "Testing for time‐varying nonlinear dependence structures: Regime‐switching and local Gaussian correlation," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 51(3), pages 1012-1060, September.
    117. Nilsson, Birger, 2002. "Financial Liberalization and the Changing Characteristics of Nordic Stock Returns," Working Papers 2002:4, Lund University, Department of Economics.
    118. Richard D. F. Harris & Murat Mazibas, 2022. "A component Markov regime‐switching autoregressive conditional range model," Bulletin of Economic Research, Wiley Blackwell, vol. 74(2), pages 650-683, April.
    119. Huang, Yan & Kou, Gang & Peng, Yi, 2017. "Nonlinear manifold learning for early warnings in financial markets," European Journal of Operational Research, Elsevier, vol. 258(2), pages 692-702.
    120. Elie Bouri & Rangan Gupta & Shixuan Wang, 2022. "Nonlinear contagion between stock and real estate markets: International evidence from a local Gaussian correlation approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2089-2109, April.
    121. Arias, Guillaume & Erlandsson, Ulf, 2004. "Regime switching as an alternative early warning system of currency crises - an application to South-East Asia," Working Papers 2004:11, Lund University, Department of Economics.
    122. Li, Chenxing & Maheu, John M & Yang, Qiao, 2022. "An Infinite Hidden Markov Model with Stochastic Volatility," MPRA Paper 115456, University Library of Munich, Germany.
    123. David Hallac & Peter Nystrup & Stephen Boyd, 2019. "Greedy Gaussian segmentation of multivariate time series," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(3), pages 727-751, September.
    124. Yizhan Shu & Chenyu Yu & John M. Mulvey, 2024. "Downside Risk Reduction Using Regime-Switching Signals: A Statistical Jump Model Approach," Papers 2402.05272, arXiv.org, revised Sep 2024.
    125. Guglielmo Maria Caporale & Luis Gil-Alana, 2004. "Long range dependence in daily stock returns," Applied Financial Economics, Taylor & Francis Journals, vol. 14(6), pages 375-383.
    126. Jan Bulla & Sascha Mergner & Ingo Bulla & André Sesboüé & Christophe Chesneau, 2011. "Markov-switching asset allocation: Do profitable strategies exist?," Journal of Asset Management, Palgrave Macmillan, vol. 12(5), pages 310-321, November.
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  80. Teräsvirta, Timo, 1996. "Modelling Economic Relationships with Smooth Transition Regressions," SSE/EFI Working Paper Series in Economics and Finance 131, Stockholm School of Economics.

    Cited by:

    1. Khémiri, Wafa & Noubbigh, Hédi, 2020. "Size-threshold effect in debt-firm performance nexus in the sub-Saharan region: A Panel Smooth Transition Regression approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 335-344.
    2. Bergeaud, A. & Cette, G. & Lecat, R., 2015. "Productivity trends from 1890 to 2012 in advanced countries," Rue de la Banque, Banque de France, issue 07, June..
    3. Antonin Bergeaud & Gilbert Cette & Rémy Lecat, 2016. "Productivity Trends in Advanced Countries between 1890 and 2012," Post-Print hal-01440309, HAL.
    4. Nabil Alimi & Nabil Aflouk, 2017. "Terms-of-trade shocks and macroeconomic volatility in developing countries: panel smooth transition regression models," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 26(5), pages 534-551, July.
    5. Mohamed CHIKHI & Ali BENDOB & Ahmed Ramzi SIAGH, 2019. "Day-of-the-week and month-of-the-year effects on French Small-Cap Volatility: the role of asymmetry and long memory," Eastern Journal of European Studies, Centre for European Studies, Alexandru Ioan Cuza University, vol. 10, pages 221-248, December.
    6. Petri Maki-Franti, 2008. "Money and stock returns: is there habit formation for holding liquid assets?," International Economic Journal, Taylor & Francis Journals, vol. 22(1), pages 63-80.
    7. Pan, Xiuzhen & Wei, Zixiang & Han, Botang & Shahbaz, Muhammad, 2021. "The heterogeneous impacts of interregional green technology spillover on energy intensity in China," Energy Economics, Elsevier, vol. 96(C).

  81. Teräsvirta, Timo, 1996. "Power Properties of Linearity Tests for Time Series," SSE/EFI Working Paper Series in Economics and Finance 94, Stockholm School of Economics.

    Cited by:

    1. Castle, Jennifer L. & Hendry, David F., 2010. "A low-dimension portmanteau test for non-linearity," Journal of Econometrics, Elsevier, vol. 158(2), pages 231-245, October.
    2. Lee Tae-Hwy & Xi Zhou & Zhang Ru, 2013. "Testing for Neglected Nonlinearity Using Artificial Neural Networks with Many Randomized Hidden Unit Activations," Journal of Time Series Econometrics, De Gruyter, vol. 5(1), pages 61-68, January.
    3. Q.Farooq Akram & Øyvind Eitrheim & Lucio Sarno, 2006. "Non-linear Dynamics in Output, Real Exchange Rates and Real Money Balances: Norway, 1830-2003," Contributions to Economic Analysis, in: Nonlinear Time Series Analysis of Business Cycles, pages 333-377, Emerald Group Publishing Limited.
    4. Berg, Nathan, 2004. "No-decision classification: an alternative to testing for statistical significance," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 33(5), pages 631-650, November.

  82. Kauppi, Eija & Lassila, Jukka & Teräsvirta, Timo, 1996. "Short-Term Forecasting of Industrial Production with Business Survey Data: Experience from Finland's Great Depression," Discussion Papers 546, The Research Institute of the Finnish Economy.

    Cited by:

    1. Dr Silvia Lui & Dr Martin Weale & Dr. James Mitchell, 2009. "The utility of expectational data: Firm-level evidence using matched qualitative-quantitative UK surveys," National Institute of Economic and Social Research (NIESR) Discussion Papers 343, National Institute of Economic and Social Research.
    2. Juan G Brida & Bibiana Lanzilotta & Lucia I Rosich, 2021. "On the empirical relations between producers expectations and economic growth," Economics Bulletin, AccessEcon, vol. 41(3), pages 1970-1982.
    3. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," IREA Working Papers 201801, University of Barcelona, Research Institute of Applied Economics, revised Jan 2018.
    4. Boriss Siliverstovs, 2013. "Do business tendency surveys help in forecasting employment?: A real-time evidence for Switzerland," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 129-151.
    5. Mansoor Maitah & Daniel Toth & Elena Kuzmenko & Karel r dl & Helena Rezbov & Petra nov, 2016. "Forecast of Employment in Switzerland: The Macroeconomic View," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 132-138.
    6. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.
    7. Claveria, Oscar & Pons, Ernest & Ramos, Raul, 2007. "Business and consumer expectations and macroeconomic forecasts," International Journal of Forecasting, Elsevier, vol. 23(1), pages 47-69.
    8. Bengoechea, Pilar & Camacho, Maximo & Perez-Quiros, Gabriel, 2006. "A useful tool for forecasting the Euro-area business cycle phases," International Journal of Forecasting, Elsevier, vol. 22(4), pages 735-749.
    9. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Evolutionary Computation for Macroeconomic Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 833-849, February.
    10. Guizzardi, Andrea & Stacchini, Annalisa, 2015. "Real-time forecasting regional tourism with business sentiment surveys," Tourism Management, Elsevier, vol. 47(C), pages 213-223.
    11. Boriss Siliverstovs, 2010. "Assessing Predictive Content of the KOF Barometer in Real Time," KOF Working papers 10-249, KOF Swiss Economic Institute, ETH Zurich.
    12. Miquel Clar & Juan-Carlos Duque & Rosina Moreno, 2007. "Forecasting business and consumer surveys indicators-a time-series models competition," Applied Economics, Taylor & Francis Journals, vol. 39(20), pages 2565-2580.

  83. Teräsvirta, Timo, 1996. "Smooth Transition Models," SSE/EFI Working Paper Series in Economics and Finance 132, Stockholm School of Economics.

    Cited by:

    1. Stefan Reitz & Frank Westerhoff, 2007. "Commodity price cycles and heterogeneous speculators: a STAR–GARCH model," Empirical Economics, Springer, vol. 33(2), pages 231-244, September.
    2. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
    3. Virginie Coudert & Valérie Mignon, 2016. "Reassessing the empirical relationship between the oil price and the dollar," EconomiX Working Papers 2016-2, University of Paris Nanterre, EconomiX.
    4. Aslanidis, Nektarios & Christiansen, Charlotte, 2012. "Smooth transition patterns in the realized stock–bond correlation," Journal of Empirical Finance, Elsevier, vol. 19(4), pages 454-464.
    5. Boldea, Otilia & Hall, Alastair R., 2013. "Estimation and inference in unstable nonlinear least squares models," Journal of Econometrics, Elsevier, vol. 172(1), pages 158-167.
    6. Reitz, Stefan & Ruelke, Jan C. & Taylor, Mark P., 2010. "On the nonlinear influence of Reserve Bank of Australia interventions on exchange rates," Discussion Paper Series 1: Economic Studies 2010,08, Deutsche Bundesbank.
    7. Virginie Coudert & Valérie Mignon, 2013. "The ‘Forward Premium Puzzle’ and the Sovereign Default risk," Post-Print hal-01385839, HAL.
    8. Virginie Coudert & Cécile Couharde & Valérie Mignon, 2013. "Pegging emerging currencies in the face of dollar swings," Post-Print hal-01411740, HAL.
    9. Clemens Kool & Alex Lammertsma, 2005. "Inflation Persistence under Semi-Fixed Exchange Rate Regimes: The European Evidence 1974–1998," Open Economies Review, Springer, vol. 16(1), pages 51-76, January.
    10. Reitz, Stefan & Rülke, Jan-Christoph & Stadtmann, Georg, 2012. "Nonlinear expectations in speculative markets: Evidence from the ECB survey of professional forecasters," Discussion Papers 311, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    11. Cristina Amado & Timo Teräsvirta, 2011. "Modelling Volatility by Variance Decomposition," NIPE Working Papers 01/2011, NIPE - Universidade do Minho.
    12. Nidhaleddine Ben Cheikh & Sami Ben Naceur & Oussama Kanaan & Christophe Rault, 2018. "Oil Prices and GCC Stock Markets: New Evidence from Smooth Transition Models," CESifo Working Paper Series 7072, CESifo.
    13. Sandy Suardi & O.T.Henry & N. Olekalns, "undated". "Testing for Rate-Dependence and Asymmetry in Inflation Uncertainty: Evidence from the G7 Economies," MRG Discussion Paper Series 0306, School of Economics, University of Queensland, Australia.
    14. Menzie Chinn & Laurent Ferrara & Valérie Mignon, 2013. "Post-Recession US Employment through the Lens of a Non-Linear Okun's Law," Working Papers 2013-13, CEPII research center.
    15. Yuri S. Popkov & Alexey Yu. Popkov & Yuri A. Dubnov & Dimitri Solomatine, 2020. "Entropy-Randomized Forecasting of Stochastic Dynamic Regression Models," Mathematics, MDPI, vol. 8(7), pages 1-20, July.
    16. Vinícius Dos Santos Cerqueira & Márcio Bruno Ribeiro & Thiago Sevilhano Martinez, 2014. "Propagaçãoassimétrica De Choques Monetários Na Economia Brasileira: Evidênciascom Base Em Um Modelo Vetorial Não-Linear De Transição Suave," Anais do XL Encontro Nacional de Economia [Proceedings of the 40th Brazilian Economics Meeting] 032, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    17. Christopher Martin & Costas Milas, 2007. "Testing the Opportunistic Approach to Monetary Policy," Keele Economics Research Papers KERP 2007/02, Centre for Economic Research, Keele University.
    18. Jieye Qin & Christopher J. Green & Kavita Sirichand, 2019. "Determinants of Nikkei futures mispricing in international markets: Dividend clustering, currency risk, and transaction costs," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 39(10), pages 1269-1300, October.
    19. Maringer Dietmar G. & Meyer Mark, 2008. "Smooth Transition Autoregressive Models -- New Approaches to the Model Selection Problem," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(1), pages 1-21, March.
    20. Nachatchapong Kaewsompong & Songsak Sriboonchitta & Prasert Chaitip & Pathairat Pastpipatkul, 2012. "Econometric modeling of the relationship among macroeconomic variables of Thailand: Smooth transition autoregressive regression model," The Empirical Econometrics and Quantitative Economics Letters, Faculty of Economics, Chiang Mai University, vol. 1(4), pages 21-38, December.
    21. Mehmet Balcilar & Rangan Gupta & Stephen M. Miller, 2012. "The Out-of-Sample Forecasting Performance of Non-Linear Models of Regional Housing Prices in the US," Working papers 2012-12, University of Connecticut, Department of Economics.
    22. Bahar Araz-Takay & K. Peren Arin & Tolga Omay, 2009. "The Endogenous And Non-Linear Relationship Between Terrorism And Economic Performance: Turkish Evidence," Defence and Peace Economics, Taylor & Francis Journals, vol. 20(1), pages 1-10.
    23. Jean-Pierre Allegret & Hélène Raymond & Houda Rharrabti, 2017. "The impact of the European sovereign debt crisis on banks stocks. Some evidence of shift contagion in Europe," Post-Print hal-01589269, HAL.
    24. Jean-Pierre Allegret & Hélène Raymond & Houda Rharrabti, 2014. "The impact of the global and eurozone crises on European banks stocks Some evidence of shift contagion," Working Papers hal-04141339, HAL.
    25. Vincent Bouvatier & Antonia Lopez Villavicencio & Valérie Mignon, 2014. "Short-run dynamics in bank credit: Assessing nonlinearities in cyclicality," Post-Print hal-01385908, HAL.
    26. Baaziz, Yosra & Labidi, Moez & Lahiani, Amine, 2013. "Does the South African Reserve Bank follow a nonlinear interest rate reaction function?," Economic Modelling, Elsevier, vol. 35(C), pages 272-282.
    27. Gunnar Bårdsen & Stan Hurn & Zoë McHugh, 2010. "Asymmetric unemployment rate dynamics in Australia," CREATES Research Papers 2010-02, Department of Economics and Business Economics, Aarhus University.
    28. Skalin, Joakim & Teräsvirta, Timo, 1996. "Another Look at Swedish Business Cycles, 1861-1988," SSE/EFI Working Paper Series in Economics and Finance 130, Stockholm School of Economics.
    29. Ben Cheikh, Nidhaleddine & Rault, Christophe, 2013. "The Pass-Through of Exchange Rate in the Context of the European Sovereign Debt Crisis," MPRA Paper 59484, University Library of Munich, Germany.
    30. José Cancelo & Estefanía Mourelle, 2005. "Modeling Cyclical Asymmetries in European Imports," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 11(2), pages 135-147, May.
    31. Camarero, Mariam & Ordóñez, Javier, 2012. "Nonlinear adjustment in the real dollar–euro exchange rate: The role of the productivity differential as a fundamental," Economic Modelling, Elsevier, vol. 29(2), pages 444-449.
    32. Skalin, Joakim & Teräsvirta, Timo, 1998. "Modelling asymmetries and moving equilibria in unemployment rates," SSE/EFI Working Paper Series in Economics and Finance 262, Stockholm School of Economics, revised Jul 1999.
    33. Solveig Osborg Ose & Jan Morten Dyrstad, 2001. "Non-linear Unemployment Effects in Sickness Absence: Discipline or Composition Effects?," Working Paper Series 2502, Department of Economics, Norwegian University of Science and Technology.
    34. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
    35. Gabriella Legrenzi & Costas Milas, 2004. "Non-linear real exchange rate effects in the UK labour market," International Finance 0411007, University Library of Munich, Germany.
    36. Menzie Chinn & Laurent Ferrara & Valérie Mignon, 2014. "Explaining US employment growth after the Great Recession: the role of output-employment non-linearities," Post-Print hal-01385949, HAL.
    37. Jorge Perez-Rodriguez & Salvador Torra & Julian Andrada-Felix, 2005. "Are Spanish Ibex35 stock future index returns forecasted with non-linear models?," Applied Financial Economics, Taylor & Francis Journals, vol. 15(14), pages 963-975.
    38. Strikholm, Birgit, 2006. "Determining the number of breaks in a piecewise linear regression model," SSE/EFI Working Paper Series in Economics and Finance 648, Stockholm School of Economics.
    39. van Dijk, Dick & Franses, Philip Hans & Paap, Richard, 2002. "A nonlinear long memory model, with an application to US unemployment," Journal of Econometrics, Elsevier, vol. 110(2), pages 135-165, October.
    40. Laakkonen Helinä & Lanne Markku, 2009. "Asymmetric News Effects on Exchange Rate Volatility: Good vs. Bad News in Good vs. Bad Times," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(1), pages 1-38, December.
    41. Adnen Ben Nasr & Ahdi N. Ajmi & Rangan Gupta, 2013. "Modeling the Volatility of the Dow Jones Islamic Market World Index Using a Fractionally Integrated Time Varying GARCH (FITVGARCH) Model," Working Papers 201357, University of Pretoria, Department of Economics.
    42. Emilio Zanetti Chini, 2013. "Generalizing smooth transition autoregressions," CEIS Research Paper 294, Tor Vergata University, CEIS, revised 25 Sep 2014.
    43. Rothman, P. & van Dijk, D.J.C. & Franses, Ph.H.B.F., 1999. "A multivariate STAR analysis of the relationship between money and output," Econometric Institute Research Papers EI 9945-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    44. Fuzuli Aliyev, 2019. "Testing Market Efficiency with Nonlinear Methods: Evidence from Borsa Istanbul," IJFS, MDPI, vol. 7(2), pages 1-11, June.
    45. Chihwa Kao & Yongmiao Hong, 2004. "Detecting Neglected Nonlinearity in Dynamic Panel Data with Time-Varying Conditional Heteroskedasticity," Econometric Society 2004 Far Eastern Meetings 753, Econometric Society.
    46. Hasanov, Mübariz & Araç, Aysen & Telatar, Funda, 2010. "Nonlinearity and structural stability in the Phillips curve: Evidence from Turkey," Economic Modelling, Elsevier, vol. 27(5), pages 1103-1115, September.
    47. Woodward, George & Brooks, Robert, 2009. "Do realized betas exhibit up/down market tendencies?," International Review of Economics & Finance, Elsevier, vol. 18(3), pages 511-519, June.
    48. Alfred A. Haug & Pierre L. Siklos, 2002. "The Term Spread International Evidence of Non-Linear Adjustment," Working Papers 2002_08, York University, Department of Economics, revised Jul 2004.
    49. Stephen Dobson & John Goddard, 2008. "Strategic behaviour and risk taking in football," NBS Discussion Papers in Economics 2008/7, Economics, Nottingham Business School, Nottingham Trent University.
    50. Nadir Ocal, 2006. "Nonlinear models, composite longer leading indicator and forecasts for UK real GDP," Applied Economics, Taylor & Francis Journals, vol. 38(9), pages 1049-1053.
    51. Goodwin, Barry K. & Holt, Matthew T. & Prestemon, Jeffrey P., 2019. "Nonlinear exchange rate pass-through in timber products: The case of oriented strand board in Canada and the United States," The North American Journal of Economics and Finance, Elsevier, vol. 50(C).
    52. McMillan, David G., 2009. "Forward interest rate premium and asymmetric adjustment: Evidence from 16 countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(2), pages 258-273, April.
    53. Scharth, Marcel & Medeiros, Marcelo C., 2009. "Asymmetric effects and long memory in the volatility of Dow Jones stocks," International Journal of Forecasting, Elsevier, vol. 25(2), pages 304-327.
    54. Dimitris K. Christopoulos & Miguel León-Ledesma, 2004. "Current Account Sustainability in the US: What Do We Really Know About It?," Studies in Economics 0412, School of Economics, University of Kent.
    55. Lucio Sarno & Daniel L. Thornton, 2002. "The dynamic relationship between the federal funds rate and the Treasury bill rate: an empirical investigation," Working Papers 2000-032, Federal Reserve Bank of St. Louis.
    56. Carlo Altavilla & Luigi Landolfo, 2005. "Do central banks act asymmetrically? Empirical evidence from the ECB and the Bank of England," Applied Economics, Taylor & Francis Journals, vol. 37(5), pages 507-519.
    57. Virginie Coudert & Cécile Couharde & Valérie Mignon, 2010. "Exchange Rate Flexibility Across Financial Crises," Working Papers 2010-08, CEPII research center.
    58. Mehmet Balcilar & Rangan Gupta & Zahra Shah, 2010. "An In-Sample and Out-of-Sample Empirical Investigation of the Nonlinearity in House Prices of South Africa," Working Papers 201008, University of Pretoria, Department of Economics.
    59. Lof, Matthijs, 2010. "Heterogeneity in Stock Pricing: A STAR Model with Multivariate Transition Functions," MPRA Paper 30520, University Library of Munich, Germany.
    60. Liew Khim Sen & Ahmad Zubaidi Baharumshah, 2003. "How Well the Ringgit-Yen Rate Fits the Non-linear Smooth Transition Autoregressive and Linear Autoregressive Models," GE, Growth, Math methods 0307004, University Library of Munich, Germany.
    61. Luis Eduardo Arango & Andrés González, 1999. "A Nonlinear Specification Of Demand For Narrow Money In Colombia," Borradores de Economia 1894, Banco de la Republica.
    62. Zanetti Chini, Emilio, 2010. "Does the purchasing power parity hypothesis hold after 1998?," MPRA Paper 27225, University Library of Munich, Germany.
    63. Milena Hoyos & Mario Galindo, 2011. "Comparación de los modelos SETAR y STAR para el índice de empleo industrial colombiano," Documentos de Trabajo, Escuela de Economía 8347, Universidad Nacional de Colombia, FCE, CID.
    64. Omay, Tolga & Iren, Perihan, 2019. "Behavior of foreign investors in the Malaysian stock market in times of crisis: A nonlinear approach," Journal of Asian Economics, Elsevier, vol. 60(C), pages 85-100.
    65. Locke, Peter & Onayev, Zhan, 2007. "Order flow, dealer profitability, and price formation," Journal of Financial Economics, Elsevier, vol. 85(3), pages 857-887, September.
    66. González, Andrés & Teräsvirta, Timo, 2006. "Modelling autoregressive processes with a shifting mean," SSE/EFI Working Paper Series in Economics and Finance 637, Stockholm School of Economics, revised 22 May 2007.
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    1. Christian Dreger & Jürgen Wolters, 2010. "M3 money demand and excess liquidity in the euro area," Public Choice, Springer, vol. 144(3), pages 459-472, September.
    2. Ivo Arnold, 2003. "A Regional Analysis of German Money Demand Around Reunification with Implications for EMU," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 30(1), pages 63-80, March.
    3. Carstensen Kai & Hansen Gerd, 2004. "Inflationäre Schocks in Deutschland: Eine Common Trends Analyse / Inflationary Shocks in Germany: A Common Trends Analysis," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 224(3), pages 271-291, June.
    4. Carstensen, Kai, 2004. "Is European Money Demand Still Stable?," Kiel Working Papers 1179, Kiel Institute for the World Economy (IfW Kiel).
    5. Lütkepohl, Helmut & Wolters, Jürgen, 2001. "The transmission of German monetary policy in the pre-Euro period," SFB 373 Discussion Papers 2001,87, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    6. Frank Browne & Gabriel Fagan & Jerome Henry, 2005. "Money Demand in EU Countries: A Survey," Macroeconomics 0503004, University Library of Munich, Germany.
    7. Svensson, Lars E. O., 1999. "Monetary policy issues for the Eurosystem," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 51(1), pages 79-136, December.
    8. Abbas Valadkhani, 2005. "Modelling Demand For Broad Money In Australia," Australian Economic Papers, Wiley Blackwell, vol. 44(1), pages 47-64, March.
    9. Volker W. Wieland, 1999. "Monetary policy, parameter uncertainty and optimal learning," Finance and Economics Discussion Series 1999-48, Board of Governors of the Federal Reserve System (U.S.).
    10. Mawuli Segnon & Rangan Gupta & Stelios Bekiros & Mark E. Wohar, 2018. "Forecasting US GNP growth: The role of uncertainty," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(5), pages 541-559, August.
    11. Nautz, Dieter & Rondorf, Ulrike, 2010. "The (in)stability of money demand in the Euro area," Discussion Papers 2010/17, Free University Berlin, School of Business & Economics.
    12. Heimonen, Kari, 2008. "Substituting a substitute currency," International Review of Economics & Finance, Elsevier, vol. 17(1), pages 66-84.
    13. Dreger, Christian & Wolters, Jürgen, 2011. "Money and inflation in the euro area during the financial crisis," Discussion Papers 300, European University Viadrina Frankfurt (Oder), Department of Business Administration and Economics.
    14. Philip Arestis & Malcolm Sawyer, 2001. "Will the Euro Bring Economic Crisis to Europe?," Palgrave Macmillan Books, in: Philip Arestis & Michelle Baddeley & John McCombie (ed.), What Global Economic Crisis?, chapter 5, pages 78-103, Palgrave Macmillan.
    15. Brüggemann, Imke & Nautz, Dieter, 1997. "Money growth volatility and the demand for money in Germany: Friedman's volatility hypothesis revisited," SFB 373 Discussion Papers 1997,23, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    16. Kai Carstensen & Jan Hagen & Oliver Hossfeld & Abelardo Salazar Neaves, 2008. "Money Demand Stability and Inflation Prediction in the Four Largest EMU Countries," ifo Working Paper Series 61, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    17. El-Shagi, Makram & Giesen, Sebastian, 2013. "Money and inflation: Consequences of the recent monetary policy," Journal of Policy Modeling, Elsevier, vol. 35(4), pages 520-537.
    18. Arize, Augustine C. & Malindretos, John & Ghosh, Dilip, 2015. "Purchasing power parity-symmetry and proportionality: Evidence from 116 countries," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 69-85.
    19. Arize, A. C. & Malindretos, John & Grivoyannis, Elias C., 2005. "Inflation-rate volatility and money demand: Evidence from less developed countries," International Review of Economics & Finance, Elsevier, vol. 14(1), pages 57-80.
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    21. Mariá Dolores Gadea & José Mariá Serrano-Sanz, 2002. "The hidden economy in Spain - A monetary estimation, 1964-1998," Empirical Economics, Springer, vol. 27(3), pages 499-527.
    22. Koen Pauwels & Shuba Srinivasan, 2004. "Who Benefits from Store Brand Entry?," Marketing Science, INFORMS, vol. 23(3), pages 364-390, July.
    23. Christian Dreger & Jürgen Wolters, 2008. "Money Velocity and Asset Prices in the Euro Area," Working Paper / FINESS 7.1b, DIW Berlin, German Institute for Economic Research.
    24. Holtemöller Oliver, 2003. "Money Stock, Monetary Base and Bank Behavior in Germany / Geldmenge, Geldbasis und Bankenverhalten in Deutschland," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 223(3), pages 257-278, June.
    25. Lee, Chien-Chiang & Chen, Pei-Fen & Chang, Chun-Ping, 2007. "Testing linearity in a cointegrating STR model for the money demand function: International evidence from G-7 countries," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 76(4), pages 293-302.
    26. Dreger, Christian & Wolters, Jürgen, 2010. "Investigating M3 money demand in the euro area," Journal of International Money and Finance, Elsevier, vol. 29(1), pages 111-122, February.
    27. Julian Ramajo & Miguel A. Marquez, 1998. "Structural change in regional economies: A varying coefficients econometric modeling approach," ERSA conference papers ersa98p189, European Regional Science Association.
    28. Ante Babić, 2000. "The Monthly Transaction Money Demand in Croatia," Working Papers 5, The Croatian National Bank, Croatia.
    29. Kirstin Hubrich & Peter J. G. Vlaar, 2000. "Germany and the Euro Area: Differences in the Transmission Process of Monetary Policy," Econometric Society World Congress 2000 Contributed Papers 1802, Econometric Society, revised 08 Nov 2000.
    30. Stéphane Guéné, 2001. "Agrégats et politique monétaires dans la zone euro," Economie & Prévision, La Documentation Française, vol. 147(1), pages 187-201.
    31. Caner, M. & Kilian, L., 2001. "Size distortions of tests of the null hypothesis of stationarity: evidence and implications for the PPP debate," Journal of International Money and Finance, Elsevier, vol. 20(5), pages 639-657, October.
    32. Oliver Hossfeld, 2010. "US Money Demand, Monetary Overhang, and Inflation," Working Papers 2010.4, International Network for Economic Research - INFER.
    33. Imke Brüggemann, 2003. "Measuring Monetary Policy in Germany: A Structural Vector Error Correction Approach," German Economic Review, Verein für Socialpolitik, vol. 4(3), pages 307-339, August.
    34. Gerberding, Christina & Seitz, Franz & Worms, Andreas, 2007. "Money-based interest rate rules: lessons from German data," Discussion Paper Series 1: Economic Studies 2007,06, Deutsche Bundesbank.
    35. Henry, Olan T. & Shields, Kalvinder, 2004. "Is there a unit root in inflation?," Journal of Macroeconomics, Elsevier, vol. 26(3), pages 481-500, September.
    36. Avouyi-Dovi, S. & Diop, A. & Fonteny, E-C. & Gervais, E. & Jacquinot, P. & Mésonnier, J-S. & Sahuc, J-G., 2003. "Estimation d’une fonction de demande de monnaie pour la zone euro : une synthèse des résultats," Bulletin de la Banque de France, Banque de France, issue 111, pages 47-72.
    37. El-Shagi, Makram & Giesen, Sebastian, 2010. "Money and Inflation: The Role of Persistent Velocity Movements," IWH Discussion Papers 2/2010, Halle Institute for Economic Research (IWH).
    38. Christian Dreger & Jürgen Wolters, 2006. "Investigating M3 Money Demand in the Euro Area: New Evidence Based on Standard Models," Discussion Papers of DIW Berlin 561, DIW Berlin, German Institute for Economic Research.

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    Cited by:

    1. Christian Dreger & Jürgen Wolters, 2010. "M3 money demand and excess liquidity in the euro area," Public Choice, Springer, vol. 144(3), pages 459-472, September.
    2. Luis E. Arango & Andrés González, 2000. "A Nonlinear Specification of Demand for Cash in Colombia," Money Affairs, CEMLA, vol. 0(2), pages 207-226, July-Dece.
    3. Diego Winkelried Quezada, 2003. "Indicadores adelantados de la inflación en el Perú," Monetaria, CEMLA, vol. 0(4), pages 345-382, octubre-d.
    4. Omar A Mendoza Lugo, 2008. "The differential impact of real interest rates and credit availability on private investment: evidence from Venezuela," BIS Papers chapters, in: Bank for International Settlements (ed.), Transmission mechanisms for monetary policy in emerging market economies, volume 35, pages 501-537, Bank for International Settlements.
    5. Héctor A. Valle S., 2003. "Pronósticos de inflación para Guatemala hechos con modelos ARIMA y VAR," Monetaria, CEMLA, vol. 0(4), pages 407-428, octubre-d.
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    1. Gebrenegus Ghilagaber, 2004. "Another Look at Chow's Test for the Equality of Two Heteroscedastic Regression Models," Quality & Quantity: International Journal of Methodology, Springer, vol. 38(1), pages 81-93, February.
    2. Karmakar, Sayar & Richter, Stefan & Wu, Wei Biao, 2022. "Simultaneous inference for time-varying models," Journal of Econometrics, Elsevier, vol. 227(2), pages 408-428.
    3. Mikihito Nishi, 2023. "Testing for Stationary or Persistent Coefficient Randomness in Predictive Regressions," Papers 2309.04926, arXiv.org, revised May 2024.
    4. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    5. Banerjee, Anindya & Urga, Giovanni, 2005. "Modelling structural breaks, long memory and stock market volatility: an overview," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 1-34.

  88. Jansen, Eilev S. & Teräsvirta, Timo, 1995. "Testing Parameter Constancy and super Exogeneity in Econometric Equations," SSE/EFI Working Paper Series in Economics and Finance 53, Stockholm School of Economics.

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    1. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
    2. Andres Gonzalez & Timo Terasvirta & Dick van Dijk, 2005. "Panel Smooth Transition Regression Models," Research Paper Series 165, Quantitative Finance Research Centre, University of Technology, Sydney.
    3. van Dijk, D.J.C. & Franses, Ph.H.B.F., 1997. "Nonlinear Error-Correction Models for Interest Rates in The Netherlands," Econometric Institute Research Papers EI 9704-/A, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Gilbert Colletaz & Christophe Hurlin, 2006. "Threshold Effects of the Public Capital Productivity : An International Panel Smooth Transition Approach," Working Papers halshs-00008056, HAL.
    5. Hamdi, Helmi & Hakimi, Abdelaziz, 2019. "Does Liquidity Matter on Bank Profitability? Evidence from a Nonlinear Framework for a Large Sample," Business and Economics Research Journal, Uludag University, Faculty of Economics and Administrative Sciences, vol. 10(1), pages 13-26, January.
    6. Luis E. Arango & Andrés González, 2000. "A Nonlinear Specification of Demand for Cash in Colombia," Money Affairs, CEMLA, vol. 0(2), pages 207-226, July-Dece.
    7. Virginie Coudert & Cécile Couharde & Valérie Mignon, 2013. "Pegging emerging currencies in the face of dollar swings," Post-Print hal-01411740, HAL.
    8. Chi-Hui Wang & Prasad Padmanabhan & Chia-Hsing Huang, 2021. "The Impact of Renewable Energy, Urbanization, and Environmental Sustainability Ratings on the Environmental Kuznets Curve and the Pollution Haven Hypothesis," Sustainability, MDPI, vol. 13(24), pages 1-22, December.
    9. Ghulame Rubbaniy & Ali Awais Khalid & Shoaib Ali & Efstathios Polyzos, 2023. "Cyclicality of liquidity creation: Nonlinear evidence from US bank holding companies," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 46(4), pages 1165-1185, December.
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    14. He, Changli & Kang, Jian & Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Long monthly temperature series and the Vector Seasonal Shifting Mean and Covariance Autoregressive model," Journal of Econometrics, Elsevier, vol. 239(1).
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  89. Luukkonen, Ritva & Teräsvirta, Timo, 1988. "Testing Linearity of Economic Time Series against Cyclical A symmetry," Discussion Papers 262, The Research Institute of the Finnish Economy.

    Cited by:

    1. David Kiefer, 1996. "Searching For Endogenous Business Cycles In The U.S. Postwar Economy," Metroeconomica, Wiley Blackwell, vol. 47(1), pages 34-56, February.

  90. TERÄSVIRTA, Timo, 1981. "Some results on improving the least squares estimation of linear models by mixed estimation," LIDAM Reprints CORE 434, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Sivarajah Arumairajan & Pushpakanthie Wijekoon, 2017. "The generalized preliminary test estimator when different sets of stochastic restrictions are available," Statistical Papers, Springer, vol. 58(3), pages 729-747, September.

Articles

  1. He, Changli & Kang, Jian & Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Long monthly temperature series and the Vector Seasonal Shifting Mean and Covariance Autoregressive model," Journal of Econometrics, Elsevier, vol. 239(1).
    See citations under working paper version above.
  2. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    See citations under working paper version above.
  3. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2023. "Building Multivariate Time-Varying Smooth Transition Correlation GARCH Models, with an Application to the Four Largest Australian Banks," Econometrics, MDPI, vol. 11(1), pages 1-37, February.

    Cited by:

    1. He, Changli & Kang, Jian & Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Long monthly temperature series and the Vector Seasonal Shifting Mean and Covariance Autoregressive model," Journal of Econometrics, Elsevier, vol. 239(1).

  4. Jian Kang & Johan Stax Jakobsen & Annastiina Silvennoinen & Timo Teräsvirta & Glen Wade, 2022. "A Parsimonious Test of Constancy of a Positive Definite Correlation Matrix in a Multivariate Time-Varying GARCH Model," Econometrics, MDPI, vol. 10(3), pages 1-41, August.
    See citations under working paper version above.
  5. Hurn Stan & Johnson Nicholas & Silvennoinen Annastiina & Teräsvirta Timo, 2022. "Transition from the Taylor rule to the zero lower bound," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 26(5), pages 635-647, December.
    See citations under working paper version above.
  6. Dakyung Seong & Jin Seo Cho & Timo Teräsvirta, 2022. "Comprehensively testing linearity hypothesis using the smooth transition autoregressive model," Econometric Reviews, Taylor & Francis Journals, vol. 41(8), pages 966-984, September.

    Cited by:

    1. Andrea Bucci, 2024. "A sequential test procedure for the choice of the number of regimes in multivariate nonlinear models," Papers 2406.02152, arXiv.org.
    2. Jin Seo Cho, 2024. "Estimating and Inferring the Nonlinear Autoregressive Distributed Lag Model by Ordinary Least Squares," Working papers 2024rwp-227, Yonsei University, Yonsei Economics Research Institute.

  7. He, Changli & Kang, Jian & Teräsvirta, Timo & Zhang, Shuhua, 2021. "Comparing long monthly Chinese and selected European temperature series using the Vector Seasonal Shifting Mean and Covariance Autoregressive model," Energy Economics, Elsevier, vol. 97(C).
    See citations under working paper version above.
  8. Holt, Matthew T. & Teräsvirta, Timo, 2020. "Global hemispheric temperatures and co-shifting: A vector shifting-mean autoregressive analysis," Journal of Econometrics, Elsevier, vol. 214(1), pages 198-215.
    See citations under working paper version above.
  9. He, Changli & Kang, Jian & Teräsvirta, Timo & Zhang, Shuhua, 2019. "The shifting seasonal mean autoregressive model and seasonality in the Central England monthly temperature series, 1772–2016," Econometrics and Statistics, Elsevier, vol. 12(C), pages 1-24.
    See citations under working paper version above.
  10. Paul Catani & Timo Teräsvirta & Meiqun Yin, 2017. "A Lagrange multiplier test for testing the adequacy of constant conditional correlation GARCH model," Econometric Reviews, Taylor & Francis Journals, vol. 36(6-9), pages 599-621, October.
    See citations under working paper version above.
  11. Cristina Amado & Annastiina Silvennoinen & Timo Terasvirta, 2017. "Modelling and Forecasting WIG20 Daily Returns," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 9(3), pages 173-200, September.
    See citations under working paper version above.
  12. Cristina Amado & Timo Teräsvirta, 2017. "Specification and testing of multiplicative time-varying GARCH models with applications," Econometric Reviews, Taylor & Francis Journals, vol. 36(4), pages 421-446, April.

    Cited by:

    1. Arthur J. Lin & Hai-Yen Chang, 2020. "Volatility Transmission from Equity, Bulk Shipping, and Commodity Markets to Oil ETF and Energy Fund—A GARCH-MIDAS Model," Mathematics, MDPI, vol. 8(9), pages 1-21, September.
    2. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    3. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2018. "Models with Multiplicative Decomposition of Conditional Variances and Correlations," CREATES Research Papers 2018-14, Department of Economics and Business Economics, Aarhus University.
    4. Conrad, Christian & Schienle, Melanie, 2019. "Testing for an omitted multiplicative long-term component in GARCH models," Working Paper Series in Economics 121, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    5. Martínez-García Enrique, 2018. "Modeling time-variation over the business cycle (1960–2017): an international perspective," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-25, December.
    6. Mazur Błażej & Pipień Mateusz, 2018. "Time-varying asymmetry and tail thickness in long series of daily financial returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-21, December.
    7. Chuffart Thomas & Flachaire Emmanuel & Péguin-Feissolle Anne, 2018. "Testing for misspecification in the short-run component of GARCH-type models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-17, December.
    8. Susana Martins & Cristina Amado, 2018. "Financial Market Contagion and the Sovereign Debt Crisis: A Smooth Transition Approach," NIPE Working Papers 08/2018, NIPE - Universidade do Minho.
    9. Conrad, Christian & Schienle, Melanie, 2015. "Misspecification Testing in GARCH-MIDAS Models," VfS Annual Conference 2015 (Muenster): Economic Development - Theory and Policy 112919, Verein für Socialpolitik / German Economic Association.
    10. Christian Francq & Baye Matar Kandji & Jean-Michel Zakoian, 2022. "Inference on Multiplicative Component GARCH without any Small-Order Moment," Working Papers 2022-09, Center for Research in Economics and Statistics.
    11. Bertelsen, Kristoffer Pons & Borup, Daniel & Jakobsen, Johan Stax, 2021. "Stock market volatility and public information flow: A non-linear perspective," Economics Letters, Elsevier, vol. 204(C).
    12. Christian Conrad & Robert F. Engle, 2021. "Modelling Volatility Cycles: The (MF)2 GARCH Model," Working Paper series 21-05, Rimini Centre for Economic Analysis.
    13. Hossein Asgharian & Charlotte Christiansen & Ai Jun Hou & Weining Wang, 2017. "Long- and Short-Run Components of Factor Betas: Implications for Equity Pricing," CREATES Research Papers 2017-34, Department of Economics and Business Economics, Aarhus University.
    14. Fabrizio Cipollini & Giampiero M. Gallo, 2021. "Multiplicative Error Models: 20 years on," Papers 2107.05923, arXiv.org.
    15. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2023. "Building Multivariate Time-Varying Smooth Transition Correlation GARCH Models, with an Application to the Four Largest Australian Banks," Econometrics, MDPI, vol. 11(1), pages 1-37, February.
    16. Cristina Amado & Annastiina Silvennoinen & Timo Teräsvirta, 2017. "Modelling and forecasting WIG20 daily returns," CREATES Research Papers 2017-29, Department of Economics and Business Economics, Aarhus University.
    17. Wu, Xinyu & Xie, Haibin, 2021. "A realized EGARCH-MIDAS model with higher moments," Finance Research Letters, Elsevier, vol. 38(C).
    18. Armin Pourkhanali & Jonathan Keith & Xibin Zhang, 2021. "Conditional Heteroscedasticity Models with Time-Varying Parameters: Estimation and Asymptotics," Monash Econometrics and Business Statistics Working Papers 15/21, Monash University, Department of Econometrics and Business Statistics.
    19. Anthony D. Hall & Annastiina Silvennoinen & Timo Teräsvirta, 2021. "Four Australian Banks and the Multivariate Time-Varying Smooth Transition Correlation GARCH model," CREATES Research Papers 2021-13, Department of Economics and Business Economics, Aarhus University.
    20. Jian Kang & Johan Stax Jakobsen & Annastiina Silvennoinen & Timo Teräsvirta & Glen Wade, 2022. "A parsimonious test of constancy of a positive definite correlation matrix in a multivariate time-varying GARCH model," CREATES Research Papers 2022-01, Department of Economics and Business Economics, Aarhus University.
    21. Conrad, Christian & Schienle, Melanie, 2015. "Misspecification Testing in GARCH-MIDAS Models," Working Papers 0597, University of Heidelberg, Department of Economics.
    22. Christian Conrad & Onno Kleen, 2020. "Two are better than one: Volatility forecasting using multiplicative component GARCH‐MIDAS models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 35(1), pages 19-45, January.
    23. Campos-Martins, Susana & Amado, Cristina, 2022. "Financial market linkages and the sovereign debt crisis," Journal of International Money and Finance, Elsevier, vol. 123(C).

  13. Silvennoinen Annastiina & Teräsvirta Timo, 2016. "Testing constancy of unconditional variance in volatility models by misspecification and specification tests," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 347-364, September.
    See citations under working paper version above.
  14. A. Stan Hurn & Annastiina Silvennoinen & Timo Teräsvirta, 2016. "A Smooth Transition Logit Model of The Effects of Deregulation in the Electricity Market," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 31(4), pages 707-733, June.
    See citations under working paper version above.
  15. Anders Bredahl Kock & Timo Teräsvirta, 2016. "Forecasting Macroeconomic Variables Using Neural Network Models and Three Automated Model Selection Techniques," Econometric Reviews, Taylor & Francis Journals, vol. 35(8-10), pages 1753-1779, December.
    See citations under working paper version above.
  16. Annastiina Silvennoinen & Timo Ter�svirta, 2015. "Modeling Conditional Correlations of Asset Returns: A Smooth Transition Approach," Econometric Reviews, Taylor & Francis Journals, vol. 34(1-2), pages 174-197, February.
    See citations under working paper version above.
  17. Cristina Amado & Timo Teräsvirta, 2014. "Conditional Correlation Models of Autoregressive Conditional Heteroscedasticity With Nonstationary GARCH Equations," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 32(1), pages 69-87, January.
    See citations under working paper version above.
  18. Amado, Cristina & Teräsvirta, Timo, 2014. "Modelling changes in the unconditional variance of long stock return series," Journal of Empirical Finance, Elsevier, vol. 25(C), pages 15-35.
    See citations under working paper version above.
  19. Kock, Anders Bredahl & Teräsvirta, Timo, 2014. "Forecasting performances of three automated modelling techniques during the economic crisis 2007–2009," International Journal of Forecasting, Elsevier, vol. 30(3), pages 616-631.
    See citations under working paper version above.
  20. Amado, Cristina & Teräsvirta, Timo, 2013. "Modelling volatility by variance decomposition," Journal of Econometrics, Elsevier, vol. 175(2), pages 142-153.
    See citations under working paper version above.
  21. Anders Bredahl Kock & Timo Teräsvirta, 2013. "Forecasting the Finnish Consumer Price Inflation Using Artificial Neural Network Models and Three Automated Model Selection Techniques," Finnish Economic Papers, Finnish Economic Association, vol. 26(1), pages 13-24, Spring.

    Cited by:

    1. Nyoni, Thabani, 2019. "ARIMA modeling and forecasting of Consumer Price Index (CPI) in Germany," MPRA Paper 92442, University Library of Munich, Germany.
    2. Nyoni, Thabani, 2019. "Forecasting consumer price index in Norway: An application of Box-Jenkins ARIMA models," MPRA Paper 92411, University Library of Munich, Germany.
    3. Nyoni, Thabani, 2019. "Predicting inflation in the Kingdom of Bahrain using ARIMA models," MPRA Paper 92452, University Library of Munich, Germany.
    4. Nyoni, Thabani, 2019. "Modeling and forecasting inflation in Philippines using ARIMA models," MPRA Paper 92429, University Library of Munich, Germany.
    5. Nyoni, Thabani, 2019. "Predicting CPI in Singapore: An application of the Box-Jenkins methodology," MPRA Paper 92413, University Library of Munich, Germany.
    6. Nyoni, Thabani, 2019. "Time series modeling and forecasting of the consumer price index in Japan," MPRA Paper 92409, University Library of Munich, Germany.
    7. Tamerlan Mashadihasanli, 2022. "Stock Market Price Forecasting Using the Arima Model: an Application to Istanbul, Turkiye," Journal of Economic Policy Researches, Istanbul University, Faculty of Economics, vol. 9(2), pages 439-454, July.
    8. Nyoni, Thabani, 2019. "Forecasting Australian CPI using ARIMA models," MPRA Paper 92412, University Library of Munich, Germany.
    9. Nyoni, Thabani, 2019. "Understanding inflation trends in Israel: A univariate approach," MPRA Paper 92427, University Library of Munich, Germany.
    10. Szafranek, Karol, 2019. "Bagged neural networks for forecasting Polish (low) inflation," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1042-1059.
    11. Denis Shibitov & Mariam Mamedli, 2021. "Forecasting Russian Cpi With Data Vintages And Machine Learning Techniques," Bank of Russia Working Paper Series wps70, Bank of Russia.
    12. Nyoni, Thabani, 2019. "Forecasting UK consumer price index using Box-Jenkins ARIMA models," MPRA Paper 92410, University Library of Munich, Germany.
    13. Nyoni, Thabani, 2019. "Understanding inflation dynamics in the United States of America (USA): A univariate approach," MPRA Paper 92460, University Library of Munich, Germany.
    14. Nyoni, Thabani, 2019. "Modeling and forecasting inflation in Tanzania using ARIMA models," MPRA Paper 92458, University Library of Munich, Germany.
    15. Nyoni, Thabani, 2019. "Understanding inflation trends in Finland: A univariate approach," MPRA Paper 92448, University Library of Munich, Germany.

  22. Timo Terasvirta & Zhenfang Zhao, 2011. "Stylized facts of return series, robust estimates and three popular models of volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 21(1-2), pages 67-94.
    See citations under working paper version above.
  23. Annastiina Silvennoinen & Timo Teräsvirta, 2009. "Modeling Multivariate Autoregressive Conditional Heteroskedasticity with the Double Smooth Transition Conditional Correlation GARCH Model," Journal of Financial Econometrics, Oxford University Press, vol. 7(4), pages 373-411, Fall.
    See citations under working paper version above.
  24. Tomoaki Nakatani & Timo Terasvirta, 2009. "Testing for volatility interactions in the Constant Conditional Correlation GARCH model," Econometrics Journal, Royal Economic Society, vol. 12(1), pages 147-163, March.
    See citations under working paper version above.
  25. Changli He & Timo Terasvirta & Andres Gonzalez, 2009. "Testing Parameter Constancy in Stationary Vector Autoregressive Models Against Continuous Change," Econometric Reviews, Taylor & Francis Journals, vol. 28(1-3), pages 225-245.
    See citations under working paper version above.
  26. González Andrés & Teräsvirta Timo, 2008. "Modelling Autoregressive Processes with a Shifting Mean," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 12(1), pages 1-28, March.
    See citations under working paper version above.
  27. Nakatani, Tomoaki & Teräsvirta, Timo, 2008. "Positivity constraints on the conditional variances in the family of conditional correlation GARCH models," Finance Research Letters, Elsevier, vol. 5(2), pages 88-95, June.
    See citations under working paper version above.
  28. Changli He & Annastiina Silvennoinen & Timo Teräsvirta, 2008. "Parameterizing Unconditional Skewness in Models for Financial Time Series," Journal of Financial Econometrics, Oxford University Press, vol. 6(2), pages 208-230, Spring.
    See citations under working paper version above.
  29. Eklund, Bruno & Terasvirta, Timo, 2007. "Testing constancy of the error covariance matrix in vector models," Journal of Econometrics, Elsevier, vol. 140(2), pages 753-780, October.
    See citations under working paper version above.
  30. Andrés González & Timo Teräsvirta, 2006. "Simulation‐based Finite Sample Linearity Test against Smooth Transition Models," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 68(s1), pages 797-812, December.
    See citations under working paper version above.
  31. Lundbergh, Stefan & Terasvirta, Timo, 2006. "A time series model for an exchange rate in a target zone with applications," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 579-609.
    See citations under working paper version above.
  32. Granger, Clive W.J. & Terasvirta, Timo & Patton, Andrew J., 2006. "Common factors in conditional distributions for bivariate time series," Journal of Econometrics, Elsevier, vol. 132(1), pages 43-57, May.
    See citations under working paper version above.
  33. Birgit Strikholm & Timo Teräsvirta, 2006. "A sequential procedure for determining the number of regimes in a threshold autoregressive model," Econometrics Journal, Royal Economic Society, vol. 9(3), pages 472-491, November.

    Cited by:

    1. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    2. Terasvirta, Timo & Yang, Yukai, 2014. "Linearity and misspecification tests for vector smooth transition regression models," LIDAM Discussion Papers CORE 2014061, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Jens-Peter Loy & Thore Holm & Carsten Steinhagen & Thomas Glauben, 2015. "Cost pass-through in differentiated product markets: a disaggregated study for milk and butter," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 42(3), pages 441-471.
    4. Kirstin Hubrich & Timo Teräsvirta, 2013. "Thresholds and Smooth Transitions in Vector Autoregressive Models," CREATES Research Papers 2013-18, Department of Economics and Business Economics, Aarhus University.
    5. Habib Ur Rahman & Ghulam Ali & Umer Zaman & Carlo Pugnetti, 2021. "Role of ICT Investment and Diffusion in the Economic Growth: A Threshold Approach for the Empirical Evidence from Pakistan," IJFS, MDPI, vol. 9(1), pages 1-14, March.
    6. Loy, Jens-Peter & Glauben, Thomas & Weiss, Christoph, 2015. "Asymmetric Cost Pass-Through? Empirical Evidence on the Role of Market Power, Search and Menu Costs," 2015 Conference, August 9-14, 2015, Milan, Italy 212156, International Association of Agricultural Economists.
    7. Cho, Dooyeon, 2018. "On the persistence of the forward premium in the joint presence of nonlinearity, asymmetry, and structural changes," Economic Modelling, Elsevier, vol. 70(C), pages 310-319.
    8. Loy, Jens-Peter & Holm, Thore & Steinhagen, Carsten, 2012. "Vertical Price Transmission In Differentiated Product Markets: A Disaggregated Study For Milk And Butter," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 123284, Agricultural and Applied Economics Association.
    9. Bucci, Andrea & Sanmarchi, Francesco & Santi, Luca & Golinelli, Davide, 2024. "Evaluating the nonlinear association between PM10 and emergency department visits," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).
    10. Bucci, Andrea & Palomba, Giulio & Rossi, Eduardo, 2023. "The role of uncertainty in forecasting volatility comovements across stock markets," Economic Modelling, Elsevier, vol. 125(C).
    11. Eric Hillebrand & Marcelo C. Medeiros, 2012. "Nonlinearity, Breaks, and Long-Range Dependence in Time-Series Models," CREATES Research Papers 2012-30, Department of Economics and Business Economics, Aarhus University.
    12. Alexander Bick & Dieter Nautz, 2008. "Inflation Thresholds and Relative Price Variability: Evidence from U.S. Cities," International Journal of Central Banking, International Journal of Central Banking, vol. 4(3), pages 61-76, September.
    13. Peter Martey Addo, 2014. "Multivariate Self-Exciting Threshold Autoregressive Models with eXogenous Input," Papers 1407.7738, arXiv.org.
    14. Ellen Hamaker & Zhiyong Zhang & Han Maas, 2009. "Using Threshold Autoregressive Models to Study Dyadic Interactions," Psychometrika, Springer;The Psychometric Society, vol. 74(4), pages 727-745, December.
    15. Holm, Thore & Loy, Jens-Peter & Steinhagen, Carsten, 2012. "Bio Auch Bei Der Preissetzung: Konsummilch In Deutschland," 52nd Annual Conference, Stuttgart, Germany, September 26-28, 2012 137159, German Association of Agricultural Economists (GEWISOLA).
    16. Holm, T. & Loy, J.-P. & Steinhagen, C., 2013. "Bio auch bei der Preissetzung: Konsummilch in Deutschland," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 48, March.
    17. Gulasekaran Rajaguru & Safdar Ullah Khan & Habib-Ur Rahman, 2021. "Analysis of Australia’s Fiscal Vulnerability to Crisis," JRFM, MDPI, vol. 14(7), pages 1-13, June.
    18. Dreger, Christian & Gerdesmeier, Dieter & Roffia, Barbara, 2020. "The impact of credit for house price overvaluations in the euro area: Evidence from threshold models," MPRA Paper 99523, University Library of Munich, Germany.
    19. Wei-han Liu & Zhefang Zhou, 2009. "Inflation-hedging Behavior of a Securitized Real Estate Market," International Real Estate Review, Global Social Science Institute, vol. 12(3), pages 221-251.

  34. Timo Teräsvirta & Marcelo C. Medeiros & Gianluigi Rech, 2006. "Building neural network models for time series: a statistical approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(1), pages 49-75.
    See citations under working paper version above.
  35. Meitz, Mika & Terasvirta, Timo, 2006. "Evaluating Models of Autoregressive Conditional Duration," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 104-124, January.
    See citations under working paper version above.
  36. Terasvirta, Timo & van Dijk, Dick & Medeiros, Marcelo C., 2005. "Linear models, smooth transition autoregressions, and neural networks for forecasting macroeconomic time series: A re-examination," International Journal of Forecasting, Elsevier, vol. 21(4), pages 755-774.
    See citations under working paper version above.
  37. He, Changli & Teräsvirta, Timo, 2004. "An Extended Constant Conditional Correlation Garch Model And Its Fourth-Moment Structure," Econometric Theory, Cambridge University Press, vol. 20(5), pages 904-926, October.
    See citations under working paper version above.
  38. Anna Persson & Timo Teräsvirta, 2003. "The net barter terms of trade: A smooth transition approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 8(1), pages 81-97.
    See citations under working paper version above.
  39. Dick van Dijk 1 & Birgit Strikholm & Timo Teräsvirta, 2003. "The effects of institutional and technological change and business cycle fluctuations on seasonal patterns in quarterly industrial production series," Econometrics Journal, Royal Economic Society, vol. 6(1), pages 79-98, June.
    See citations under working paper version above.
  40. Lundbergh, Stefan & Terasvirta, Timo & van Dijk, Dick, 2003. "Time-Varying Smooth Transition Autoregressive Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(1), pages 104-121, January.
    See citations under working paper version above.
  41. Dick van Dijk & Timo Terasvirta & Philip Hans Franses, 2002. "Smooth Transition Autoregressive Models — A Survey Of Recent Developments," Econometric Reviews, Taylor & Francis Journals, vol. 21(1), pages 1-47.
    See citations under working paper version above.
  42. Skalin, Joakim & Teräsvirta, Timo, 2002. "Modeling Asymmetries And Moving Equilibria In Unemployment Rates," Macroeconomic Dynamics, Cambridge University Press, vol. 6(2), pages 202-241, April.
    See citations under working paper version above.
  43. Davidson, James & Terasvirta, Timo, 2002. "Long memory and nonlinear time series," Journal of Econometrics, Elsevier, vol. 110(2), pages 105-112, October.

    Cited by:

    1. Pan, Shuiyang & Long, Suwan(Cheng) & Wang, Yiming & Xie, Ying, 2023. "Nonlinear asset pricing in Chinese stock market: A deep learning approach," International Review of Financial Analysis, Elsevier, vol. 87(C).
    2. Gbaguidi DAVID, 2011. "Expectations Impact On The Effectiveness Of The Inflation-Real Activity Trade-Off," Theoretical and Practical Research in the Economic Fields, ASERS Publishing, vol. 2(2), pages 141-181.
    3. Caporale, Guglielmo Maria & Gil-Alana, Luis A. & Poza, Carlos, 2020. "Persistence, non-linearities and structural breaks in European stock market indices," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 50-61.
    4. Chevillon, Guillaume & Mavroeidis, Sophocles, 2011. "Learning generates Long Memory," ESSEC Working Papers WP1113, ESSEC Research Center, ESSEC Business School.
    5. Luis Alberiko Gil-Alaña & Juan C. Cuestas & Estefania Mourelle, 2011. "Is there asymmetric behaviour in African inflation? A non-linear approach," NCID Working Papers 03/2011, Navarra Center for International Development, University of Navarra.
    6. Chevillon, Guillaume & Mavroeidis, Sophocles, 2017. "Learning can generate long memory," Journal of Econometrics, Elsevier, vol. 198(1), pages 1-9.
    7. Holt, Matthew T. & Goodwin, Barry K., 2009. "The Almost Ideal and Translog Demand Systems," MPRA Paper 15092, University Library of Munich, Germany.
    8. Shikta Sing & Supun Chandrasena & Yue Shi & Abdullah Alhussain & Claude DIEBOLT & Martin Enilov & Tapas Mishra, 2024. "A Learning Model with Memory in the Financial Markets," Working Papers 06-24, Association Française de Cliométrie (AFC).
    9. Caporale, Guglielmo Maria & Gil-Alana, Luis A., 2008. "Modelling the US, UK and Japanese unemployment rates: Fractional integration and structural breaks," Computational Statistics & Data Analysis, Elsevier, vol. 52(11), pages 4998-5013, July.
    10. Caporale, Guglielmo Maria & Gil-Alana, Luis A. & Poza, Carlos, 2020. "High and low prices and the range in the European stock markets: A long-memory approach," Research in International Business and Finance, Elsevier, vol. 52(C).
    11. Banerjee, Anindya & Urga, Giovanni, 2005. "Modelling structural breaks, long memory and stock market volatility: an overview," Journal of Econometrics, Elsevier, vol. 129(1-2), pages 1-34.
    12. CHIKHI, Mohamed, 2011. "Analyse du choc informationnel et de l’hétéroscédasticité conditionnelle dans les flux de trésorerie [Analysis of informational shock and conditional heteroscedasticity in cash flows]," MPRA Paper 77269, University Library of Munich, Germany, revised Jun 2011.

  44. He, Changli & Teräsvirta, Timo & Malmsten, Hans, 2002. "Moment Structure Of A Family Of First-Order Exponential Garch Models," Econometric Theory, Cambridge University Press, vol. 18(4), pages 868-885, August.

    Cited by:

    1. Eduardo Rossi & Dean Fantazzini, 2012. "Long memory and Periodicity in Intraday Volatility," DEM Working Papers Series 015, University of Pavia, Department of Economics and Management.
    2. Georgios Bampinas & Konstantinos Ladopoulos & Theodore Panagiotidis, 2018. "A note on the estimated GARCH coefficients from the S&P1500 universe," Applied Economics, Taylor & Francis Journals, vol. 50(34-35), pages 3647-3653, July.
    3. Giraitis, Liudas & Leipus, Remigijus & Robinson, Peter M. & Surgailis, Donatas, 2004. "LARCH, leverage, and long memory," LSE Research Online Documents on Economics 294, London School of Economics and Political Science, LSE Library.
    4. Sofia Anyfantaki & Antonis Demos, 2012. "Estimation and Properties of a Time-Varying EGARCH(1,1) in Mean Model," DEOS Working Papers 1228, Athens University of Economics and Business.
    5. Liudas Giraitis, 2004. "LARCH, Leverage, and Long Memory," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 177-210.
    6. Hartz, Christoph & Mittnik, Stefan & Paolella, Marc, 2006. "Accurate value-at-risk forecasting based on the normal-GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2295-2312, December.
    7. DEMOS Antonis, & KYRIAKOPOULOU Dimitra,, 2018. "Finite sample theory and bias correction of maximum likelihood estimators in the EGARCH model," LIDAM Discussion Papers CORE 2018007, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Pourkhanali, Armin & Tafakori, Laleh & Bee, Marco, 2023. "Forecasting Value-at-Risk using functional volatility incorporating an exogenous effect," International Review of Financial Analysis, Elsevier, vol. 89(C).
    9. Francq, Christian & Wintenberger, Olivier & Zakoïan, Jean-Michel, 2013. "GARCH models without positivity constraints: Exponential or log GARCH?," Journal of Econometrics, Elsevier, vol. 177(1), pages 34-46.
    10. Nankervis, John C. & Savin, N. E., 2010. "Testing for Serial Correlation: Generalized Andrews–Ploberger Tests," Journal of Business & Economic Statistics, American Statistical Association, vol. 28(2), pages 246-255.
    11. Rodríguez, Mª José, 2009. "GARCH models with leverage effect : differences and similarities," DES - Working Papers. Statistics and Econometrics. WS ws090302, Universidad Carlos III de Madrid. Departamento de Estadística.
    12. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107630024, January.
    13. Veiga, Helena, 2006. "Modelling long-memory volatilities with leverage effect: ALMSV versus FIEGARCH," DES - Working Papers. Statistics and Econometrics. WS ws066016, Universidad Carlos III de Madrid. Departamento de Estadística.
    14. Dominique Guegan & Bertrand K. Hassani, 2019. "Risk Measurement," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02119256, HAL.
    15. Hartz, Christoph & Mittnik, Stefan & Paolella, Marc S., 2006. "Accurate Value-at-Risk forecast with the (good old) normal-GARCH model," CFS Working Paper Series 2006/23, Center for Financial Studies (CFS).
    16. Wintenberger, Olivier, 2013. "Continuous invertibility and stable QML estimation of the EGARCH(1,1) model," MPRA Paper 46027, University Library of Munich, Germany.
    17. M. Angeles Carnero, 2004. "Persistence and Kurtosis in GARCH and Stochastic Volatility Models," Journal of Financial Econometrics, Oxford University Press, vol. 2(2), pages 319-342.
    18. FERNANDES, Marcelo & GRAMMIG, Joachim, 2001. "A family of autoregressive conditional duration models," LIDAM Discussion Papers CORE 2001036, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    19. Timo Terasvirta & Zhenfang Zhao, 2011. "Stylized facts of return series, robust estimates and three popular models of volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 21(1-2), pages 67-94.
    20. Hafner, Christian & Kyriakopoulou, Dimitra, 2020. "Exponential-Type GARCH Models With Linear-in-Variance Risk Premium," LIDAM Reprints ISBA 2020029, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    21. Linton, Oliver & Wu, Jianbin, 2020. "A coupled component DCS-EGARCH model for intraday and overnight volatility," Journal of Econometrics, Elsevier, vol. 217(1), pages 176-201.
    22. Menelaos Karanasos & J. Kim, "undated". "Moments of the ARMA-EGARCH Model," Discussion Papers 00/29, Department of Economics, University of York.
    23. Amélie Charles & Olivier Darné, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Post-Print hal-01598141, HAL.
    24. Wintenberger, Olivier & Cai, Sixiang, 2011. "Parametric inference and forecasting in continuously invertible volatility models," MPRA Paper 31767, University Library of Munich, Germany.
    25. Dalla, Violetta, 2015. "Power transformations of absolute returns and long memory estimation," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 1-18.
    26. Ruiz Esther & Pérez Ana, 2012. "Maximally Autocorrelated Power Transformations: A Closer Look at the Properties of Stochastic Volatility Models," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(3), pages 1-33, September.
    27. Christian M. Dahl & Emma M. Iglesias, 2008. "The limiting properties of the QMLE in a general class of asymmetric volatility models," CREATES Research Papers 2008-38, Department of Economics and Business Economics, Aarhus University.
    28. Kirt C. Butler & Katsushi Okada, 2008. "Higher-Order Terms in Bivariate Returns to International Stock Market Indices," Multinational Finance Journal, Multinational Finance Journal, vol. 12(1-2), pages 127-155, March-Jun.
    29. Charles, Amélie & Darné, Olivier, 2019. "The accuracy of asymmetric GARCH model estimation," International Economics, Elsevier, vol. 157(C), pages 179-202.
    30. John C. Nankervis & Nathan E. Savin, 2012. "Testing for uncorrelated errors in ARMA models: non‐standard Andrews‐Ploberger tests," Econometrics Journal, Royal Economic Society, vol. 15(3), pages 516-534, October.
    31. Carol Alexander & Emese Lazar & Silvia Stanescu, 2010. "Analytic Moments for GARCH Processes," ICMA Centre Discussion Papers in Finance icma-dp2011-07, Henley Business School, University of Reading, revised Apr 2011.
    32. Liudas Giraitis & Remigijus Leipus & Peter M Robinson & Donatas Surgailis, 2003. "LARCH, Leverage and Long Memory," STICERD - Econometrics Paper Series 460, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    33. Malmsten, Hans & Teräsvirta, Timo, 2004. "Stylized Facts of Financial Time Series and Three Popular Models of Volatility," SSE/EFI Working Paper Series in Economics and Finance 563, Stockholm School of Economics, revised 03 Sep 2004.
    34. Das, Mahamitra & Kundu, Srikanta & Sarkar, Nityananda, 2019. "Mean and Volatility Spillovers between REIT and Stocks Returns A STVAR-BTGARCH-M Model," MPRA Paper 94707, University Library of Munich, Germany.
    35. Gregor Dorfleitner & Carina Lung, 2018. "Cryptocurrencies from the perspective of euro investors: a re-examination of diversification benefits and a new day-of-the-week effect," Journal of Asset Management, Palgrave Macmillan, vol. 19(7), pages 472-494, December.
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    38. Wilfredo Palma & Mauricio Zevallos, 2004. "Analysis of the correlation structure of square time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 25(4), pages 529-550, July.
    39. Neil Kellard & Denise Osborn & Jerry Coakley & John C. Nankervis & Periklis Kougoulis & Jerry Coakley, 2015. "Generalized Variance-Ratio Tests in the Presence of Statistical Dependence," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(5), pages 687-705, September.
    40. Carnero, M. Angeles & Pérez, Ana, 2019. "Leverage effect in energy futures revisited," Energy Economics, Elsevier, vol. 82(C), pages 237-252.
    41. Antonis Demos & Dimitra Kyriakopoulou, 2011. "Bias Correction of ML and QML Estimators in the EGARCH(1,1) Model," DEOS Working Papers 1108, Athens University of Economics and Business.
    42. Batten, Jonathan A. & Mo, Di & Pourkhanali, Armin, 2024. "Can inflation predict energy price volatility?," Energy Economics, Elsevier, vol. 129(C).
    43. Sucarrat, Genaro, 2010. "The power log-GARCH model," UC3M Working papers. Economics we1013, Universidad Carlos III de Madrid. Departamento de Economía.
    44. Mr. Jerome Vandenbussche & Mr. Stanley B Watt & Szabolcs Blazsek, 2009. "The Liquidity and Liquidity Distribution Effects in Emerging Markets: The Case of Jordan," IMF Working Papers 2009/228, International Monetary Fund.
    45. Giraitis, Liudas & Leipus, Remigijus & Robinson, Peter M. & Surgailis, Donatas, 2003. "LARCH, leverage and long memory," LSE Research Online Documents on Economics 2020, London School of Economics and Political Science, LSE Library.
    46. Pérez, Ana & Ruiz, Esther & Veiga, Helena, 2009. "A note on the properties of power-transformed returns in long-memory stochastic volatility models with leverage effect," Computational Statistics & Data Analysis, Elsevier, vol. 53(10), pages 3593-3600, August.
    47. María José Rodríguez & Esther Ruiz, 2012. "Revisiting Several Popular GARCH Models with Leverage Effect: Differences and Similarities," Journal of Financial Econometrics, Oxford University Press, vol. 10(4), pages 637-668, September.

  45. Lundbergh, Stefan & Terasvirta, Timo, 2002. "Evaluating GARCH models," Journal of Econometrics, Elsevier, vol. 110(2), pages 417-435, October.
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  46. Franses, Philip Hans & Teräsvirta, Timo, 2001. "Introduction To The Special Issue: Nonlinear Modeling Of Multivariate Macroeconomic Relations," Macroeconomic Dynamics, Cambridge University Press, vol. 5(4), pages 461-465, September.

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    1. Donayre, Luiggi, 2014. "Estimated Thresholds In The Response Of Output To Monetary Policy: Are Large Policy Changes Less Effective?," Macroeconomic Dynamics, Cambridge University Press, vol. 18(1), pages 41-64, January.

  47. Timo Teräsvirta & Ann-Charlotte Eliasson, 2001. "Non-linear error correction and the UK demand for broad money, 1878-1993," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 277-288.

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    1. De Santis, Roberto A. & Favero, Carlo A. & Roffia, Barbara, 2008. "Euro area money demand and international portfolio allocation: a contribution to assessing risks to price stability," Working Paper Series 926, European Central Bank.
    2. Fredj Jawadi & Ricardo M. Sousa, 2012. "Money Demand in the euro area, the US and the UK:Assessing the Role of Nonlinearity," NIPE Working Papers 22/2012, NIPE - Universidade do Minho.
    3. Seitz, Franz & von Landesberger, Julian, 2010. "Household money holdings in the euro area: An explorative investigation," Working Paper Series 1238, European Central Bank.
    4. doğru, bülent, 2013. "Dynamic Analysis of Money Demand Function: Case of Turkey," MPRA Paper 48402, University Library of Munich, Germany.
    5. Garcés Díaz, Daniel Guillermo, 2008. "Efectos de los cambios de la política monetaria en las dinámicas del tipo de cambio, el dinero y los precios en México (1945-2000)," El Trimestre Económico, Fondo de Cultura Económica, vol. 0(299), pages 683-713, julio-sep.
    6. Escribano Alvaro & Torrado María, 2018. "Nonlinear and asymmetric pricing behaviour in the Spanish gasoline market," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 22(5), pages 1-19, December.
    7. Chien-Chiang Lee & An-Hsing Chang, 2013. "Revisiting the demand for money function: evidence from the random coefficients approach," Quantitative Finance, Taylor & Francis Journals, vol. 13(9), pages 1491-1502, September.
    8. Theodore Panagiotidis, 2003. "Market Efficiency and the Euro:The case of the Athens Stock Exchange," Public Policy Discussion Papers 03-08, Economics and Finance Section, School of Social Sciences, Brunel University.
    9. Jyh-Lin Wu & Yu-Hau Hu, 2007. "Currency substitution and nonlinear error correction in Taiwan's demand for broad money," Applied Economics, Taylor & Francis Journals, vol. 39(13), pages 1635-1645.
    10. Timo Teräsvirta, 2017. "Nonlinear models in macroeconometrics," CREATES Research Papers 2017-32, Department of Economics and Business Economics, Aarhus University.
    11. Tomáš Havránek & Jana Sedlaříková, 2014. "Meta-analýza důchodové elasticity poptávky po penězích [A Meta-Analysis of the Income Elasticity of Money Demand]," Politická ekonomie, Prague University of Economics and Business, vol. 2014(3), pages 366-382.
    12. Lee, Chien-Chiang & Chen, Pei-Fen & Chang, Chun-Ping, 2007. "Testing linearity in a cointegrating STR model for the money demand function: International evidence from G-7 countries," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 76(4), pages 293-302.
    13. Calza, Alessandro & Zaghini, Andrea, 2009. "Nonlinearities In The Dynamics Of The Euro Area Demand For M1," Macroeconomic Dynamics, Cambridge University Press, vol. 13(1), pages 1-19, February.
    14. Escribano, Álvaro & Wang, Dandan, 2021. "Mixed random forest, cointegration, and forecasting gasoline prices," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1442-1462.
    15. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    16. Deborah Gefang, 2012. "Money‐output Causality Revisited – A Bayesian Logistic Smooth Transition VECM Perspective," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 74(1), pages 131-151, February.
    17. I A Venetis & I Paya & D Peel, 2009. "ESTAR model with multiple fixed points. Testing and Estimation," Working Papers 599093, Lancaster University Management School, Economics Department.
    18. Levent KORAP & Metin YILDIRIM, 2012. "Testing the Lucas Critique for the Turkish Money Demand Function," Iktisat Isletme ve Finans, Bilgesel Yayincilik, vol. 27(318), pages 57-82.
    19. Rosales, Francisco & von-Cramon, Stephan, 2015. "Analysis of Price Transmission using a Nonparametric Error Correction Model with Time-Varying Cointegration," 2015 Conference, August 9-14, 2015, Milan, Italy 230227, International Association of Agricultural Economists.
    20. A Duarte & J L Nicolini-Llosa & I Paya, 2007. "Estimating Argentina''s imports elasticities," Working Papers 583372, Lancaster University Management School, Economics Department.
    21. Franz Seitz & Julian von Landesberger, 2012. "Household Money Demand: The Euro Area Case," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 148(III), pages 409-438, September.
    22. Amir Kia, 2002. "Interest Free and Interest-Bearing Money Demand: Policy Invariance and Stability," Working Papers 0214, Economic Research Forum, revised 09 May 2002.
    23. Rodríguez, Juan Andrés & Arranz Cuesta, Miguel Angel, 2025. "Are money demand equations still alive and kicking? Historical evidence of cointegration for the UK, using nonlinear techniques," UC3M Working papers. Economics 45845, Universidad Carlos III de Madrid. Departamento de Economía.
    24. Mouyad Alsamara & Zouhair Mrabet, 2019. "Asymmetric impacts of foreign exchange rate on the demand for money in Turkey: new evidence from nonlinear ARDL," International Economics and Economic Policy, Springer, vol. 16(2), pages 335-356, April.
    25. Jui-Chuan (Della) Chang & Dennis W. Jansen, 2005. "The Effect of Monetary Policy on Bank Lending and Aggregate Output: Asymmetries from Nonlinearities in the Lending Channel," Annals of Economics and Finance, Society for AEF, vol. 6(1), pages 129-153, May.
    26. Ericsson Neil R., 2016. "Testing for and estimating structural breaks and other nonlinearities in a dynamic monetary sector," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 20(4), pages 377-398, September.

  48. Granger, Clive W. J. & Terasvirta, Timo, 1999. "A simple nonlinear time series model with misleading linear properties," Economics Letters, Elsevier, vol. 62(2), pages 161-165, February.
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  49. He, Changli & Terasvirta, Timo, 1999. "Properties of moments of a family of GARCH processes," Journal of Econometrics, Elsevier, vol. 92(1), pages 173-192, September.
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  50. Lin, Chien-Fu Jeff & Terasvirta, Timo, 1999. "Testing parameter constancy in linear models against stochastic stationary parameters," Journal of Econometrics, Elsevier, vol. 90(2), pages 193-213, June.
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  51. Changli He & Timo Terasvirta, 1999. "Properties of the Autocorrelation Function of Squared Observations for Second‐order Garch Processes Under Two Sets of Parameter Constraints," Journal of Time Series Analysis, Wiley Blackwell, vol. 20(1), pages 23-30, January.
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  52. Lutkepohl, Helmut & Terasvirta, Timo & Wolters, Jurgen, 1999. "Investigating Stability and Linearity of a German M1 Money Demand Function," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(5), pages 511-525, Sept.-Oct.
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  53. He, Changli & Teräsvirta, Timo, 1999. "FOURTH MOMENT STRUCTURE OF THE GARCH(p,q) PROCESS," Econometric Theory, Cambridge University Press, vol. 15(6), pages 824-846, December.
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  54. Skalin, Joakim & Terasvirta, Timo, 1999. "Another Look at Swedish Business Cycles, 1861-1988," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 14(4), pages 359-378, July-Aug..
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  55. Tobias Rydén & Timo Teräsvirta & Stefan Åsbrink, 1998. "Stylized facts of daily return series and the hidden Markov model," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(3), pages 217-244.
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  56. Jürgen Wolters & Timo Teräsvirta & Helmut Lütkepohl, 1998. "Modeling The Demand For M3 In The Unified Germany," The Review of Economics and Statistics, MIT Press, vol. 80(3), pages 399-409, August.
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  57. Teräsvirta Timo, 1996. "Power Properties of Linearity Tests for Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 1(1), pages 1-10, April.
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  58. Eitrheim, Oyvind & Terasvirta, Timo, 1996. "Testing the adequacy of smooth transition autoregressive models," Journal of Econometrics, Elsevier, vol. 74(1), pages 59-75, September.
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  59. Jansen, Eilev S & Terasvirta, Timo, 1996. "Testing Parameter Constancy and Super Exogeneity in Econometric Equations," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 58(4), pages 735-763, November.
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  60. Kauppi, Eija & Lassila, Jukka & Terasvirta, Timo, 1996. "Short-term forecasting of industrial production with business survey data: experience from Finland's great depression 1990-1993," International Journal of Forecasting, Elsevier, vol. 12(3), pages 373-381, September.

    Cited by:

    1. Juan G Brida & Bibiana Lanzilotta & Lucia I Rosich, 2021. "On the empirical relations between producers expectations and economic growth," Economics Bulletin, AccessEcon, vol. 41(3), pages 1970-1982.
    2. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "“Tracking economic growth by evolving expectations via genetic programming: A two-step approach”," IREA Working Papers 201801, University of Barcelona, Research Institute of Applied Economics, revised Jan 2018.
    3. Boriss Siliverstovs, 2013. "Do business tendency surveys help in forecasting employment?: A real-time evidence for Switzerland," OECD Journal: Journal of Business Cycle Measurement and Analysis, OECD Publishing, Centre for International Research on Economic Tendency Surveys, vol. 2013(2), pages 129-151.
    4. Mansoor Maitah & Daniel Toth & Elena Kuzmenko & Karel r dl & Helena Rezbov & Petra nov, 2016. "Forecast of Employment in Switzerland: The Macroeconomic View," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 132-138.
    5. Oscar Claveria & Enric Monte & Salvador Torra, 2018. "A Data-Driven Approach to Construct Survey-Based Indicators by Means of Evolutionary Algorithms," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 135(1), pages 1-14, January.
    6. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Evolutionary Computation for Macroeconomic Forecasting," Computational Economics, Springer;Society for Computational Economics, vol. 53(2), pages 833-849, February.
    7. Guizzardi, Andrea & Stacchini, Annalisa, 2015. "Real-time forecasting regional tourism with business sentiment surveys," Tourism Management, Elsevier, vol. 47(C), pages 213-223.
    8. Miquel Clar & Juan-Carlos Duque & Rosina Moreno, 2007. "Forecasting business and consumer surveys indicators-a time-series models competition," Applied Economics, Taylor & Francis Journals, vol. 39(20), pages 2565-2580.

  61. Terasvirta, Timo, 1995. "Modelling Nonlinearity in U.S. Gross National Product 1889-1987," Empirical Economics, Springer, vol. 20(4), pages 577-597.

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    1. Frédéric Karamé & Alexandra Olmedo, 2010. "Asymmetric Properties of Impulse Response Functions in Markov-Switching Structural Vector AutoRegressions," Documents de recherche 10-04, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    2. F. Karamé, 2012. "An algorithm for generalized impulse-response functions in Markov-switching structural VAR," Post-Print hal-02877971, HAL.

  62. Deutsch, Melinda & Granger, Clive W. J. & Terasvirta, Timo, 1994. "The combination of forecasts using changing weights," International Journal of Forecasting, Elsevier, vol. 10(1), pages 47-57, June.

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    1. Pesaran, M. Hashem & Weale, Martin, 2006. "Survey Expectations," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 14, pages 715-776, Elsevier.
    2. Robin L. Lumsdaine & Mr. Eswar S Prasad, 1999. "Identifying the Common Component in International Economic Fluctuations: A New Approach," IMF Working Papers 1999/154, International Monetary Fund.
    3. Benavides, Guillermo & Capistrán, Carlos, 2012. "Forecasting exchange rate volatility: The superior performance of conditional combinations of time series and option implied forecasts," Journal of Empirical Finance, Elsevier, vol. 19(5), pages 627-639.
    4. Wenzel, Thomas, 1999. "Combination of biased forecasts: Bias correction or bias based weights?," Technical Reports 1999,50, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    5. Francis X. Diebold & Jose A. Lopez, 1996. "Forecast Evaluation and Combination," NBER Technical Working Papers 0192, National Bureau of Economic Research, Inc.
    6. Tse, Yiuman, 2001. "Index arbitrage with heterogeneous investors: A smooth transition error correction analysis," Journal of Banking & Finance, Elsevier, vol. 25(10), pages 1829-1855, October.
    7. Aguilar, Ruben & Valdivia, Daney, 2011. "Precios de exportación de gas natural para Bolivia: Modelación y pooling de pronósticos [Bolivian natural gas export prices: Modeling and forecast pooling]," MPRA Paper 35485, University Library of Munich, Germany.
    8. Bacci, Livio Agnew & Mello, Luiz Gustavo & Incerti, Taynara & Paulo de Paiva, Anderson & Balestrassi, Pedro Paulo, 2019. "Optimization of combined time series methods to forecast the demand for coffee in Brazil: A new approach using Normal Boundary Intersection coupled with mixture designs of experiments and rotated fact," International Journal of Production Economics, Elsevier, vol. 212(C), pages 186-211.
    9. Sun, Yuying & Hong, Yongmiao & Wang, Shouyang & Zhang, Xinyu, 2023. "Penalized time-varying model averaging," Journal of Econometrics, Elsevier, vol. 235(2), pages 1355-1377.
    10. Farmer, J. Doyne & Heinrich, Torsten & Sabuco, Juan, 2019. "A simulation of the insurance industry: The problem of risk model homogeneity," INET Oxford Working Papers 2019-12, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    11. AsadUllah, Muhammad & Mujahid, Hira & I. Tabash, Mosab & Ayubi, Sharique & Sabri, Rabia, 2020. "Forecasting indian rupee/us dollar: arima, exponential smoothing, naïve, nardl, combination techniques," MPRA Paper 111150, University Library of Munich, Germany.
    12. Eo, Yunjong & Kang, Kyu Ho, 2020. "The effects of conventional and unconventional monetary policy on forecasting the yield curve," Journal of Economic Dynamics and Control, Elsevier, vol. 111(C).
    13. Ramanathan, Ramu & Engle, Robert & Granger, Clive W. J. & Vahid-Araghi, Farshid & Brace, Casey, 1997. "Shorte-run forecasts of electricity loads and peaks," International Journal of Forecasting, Elsevier, vol. 13(2), pages 161-174, June.
    14. de Menezes, Lilian M. & W. Bunn, Derek & Taylor, James W., 2000. "Review of guidelines for the use of combined forecasts," European Journal of Operational Research, Elsevier, vol. 120(1), pages 190-204, January.
    15. Aiolfi Marco & Capistrán Carlos & Timmermann Allan, 2010. "Forecast Combinations," Working Papers 2010-04, Banco de México.
    16. Massimo Guidolin, 2011. "Markov Switching Models in Empirical Finance," Working Papers 415, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    17. de la Croix, David & Lindh, Thomas & Malmberg, Bo, 2009. "Demographic change and economic growth in Sweden: 1750-2050," Journal of Macroeconomics, Elsevier, vol. 31(1), pages 132-148, March.
    18. Sancetta, A., 2007. "Online Forecast Combination for Dependent Heterogeneous Data," Cambridge Working Papers in Economics 0718, Faculty of Economics, University of Cambridge.
    19. Chan Guk Huh, 1998. "Forecasting industrial production using models with business cycle asymmetry," Economic Review, Federal Reserve Bank of San Francisco, pages 29-41.
    20. Yi-Chung Hu, 2023. "Tourism combination forecasting using a dynamic weighting strategy with change-point analysis," Current Issues in Tourism, Taylor & Francis Journals, vol. 26(14), pages 2357-2374, July.
    21. Zhang, Feng, 2007. "An application of vector GARCH model in semiconductor demand planning," European Journal of Operational Research, Elsevier, vol. 181(1), pages 288-297, August.
    22. Lahiri, Kajal & Yang, Liu, 2013. "Forecasting Binary Outcomes," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1025-1106, Elsevier.
    23. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
    24. Chan, Chi Kin & Kingsman, Brian G. & Wong, H., 2004. "Determining when to update the weights in combined forecasts for product demand--an application of the CUSUM technique," European Journal of Operational Research, Elsevier, vol. 153(3), pages 757-768, March.
    25. Bin Chen & Kenwin Maung, 2020. "Time-varying Forecast Combination for High-Dimensional Data," Papers 2010.10435, arXiv.org.
    26. Chen, Bin & Maung, Kenwin, 2023. "Time-varying forecast combination for high-dimensional data," Journal of Econometrics, Elsevier, vol. 237(2).
    27. David, DE LA CROIX & Bo, MALMBERG, 2006. "Growth and Longevity from the Industrial Revolution to the Future of an Aging Society," Discussion Papers (ECON - Département des Sciences Economiques) 2006037, Université catholique de Louvain, Département des Sciences Economiques.
    28. Junrong Liu & Zhiping Chen & Qihong Duan, 2024. "Automation of the Individualized Investing Strategy for an Investment Advisor Established by a Semi-Markov Regime-Switching Model," Computational Economics, Springer;Society for Computational Economics, vol. 63(6), pages 2351-2370, June.
    29. Johannes Mayr & Dirk Ulbricht, 2007. "VAR Model Averaging for Multi-Step Forecasting," ifo Working Paper Series 48, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    30. Sarno, Lucio & Daniel l Thornton & Giorgio Valente, 2003. "Federal Funds Rate Prediction," Royal Economic Society Annual Conference 2003 183, Royal Economic Society.
    31. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    32. Troschke, Sven-Oliver, 1998. "A selective procedure for combining forecasts," Technical Reports 1998,36, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    33. Mark W. Watson & James H. Stock, 2004. "Combination forecasts of output growth in a seven-country data set," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 23(6), pages 405-430.
    34. Yang Yang & Tae-Hwy Lee, 2004. "Bagging Binary Predictors for Time Series," Econometric Society 2004 Far Eastern Meetings 512, Econometric Society.
    35. Clements, Michael P. & Harvey, David I., 2011. "Combining probability forecasts," International Journal of Forecasting, Elsevier, vol. 27(2), pages 208-223, April.
    36. Esteban Fernández-Vázquez & Blanca Moreno, 2017. "Entropy Econometrics for combining regional economic forecasts: A Data-Weighted Prior Estimator," Journal of Geographical Systems, Springer, vol. 19(4), pages 349-370, October.
    37. Chan, Chi Kin & Kingsman, Brian G. & Wong, H., 1999. "The value of combining forecasts in inventory management - a case study in banking," European Journal of Operational Research, Elsevier, vol. 117(2), pages 199-210, September.
    38. Charalampos Stasinakis & Georgios Sermpinis & Konstantinos Theofilatos & Andreas Karathanasopoulos, 2016. "Forecasting US Unemployment with Radial Basis Neural Networks, Kalman Filters and Support Vector Regressions," Computational Economics, Springer;Society for Computational Economics, vol. 47(4), pages 569-587, April.
    39. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
    40. Huiyu Huang & Tae-Hwy Lee, 2010. "To Combine Forecasts or to Combine Information?," Econometric Reviews, Taylor & Francis Journals, vol. 29(5-6), pages 534-570.
    41. Timmermann, Allan & Guidolin, Massimo, 2007. "Forecasts of US Short-term Interest Rates: A Flexible Forecast Combination Approach," CEPR Discussion Papers 6188, C.E.P.R. Discussion Papers.
    42. Li Fuchun & Tkacz Greg, 2004. "Combining Forecasts with Nonparametric Kernel Regressions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 8(4), pages 1-18, December.
    43. Robin L. Lumsdaine & Eswar S. Prasad, 1997. "Identifying the Common Component in International Economic Fluctuations," NBER Working Papers 5984, National Bureau of Economic Research, Inc.
    44. Chen, Cathy W. S., 1998. "A Bayesian analysis of generalized threshold autoregressive models," Statistics & Probability Letters, Elsevier, vol. 40(1), pages 15-22, September.
    45. Park, Timothy A. & Gubanova, Tatiana & Lohr, Luanne & Escalante, Cesar L., 2005. "Forecasting Organic Food Prices: Testing and Evaluating Conditional Predictive Ability," 2005 Annual meeting, July 24-27, Providence, RI 19412, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    46. Chan, Chi Kin & Witt, Stephen F. & Lee, Y.C.E. & Song, H., 2010. "Tourism forecast combination using the CUSUM technique," Tourism Management, Elsevier, vol. 31(6), pages 891-897.
    47. Lee, Tae-Hwy & Yang, Yang, 2006. "Bagging binary and quantile predictors for time series," Journal of Econometrics, Elsevier, vol. 135(1-2), pages 465-497.
    48. Luis Fernando Melo & Héctor Núñez, 2004. "Combinación de Pronósticos de la Inflación en Presencia de cambios Estructurales," Borradores de Economia 286, Banco de la Republica de Colombia.
    49. Thomas Theobald, 2012. "Combining Recession Probability Forecasts from a Dynamic Probit Indicator," IMK Working Paper 89-2012, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    50. Wang, Xiaoqian & Hyndman, Rob J. & Li, Feng & Kang, Yanfei, 2023. "Forecast combinations: An over 50-year review," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1518-1547.
    51. Rendon-Sanchez, Juan F. & de Menezes, Lilian M., 2019. "Structural combination of seasonal exponential smoothing forecasts applied to load forecasting," European Journal of Operational Research, Elsevier, vol. 275(3), pages 916-924.
    52. Elkin Castaño Vélez & Luis Fernando Melo Velandia, 2000. "Metodos de combinacion de pronosticos: una aplicacion a la inflacion," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 52, pages 113-165, Enero Jun.
    53. Liu, Xiuli & Moreno, Blanca & García, Ana Salomé, 2016. "A grey neural network and input-output combined forecasting model. Primary energy consumption forecasts in Spanish economic sectors," Energy, Elsevier, vol. 115(P1), pages 1042-1054.
    54. Sancetta, Alessio, 2007. "Online forecast combinations of distributions: Worst case bounds," Journal of Econometrics, Elsevier, vol. 141(2), pages 621-651, December.

  63. Lin, Chien-Fu Jeff & Terasvirta, Timo, 1994. "Testing the constancy of regression parameters against continuous structural change," Journal of Econometrics, Elsevier, vol. 62(2), pages 211-228, June.

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    1. INOUE Tomoo & OKIMOTO Tatsuyoshi, 2019. "How Does Unconventional Monetary Policy Affect the Global Financial Markets?: Evaluating Policy Effects by Global VAR Models," Discussion papers 19031, Research Institute of Economy, Trade and Industry (RIETI).
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    443. Kushal Banik Chowdhury & Kaustav Kanti Sarkar & Srikanta Kundu, 2021. "Nonlinear relationships between inflation, output growth and uncertainty in India: New evidence from a bivariate threshold model," Bulletin of Economic Research, Wiley Blackwell, vol. 73(3), pages 469-493, July.
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    446. Bradley, Michael D. & Jansen, Dennis W., 2004. "Forecasting with a nonlinear dynamic model of stock returns and industrial production," International Journal of Forecasting, Elsevier, vol. 20(2), pages 321-342.
    447. Barrow, Devon K. & Crone, Sven F., 2016. "Cross-validation aggregation for combining autoregressive neural network forecasts," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1120-1137.
    448. Chen, Yi-Ting, 2003. "Discriminating between competing STAR models," Economics Letters, Elsevier, vol. 79(2), pages 161-167, May.
    449. Liu, Qiming & Liu, Zhenya & Moussa, Faten & Mu, Yuhao, 2024. "International capital flow in a period of high inflation: The case of China," Research in International Business and Finance, Elsevier, vol. 67(PB).
    450. Hsiang-Hsi Liu & Pi-Hsia Hung & Po-Hung Luo Cho, 2021. "Nonlinear Interactions and Volatility Spillovers between Stock and Foreign Exchange Markets: The STVEC-STGARCH-DCC Approach," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 11(4), pages 1-3.
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    452. Jui-Chuan (Della) Chang & Dennis W. Jansen, 2005. "The Effect of Monetary Policy on Bank Lending and Aggregate Output: Asymmetries from Nonlinearities in the Lending Channel," Annals of Economics and Finance, Society for AEF, vol. 6(1), pages 129-153, May.
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    460. Kisswani, Khalid/ M. & Nusair, Salah/ A., 2011. "Non-linear convergence in Asian interest rates and inflation rates," MPRA Paper 34179, University Library of Munich, Germany.
    461. Bo Pieter Johannes Andree & Francisco Blasques & Eric Koomen, 2017. "Smooth Transition Spatial Autoregressive Models," Tinbergen Institute Discussion Papers 17-050/III, Tinbergen Institute.
    462. Mei-Se Chien, 2013. "The Non-linear Ripple Effect of Housing Prices in Taiwan: A Smooth Transition Regressive Model," ERES eres2013_51, European Real Estate Society (ERES).
    463. Korhonen Marko & Puhakka Mikko, 2021. "The Behavior of Divorce Rates: A Smooth Transition Regression Approach," Journal of Time Series Econometrics, De Gruyter, vol. 13(1), pages 1-19, January.
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    475. Saikkonen, Pentti & Choi, In, 2000. "Cointegrating smooth transition regressions with applications to the Asian currency crisis," SFB 373 Discussion Papers 2000,98, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    476. Gabe J. Bondt & Stefano Schiaffi, 2015. "Confidence Matters for Current Economic Growth: Empirical Evidence for the Euro Area and the United States," Social Science Quarterly, Southwestern Social Science Association, vol. 96(4), pages 1027-1040, December.

  66. Boucelham, Jamel & Terasvirta, Timo, 1990. "Use of preliminary values in forecasting industrial production," International Journal of Forecasting, Elsevier, vol. 6(4), pages 463-468, December.

    Cited by:

    1. Thury, Gerhard & Witt, Stephen F., 1998. "Forecasting industrial production using structural time series models," Omega, Elsevier, vol. 26(6), pages 751-767, December.

  67. Terasvirta, Timo, 1987. "Usefulness of proxy variables in linear models with stochastic regressors," Journal of Econometrics, Elsevier, vol. 36(3), pages 377-382, November.

    Cited by:

    1. Giuseppe De Luca & Jan R. Magnus & Franco Peracchi, 2018. "Balanced Variable Addition In Linear Models," Journal of Economic Surveys, Wiley Blackwell, vol. 32(4), pages 1183-1200, September.
    2. Nikolaos Mylonidis, 2003. "Financial variables as leading indicators in Greece," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 9(4), pages 268-278, November.

  68. Judge, George & Yi, Gang & Yancey, Thomas & Terasvirta, Timo, 1987. "The extended Stein procedure for simultaneous model selection and parameter estimation," Journal of Econometrics, Elsevier, vol. 35(2-3), pages 375-391, July.

    Cited by:

    1. Golan, Amos, 2001. "A simultaneous estimation and variable selection rule," Journal of Econometrics, Elsevier, vol. 101(1), pages 165-193, March.

Chapters

  1. Niels Haldrup & Robinson Kruse & Timo Teräsvirta & Rasmus T. Varneskov, 2013. "Unit roots, non-linearities and structural breaks," Chapters, in: Nigar Hashimzade & Michael A. Thornton (ed.), Handbook of Research Methods and Applications in Empirical Macroeconomics, chapter 4, pages 61-94, Edward Elgar Publishing.
    See citations under working paper version above.
  2. Terasvirta, Timo, 2006. "Forecasting economic variables with nonlinear models," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 1, chapter 8, pages 413-457, Elsevier.
    See citations under working paper version above.
  3. Clive W. Granger & Timo Terasvirta & Heather M. Anderson, 1993. "Modeling Nonlinearity over the Business Cycle," NBER Chapters, in: Business Cycles, Indicators, and Forecasting, pages 311-326, National Bureau of Economic Research, Inc.

    Cited by:

    1. Ubilava, David, 2014. "On the Relationship between Financial Instability and Economic Performance: Stressing the Business of Nonlinear Modelling," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170222, Agricultural and Applied Economics Association.
    2. Akdi, Yilmaz & Varlik, Serdar & Berument, M. Hakan, 2020. "Duration of Global Financial Cycles," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 549(C).
    3. Apergis, Nicholas, 2015. "Financial portfolio choice: Do business cycle regimes matter? Panel evidence from international household surveys," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 34(C), pages 14-27.
    4. Luis Eduardo Arango & Luis Fernando Melo, 2001. "Expansions and Contractions in Some Latin American Countries: A View Throught Non- Linear Models," Borradores de Economia 2691, Banco de la Republica.
    5. Luis Arango & Andres Gonzalez, 2001. "Some evidence of smooth transition nonlinearity in Colombian inflation," Applied Economics, Taylor & Francis Journals, vol. 33(2), pages 155-162.
    6. Maximo Cosme Camacho Alonso & Gabriel Perez-Quiros, 2000. "This is What Leading Indicators Lead," Econometric Society World Congress 2000 Contributed Papers 0202, Econometric Society.
    7. Willi Semmler, 2011. "Asset Prices, Booms and Recessions," Springer Books, Springer, number 978-3-642-20680-1, March.
    8. Novella Maugeri, 2014. "Some Pitfalls in Smooth Transition Models Estimation: A Monte Carlo Study," Computational Economics, Springer;Society for Computational Economics, vol. 44(3), pages 339-378, October.
    9. Nath, Hiranya K., 2016. "A note on the cyclical behavior of sectoral employment in the U.S," Economic Analysis and Policy, Elsevier, vol. 50(C), pages 52-61.
    10. Edward S. Knotek & Saeed Zaman, 2020. "Asymmetric Responses of Consumer Spending to Energy Prices: A Threshold VAR Approach," Working Papers 20-17, Federal Reserve Bank of Cleveland.
    11. Donayre, Luiggi & Panovska, Irina, 2016. "State-dependent exchange rate pass-through behavior," Journal of International Money and Finance, Elsevier, vol. 64(C), pages 170-195.
    12. Luis Eduardo Arango Thomas, 1998. "Some univariate time series properties of output," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 49, pages 7-46, Julio Dic.
    13. Luis Eduardo Arango & Fernando Arias & Luz Adriana Flórez, 2008. "Trends, Fluctuations, and Determinants of Commodity Prices," Borradores de Economia 521, Banco de la Republica de Colombia.
    14. Nguyen, Quoc Phu & Vo, Duc Hong, 2022. "Artificial intelligence and unemployment:An international evidence," Structural Change and Economic Dynamics, Elsevier, vol. 63(C), pages 40-55.
    15. Blake LeBaron, 1994. "Chaos and Nonlinear Forecastability in Economics and Finance," Finance 9411001, University Library of Munich, Germany.
    16. Huh, Hyeon-seung, 2002. "GDP growth and the composite leading index: a nonlinear causality analysis for eleven countries," Economics Letters, Elsevier, vol. 77(1), pages 93-99, September.
    17. Granger, Clive W. J. & Jeon, Yongil, 2003. "A time-distance criterion for evaluating forecasting models," International Journal of Forecasting, Elsevier, vol. 19(2), pages 199-215.
    18. Javed Ahmad Bhat & Sajad Ahmad Bhat & Waseem Ahmad Parray, 2025. "Nonlinearity in exchange rate pass-through across BRICS: Role of business cycle and inflation," International Economics and Economic Policy, Springer, vol. 22(1), pages 1-32, February.
    19. Yýlmaz Akdi & Serdar Varlik & Hakan Berument, 2018. "Cycle Duration in Production with Periodicity – Evidence from Turkey," International Econometric Review (IER), Econometric Research Association, vol. 10(2), pages 24-32, September.
    20. James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc.

  4. Terasvirta, Timo & Tjostheim, Dag & W.J. Granger, Clive, 1986. "Aspects of modelling nonlinear time series," Handbook of Econometrics, in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 48, pages 2917-2957, Elsevier.

    Cited by:

    1. Giorgio Busetti & Matteo Manera, 2003. "STAR-GARCH Models for Stock Market Interactions in the Pacific Basin Region, Japan and US," Working Papers 2003.43, Fondazione Eni Enrico Mattei.
    2. Andros Kourtellos & Thanasis Stengos & Yiguo Sun, 2017. "Endogeneity in Semiparametric Threshold Regression," Working Paper series 17-13, Rimini Centre for Economic Analysis.
    3. Bruce E. Hansen, 1996. "Estimation of TAR Models," Boston College Working Papers in Economics 325., Boston College Department of Economics.
    4. Adrian Pagan & Hashem Pesaran, 2007. "Econometric Analysis of Structural Systems with Permanent and Transitory Shocks. Working paper #7," NCER Working Paper Series 7, National Centre for Econometric Research.
    5. James H. Stock & Mark W. Watson, 1998. "A Comparison of Linear and Nonlinear Univariate Models for Forecasting Macroeconomic Time Series," NBER Working Papers 6607, National Bureau of Economic Research, Inc.

Books

  1. Terasvirta, Timo & Tjostheim, Dag & Granger, Clive W. J., 2010. "Modelling Nonlinear Economic Time Series," OUP Catalogue, Oxford University Press, number 9780199587155.

    Cited by:

    1. Galvão, Ana Beatriz, 2013. "Changes in predictive ability with mixed frequency data," International Journal of Forecasting, Elsevier, vol. 29(3), pages 395-410.
    2. Bonciani, Dario, 2015. "Estimating the effects of uncertainty over the business cycle," MPRA Paper 65921, University Library of Munich, Germany.
    3. Yu. A. Polunin & A. Yu. Yudanov, 2020. "Growth Rates of Companies and Filling of a Market Niche," Studies on Russian Economic Development, Springer, vol. 31(2), pages 202-211, March.
    4. Silvennoinen, Annastiina & Teräsvirta, Timo, 2024. "Consistency and asymptotic normality of maximum likelihood estimators of a multiplicative time-varying smooth transition correlation GARCH model," Econometrics and Statistics, Elsevier, vol. 32(C), pages 57-72.
    5. Emilio Zanetti Chini, 2018. "Forecaster’s utility and forecasts coherence," CREATES Research Papers 2018-01, Department of Economics and Business Economics, Aarhus University.
    6. Cristina Amado & Timo Teräsvirta, 2011. "Modelling Volatility by Variance Decomposition," NIPE Working Papers 01/2011, NIPE - Universidade do Minho.
    7. Psaradakis, Zacharias & Vávra, Marián, 2014. "On testing for nonlinearity in multivariate time series," Economics Letters, Elsevier, vol. 125(1), pages 1-4.
    8. Heinzelmann Ludwig & Missong Martin, 2020. "Nonlinear interest rate-setting behaviour of German commercial banks," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(3), pages 1-28, June.
    9. R. Xie & O. Isengildina-Massa & G. P. Dwyer & J. L. Sharp, 2016. "The impact of public and semi-public information on cotton futures market," Applied Economics, Taylor & Francis Journals, vol. 48(36), pages 3416-3431, August.
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    6. Dalu Zhang & Peter Moffatt, 2013. "Time series non-linearity in the real growth / recession-term spread relationship," University of East Anglia Applied and Financial Economics Working Paper Series 047, School of Economics, University of East Anglia, Norwich, UK..

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