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Stefan Mittnik

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.

Working papers

  1. Davide Lauria & W. Brent Lindquist & Stefan Mittnik & Svetlozar T. Rachev, 2022. "ESG-Valued Portfolio Optimization and Dynamic Asset Pricing," Papers 2206.02854, arXiv.org.

    Cited by:

    1. Nancy Asare Nyarko & Bhathiya Divelgama & Jagdish Gnawali & Blessing Omotade & Svetlozar T. Rachev & Peter Yegon, 2023. "Exploring Dynamic Asset Pricing within Bachelier’s Market Model," JRFM, MDPI, vol. 16(8), pages 1-18, July.
    2. Nancy Asare Nyarko & Bhathiya Divelgama & Jagdish Gnawali & Blessing Omotade & Svetlozar Rachev & Peter Yegon, 2023. "Exploring Dynamic Asset Pricing within Bachelier Market Model," Papers 2307.04059, arXiv.org.
    3. Yuan Hu & W. Brent Lindquist & Svetlozar T. Rachev & Frank J. Fabozzi, 2023. "Option pricing using a skew random walk pricing tree," Papers 2303.17014, arXiv.org.

  2. Jason R. Bailey & Davide Lauria & W. Brent Lindquist & Stefan Mittnik & Svetlozar T. Rachev, 2022. "Hedonic Models of Real Estate Prices: GAM and Environmental Factors," Papers 2210.14266, arXiv.org.

    Cited by:

    1. Jason R. Bailey & W. Brent Lindquist & Svetlozar T. Rachev, 2024. "Hedonic Models Incorporating ESG Factors for Time Series of Average Annual Home Prices," Papers 2404.07132, arXiv.org.

  3. Abootaleb Shirvani & Stefan Mittnik & W. Brent Lindquist & Svetlozar T. Rachev, 2021. "Bitcoin Volatility and Intrinsic Time Using Double Subordinated Levy Processes," Papers 2109.15051, arXiv.org, revised Aug 2023.

    Cited by:

    1. Yifan He & Abootaleb Shirvani & Barret Shao & Svetlozar Rachev & Frank Fabozzi, 2024. "Beyond the Bid-Ask: Strategic Insights into Spread Prediction and the Global Mid-Price Phenomenon," Papers 2404.11722, arXiv.org.

  4. Cheng Peng & Young Shin Kim & Stefan Mittnik, 2020. "Portfolio Optimization on Multivariate Regime Switching GARCH Model with Normal Tempered Stable Innovation," Papers 2009.11367, arXiv.org, revised Feb 2023.

    Cited by:

    1. Li, Chenxing, 2022. "A multivariate GARCH model with an infinite hidden Markov mixture," MPRA Paper 112792, University Library of Munich, Germany.

  5. Stefan Mittnik & Willi Semmler & Alexander Haider, 2019. "Climate Disaster Risks – Empirics and a Multi-Phase Dynamic Model," IMF Working Papers 2019/145, International Monetary Fund.

    Cited by:

    1. Ar'anzazu de Juan & Pilar Poncela & Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2022. "Economic activity and climate change," Papers 2206.03187, arXiv.org, revised Jun 2022.
    2. Andreas Breitenfellner & Wolfgang Pointner & Helene Schuberth, 2019. "The Potential Contribution of Central Banks to Green Finance," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 88(2), pages 55-71.

  6. Svetlozar Rachev & Stoyan Stoyanov & Stefan Mittnik & Frank J. Fabozzi & Abootaleb Shirvani, 2017. "Behavioral Finance -- Asset Prices Predictability, Equity Premium Puzzle, Volatility Puzzle: The Rational Finance Approach," Papers 1710.03211, arXiv.org, revised Feb 2020.

    Cited by:

    1. Binghui Wu & Tingting Duan, 2019. "Nonlinear Dynamics Characteristic of Risk Contagion in Financial Market Based on Agent Modeling and Complex Network," Complexity, Hindawi, vol. 2019, pages 1-12, June.

  7. Svetlozar T. Rachev & Stefan Mittnik & Frank J. Fabozzi, 2016. "Pricing Derivatives in Hermite Markets," Papers 1612.07016, arXiv.org, revised Dec 2016.

    Cited by:

    1. Daw, Lara & Kerchev, George, 2023. "Fractal dimensions of the Rosenblatt process," Stochastic Processes and their Applications, Elsevier, vol. 161(C), pages 544-571.

  8. Mittnik, Stefan & Semmler, Willi, 2014. "Overleveraging, financial fragility and the banking-macro link: Theory and empirical evidence," ZEW Discussion Papers 14-110, ZEW - Leibniz Centre for European Economic Research.

    Cited by:

    1. Nyambuu, Unurjargal & Semmler, Willi, 2017. "Emerging markets’ resource booms and busts, borrowing risk and regime change," Structural Change and Economic Dynamics, Elsevier, vol. 41(C), pages 29-42.
    2. Lucidi, Francesco Simone & Semmler, Willi, 2023. "Long-run scarring effects of meltdowns in a small-scale nonlinear quadratic model," Journal of Macroeconomics, Elsevier, vol. 75(C).
    3. Willi Semmler & Fabio Della Rossa & Giuseppe Orlando & Gabriel R. Padro Rosario & Levent Kockesen, 2023. "Endogenous Economic Resilience, Loss of Resilience, Persistent Cycles, Multiple Attractors, and Disruptive Contractions," Working Papers 2309, New School for Social Research, Department of Economics.
    4. Kanzari, Dalel & Nakhli, Mohamed Sahbi & Gaies, Brahim & Sahut, Jean-Michel, 2023. "Predicting macro-financial instability – How relevant is sentiment? Evidence from long short-term memory networks," Research in International Business and Finance, Elsevier, vol. 65(C).
    5. Faulwasser Timm & Gross Marco & Loungani Prakash & Semmler Willi, 2020. "Unconventional monetary policy in a nonlinear quadratic model," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 24(5), pages 1-19, December.
    6. Julia M. Puaschunder, 2020. "Monetary Systems," Proceedings of the 16th International RAIS Conference, March 30-31, 2020 001jm1, Research Association for Interdisciplinary Studies.
    7. Donal Smith, 2016. "The International Impact of Financial Shocks: A Global VAR and Connectedness Measures Approach," Discussion Papers 16/07, Department of Economics, University of York.
    8. Issa, Samar & Gevorkyan, Aleksandr V., 2022. "Optimal corporate leverage and speculative cycles: an empirical estimation," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 478-491.

  9. Stefan Mittnik & Nikolay Robinzonov & Klaus Wohlrabe, 2013. "The Micro Dynamics of Macro Announcements," CESifo Working Paper Series 4421, CESifo.

    Cited by:

    1. Stefan Sauer & Klaus Wohlrabe, 2018. "The New ifo Business Climate Index for Germany," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 19(02), pages 59-64, July.
    2. Stefan Mittnik & Nikolay Robinzonov & Klaus Wohlrabe, 2013. "What Moves the DAX?," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(23), pages 32-36, December.
    3. Stefan Sauer & Klaus Wohlrabe, 2020. "ifo Handbuch der Konjunkturumfragen," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 88.

  10. Mittnik, Stefan, 2013. "VaR-implied tail-correlation matrices," CFS Working Paper Series 2013/05, Center for Financial Studies (CFS).

    Cited by:

    1. Kim, Young Shin & Lee, Jaesung & Mittnik, Stefan & Park, Jiho, 2015. "Quanto option pricing in the presence of fat tails and asymmetric dependence," Journal of Econometrics, Elsevier, vol. 187(2), pages 512-520.
    2. Mittnik, Stefan, 2013. "VaR-implied tail-correlation matrices," CFS Working Paper Series 2013/05, Center for Financial Studies (CFS).
    3. Paulusch, Joachim & Schlütter, Sebastian, 2022. "Sensitivity-implied tail-correlation matrices," Journal of Banking & Finance, Elsevier, vol. 134(C).
    4. Joachim Paulusch, 2017. "The Solvency II Standard Formula, Linear Geometry, and Diversification," JRFM, MDPI, vol. 10(2), pages 1-12, May.
    5. Paulusch, Joachim & Schlütter, Sebastian, 2021. "Sensitivity-implied tail-correlation matrices," ICIR Working Paper Series 33/19, Goethe University Frankfurt, International Center for Insurance Regulation (ICIR), revised 2021.
    6. Aigner, Philipp, 2023. "Identifying scenarios for the own risk and solvency assessment of insurance companies," ICIR Working Paper Series 48/23, Goethe University Frankfurt, International Center for Insurance Regulation (ICIR).
    7. 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.

  11. Stefan Mittnik & Willi Semmler, 2013. "The Real Consequences of Financial Stress," SFB 649 Discussion Papers SFB649DP2013-011, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.

    Cited by:

    1. Mittnik, Stefan & Semmler, Willi, 2013. "The real consequences of financial stress," Journal of Economic Dynamics and Control, Elsevier, vol. 37(8), pages 1479-1499.
    2. Yao, Xiaoyang & Le, Wei & Sun, Xiaolei & Li, Jianping, 2020. "Financial stress dynamics in China: An interconnectedness perspective," International Review of Economics & Finance, Elsevier, vol. 68(C), pages 217-238.
    3. 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.
    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. Tommaso Ferraresi & Andrea Roventini & Willi Semmler, 2016. "Macroeconomic Regimes, Technological Shocks and Employment Dynamics," Sciences Po publications 2016-19, Sciences Po.
    6. Makrelov, Konstantin & Arndt, Channing & Davies, Rob & Harris, Laurence, 2020. "Balance sheet changes and the impact of financial sector risk-taking on fiscal multipliers," Economic Modelling, Elsevier, vol. 87(C), pages 322-343.
    7. Dindo, Pietro & Modena, Andrea & Pelizzon, Loriana, 2022. "Risk pooling, intermediation efficiency, and the business cycle," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    8. Francesco Simone Lucidi, 2019. "Real-time signals anticipating credit booms in Euro Area countries," Working Papers in Public Economics 189, University of Rome La Sapienza, Department of Economics and Law.
    9. Mittnik, Stefan & Semmler, Willi, 2018. "Overleveraging, Financial Fragility, And The Banking–Macro Link: Theory And Empirical Evidence," Macroeconomic Dynamics, Cambridge University Press, vol. 22(1), pages 4-32, January.
    10. Brunnermeier, Markus & Sannikov, Yuliy, 2016. "Macro, Money and Finance: A Continuous Time Approach," CEPR Discussion Papers 11329, C.E.P.R. Discussion Papers.
    11. Brana, Sophie & Prat, Stéphanie, 2016. "The effects of global excess liquidity on emerging stock market returns: Evidence from a panel threshold model," Economic Modelling, Elsevier, vol. 52(PA), pages 26-34.
    12. Giorgio Fagiolo & Andrea Roventini, 2016. "Macroeconomic Policy in DGSE and Agent-Based Models Redux: New Developments and Challenges Ahead," Sciences Po publications info:hdl:2441/dcditnq6282, Sciences Po.
    13. Chen, Louisa & Verousis, Thanos & Wang, Kai & Zhou, Zhiping, 2023. "Financial stress and commodity price volatility," Energy Economics, Elsevier, vol. 125(C).
    14. Stolbov, Mikhail & Shchepeleva, Maria & Karminsky, Alexander, 2022. "When central bank research meets Google search: A sentiment index of global financial stress," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 81(C).
    15. Schleer Frauke & Semmler Willi, 2016. "Banking Overleveraging and Macro Instability: A Model and VSTAR Estimations," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 236(6), pages 609-638, December.
    16. Stona, Filipe & Morais, Igor A.C. & Triches, Divanildo, 2018. "Economic dynamics during periods of financial stress: Evidences from Brazil," International Review of Economics & Finance, Elsevier, vol. 55(C), pages 130-144.
    17. Huang, Yu-Fan, 2015. "Time variation in U.S. monetary policy and credit spreads," Journal of Macroeconomics, Elsevier, vol. 43(C), pages 205-215.
    18. Hong, Yanran & Li, Pan & Wang, Lu & Zhang, Yaojie, 2023. "New evidence of extreme risk transmission between financial stress and international crude oil markets," Research in International Business and Finance, Elsevier, vol. 64(C).
    19. Dovern, Jonas & van Roye, Björn, 2013. "International transmission of financial stress: Evidence from a GVAR," Kiel Working Papers 1844, Kiel Institute for the World Economy (IfW Kiel).
    20. Gross, Marco & Henry, Jerome & Semmler, Willi, 2018. "Destabilizing Effects Of Bank Overleveraging On Real Activity—An Analysis Based On A Threshold Mcs-Gvar," Macroeconomic Dynamics, Cambridge University Press, vol. 22(7), pages 1750-1768, October.
    21. 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.
    22. Uluceviz, Erhan & Yilmaz, Kamil, 2021. "Measuring real–financial connectedness in the U.S. economy," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    23. Evgenidis, Anastasios & Tsagkanos, Athanasios, 2017. "Asymmetric effects of the international transmission of US financial stress. A threshold-VAR approach," International Review of Financial Analysis, Elsevier, vol. 51(C), pages 69-81.
    24. Proaño, Christian R. & Schoder, Christian & Semmler, Willi, 2014. "Financial stress, sovereign debt and economic activity in industrialized countries: Evidence from dynamic threshold regressions," Journal of International Money and Finance, Elsevier, vol. 45(C), pages 17-37.
    25. 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.
    26. Semmler, Willi & Haider, Alexander, 2015. "The perils of debt deflation in the euro area: A multi regime model," ZEW Discussion Papers 15-071, ZEW - Leibniz Centre for European Economic Research.
    27. Samar Issa, 2020. "Life after Debt: The Effects of Overleveraging on Conventional and Islamic Banks," JRFM, MDPI, vol. 13(6), pages 1-46, June.
    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. Marina Yu. Malkina & Rodion V. Balakin, 2023. "The Relation of Financial and Industrial Stresses to Monetary Policy Parameters in the Russian Economy," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 3, pages 104-121, June.
    30. Mao, Jie & Shen, Guanxiong & Yan, Jingzhou, 2023. "A continuous-time macro-finance model with Knightian uncertainty," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).
    31. Phil Armstrong, 2020. "Can Heterodox Economics Make a Difference?," Books, Edward Elgar Publishing, number 19964, December.
    32. Brunnermeier, M.K. & Sannikov, Y., 2016. "Macro, Money, and Finance," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1497-1545, Elsevier.
    33. Manfred Kremer, 2016. "Macroeconomic effects of financial stress and the role of monetary policy: a VAR analysis for the euro area," International Economics and Economic Policy, Springer, vol. 13(1), pages 105-138, January.
    34. Ernst, Ekkehard & Semmler, Willi & Haider, Alexander, 2016. "Debt deflation, financial market stress and regime change: Evidence from Europe using MRVAR," ZEW Discussion Papers 16-030, ZEW - Leibniz Centre for European Economic Research.
    35. Schleer, Frauke & Semmler, Willi, 2013. "Financial sector-output dynamics in the euro area: Non-linearities reconsidered," ZEW Discussion Papers 13-068, ZEW - Leibniz Centre for European Economic Research.
    36. Jayantee SAHOO, 2020. "Financial stress index, growth and price stability in India: Some recent evidence," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(1(622), S), pages 105-124, Spring.
    37. Semmler, Willi & Tahri, Ibrahim, 2017. "Current account imbalances: A new approach to assess external debt sustainability," Economic Modelling, Elsevier, vol. 62(C), pages 161-170.
    38. Pu Chen & Willi Semmler, 2018. "Short and Long Effects of Productivity on Unemployment," Open Economies Review, Springer, vol. 29(4), pages 853-878, September.
    39. Christian Proano & Christian Schoder & Willi Semmler, 2013. "The Role of Financial Stress in Debt and Recovery," SCEPA policy note series. 2012-02, Schwartz Center for Economic Policy Analysis (SCEPA), The New School.
    40. Fischer, Henning & Stolper, Oscar, 2019. "The nonlinear dynamics of corporate bond spreads: Regime-dependent effects of their determinants," Discussion Papers 08/2019, Deutsche Bundesbank.
    41. Carrillo Julio A. & García Ana Laura, 2021. "The COVID-19 Economic Crisis in Mexico through the Lens of a Financial Conditions Index," Working Papers 2021-23, Banco de México.
    42. Haddou, Samira, 2022. "International financial stress spillovers to bank lending: Do internal characteristics matter?," International Review of Financial Analysis, Elsevier, vol. 83(C).
    43. Serena Merrino, 2021. "Statedependent fiscal multipliers and financial dynamics An impulse response analysis by local projections for South Africa," Working Papers 11015, South African Reserve Bank.
    44. Poeschel, Friedrich, 2012. "Assortative matching through signals," IAB-Discussion Paper 201215, Institut für Arbeitsmarkt- und Berufsforschung (IAB), Nürnberg [Institute for Employment Research, Nuremberg, Germany].
    45. George Apostolakis & Athanasios P. Papadopoulos, 2019. "Financial Stability, Monetary Stability and Growth: a PVAR Analysis," Open Economies Review, Springer, vol. 30(1), pages 157-178, February.
    46. Giorgio Fagiolo & Andrea Roventini, 2016. "Macroeconomic Policy in DGSE and Agent-Based Models Redux," Working Papers hal-03459348, HAL.
    47. Mikhail Stolbov & Maria Shchepeleva, 2021. "Macrofinancial linkages in Europe: Evidence from quantile local projections," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(4), pages 5557-5569, October.
    48. Konstantin Makrelov & Channing Arndt & Rob Davies & Laurence Harris, 2018. "Fiscal multipliers in South Africa: The importance of financial sector dynamics," WIDER Working Paper Series wp-2018-6, World Institute for Development Economic Research (UNU-WIDER).
    49. Stephan B. Bruns & David I. Stern, 2015. "Meta-Granger causality testing," CAMA Working Papers 2015-22, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    50. Tihana Skrinjaric, 2022. "Macroeconomic effects of systemic stress: a rolling spillover index approach," Public Sector Economics, Institute of Public Finance, vol. 46(1), pages 109-140.
    51. Goldberg, Andrew & Romalis, John, 2015. "Public Debt and Growth in U.S. States," Working Papers 2015-10, University of Sydney, School of Economics.
    52. Samar Issa, 2022. "Financial Crises and Business Cycle Implications for Islamic and Non-Islamic Bank Lending in Indonesia," JRFM, MDPI, vol. 15(7), pages 1-32, June.
    53. Mikhail Stolbov & Maria Shchepeleva, 2018. "Systemic risk in Europe: deciphering leading measures, common patterns and real effects," Annals of Finance, Springer, vol. 14(1), pages 49-91, February.
    54. Samar Issa & Gulhan Bizel & Sharath Kumar Jagannathan & Sri Sarat Chaitanya Gollapalli, 2024. "A Comprehensive Approach to Bankruptcy Risk Evaluation in the Financial Industry," JRFM, MDPI, vol. 17(1), pages 1-22, January.
    55. Dovern, Jonas & van Roye, Björn, 2014. "International transmission and business-cycle effects of financial stress," Journal of Financial Stability, Elsevier, vol. 13(C), pages 1-17.
    56. Kappler, Marcus & Schleer, Frauke, 2017. "A financially stressed euro area," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 11, pages 1-37.
    57. Ishmael Radikoko & Shadreck A. Mutobo & Mphoeng Mphoeng, 2019. "The Impact of Stock Market Development on Economic Growth: The Case of Botswana," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 11(12), pages 149-149, December.
    58. Caulkins, Jonathan P. & Feichtinger, Gustav & Grass, Dieter & Hartl, Richard F. & Kort, Peter M. & Seidl, Andrea, 2015. "Capital stock management during a recession that freezes credit markets," Journal of Economic Behavior & Organization, Elsevier, vol. 116(C), pages 1-14.
    59. Kappler, Marcus & Schleer, Frauke, 2013. "How many factors and shocks cause financial stress?," ZEW Discussion Papers 13-100, ZEW - Leibniz Centre for European Economic Research.

  12. Willi Semmler & Stefan Mittnik, 2012. "Estimating a Banking-Macro Model for Europe Using a Multi-Regime VAR," EcoMod2012 4122, EcoMod.

    Cited by:

    1. Baglioni, Angelo & Cherubini, Umberto, 2013. "Within and between systemic country risk. Theory and evidence from the sovereign crisis in Europe," Journal of Economic Dynamics and Control, Elsevier, vol. 37(8), pages 1581-1597.
    2. Proaño, Christian R. & Schoder, Christian & Semmler, Willi, 2014. "Financial stress, sovereign debt and economic activity in industrialized countries: Evidence from dynamic threshold regressions," Journal of International Money and Finance, Elsevier, vol. 45(C), pages 17-37.

  13. Stefan Mittnik & Sandra Paterlini & Tina Yener, 2011. "Operational–risk Dependencies and the Determination of Risk Capital," Center for Economic Research (RECent) 070, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".

    Cited by:

    1. Lu Wei & Jianping Li & Xiaoqian Zhu, 2018. "Operational Loss Data Collection: A Literature Review," Annals of Data Science, Springer, vol. 5(3), pages 313-337, September.
    2. Oliver Kley & Claudia Kluppelberg & Sandra Paterlini, 2019. "Modelling Extremal Dependence for Operational Risk by a Bipartite Graph," Papers 1902.03041, arXiv.org.
    3. Brechmann, Eike & Czado, Claudia & Paterlini, Sandra, 2014. "Flexible dependence modeling of operational risk losses and its impact on total capital requirements," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 271-285.

  14. Stefan Mittnik & Willi Semmler, 2011. "The Instability of the Banking Sector and Macrodynamics: Theory and Empirics," DEGIT Conference Papers c016_080, DEGIT, Dynamics, Economic Growth, and International Trade.

    Cited by:

    1. Shrestha, Prakash Kumar, 2012. "Banking systems, central banks and international reserve accumulation in East Asian economies," Economics Discussion Papers 2012-48, Kiel Institute for the World Economy (IfW Kiel).
    2. Semmler, Willi & Proaño, Christian R., 2015. "Escape routes from sovereign default risk in the euro area," ZEW Discussion Papers 15-020, ZEW - Leibniz Centre for European Economic Research.
    3. Issa, Samar & Gevorkyan, Aleksandr V., 2022. "Optimal corporate leverage and speculative cycles: an empirical estimation," Structural Change and Economic Dynamics, Elsevier, vol. 62(C), pages 478-491.

  15. Thiemo Krink & Stefan Mittnik & Sandra Paterlini, 2009. "Differential Evolution and Combinatorial Search for Constrained Index Tracking," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0016, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".

    Cited by:

    1. Margherita Giuzio, 2017. "Genetic algorithm versus classical methods in sparse index tracking," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 40(1), pages 243-256, November.
    2. Chiara Pederzoli & Costanza Torricelli, 2013. "Efficiency and unbiasedness of corn futures markets: New evidence across the financial crisis," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0040, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    3. Andriosopoulos, Kostas & Nomikos, Nikos, 2014. "Performance replication of the Spot Energy Index with optimal equity portfolio selection: Evidence from the UK, US and Brazilian markets," European Journal of Operational Research, Elsevier, vol. 234(2), pages 571-582.
    4. Elisabetta Gualandri & Mario Noera, 2014. "Towards A Macroprudential Policy In The Eu: Main Issues," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0049, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    5. Andriosopoulos, Kostas & Doumpos, Michael & Papapostolou, Nikos C. & Pouliasis, Panos K., 2013. "Portfolio optimization and index tracking for the shipping stock and freight markets using evolutionary algorithms," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 52(C), pages 16-34.
    6. Stelios Tsafarakis & Charalampos Saridakis & Nikolaos Matsatsinis & George Baltas, 2016. "Private labels and retail assortment planning: a differential evolution approach," Annals of Operations Research, Springer, vol. 247(2), pages 677-692, December.
    7. Elena Giarda & Gloria Moroni, 2015. "‘It’s a trap!’ The degree of poverty persistence in Italy and Europe," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0055, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    8. Beatrice Bertelli & Gianna Boero & Costanza Torricelli, 2021. "The market price of greenness A factor pricing approach for Green Bonds," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0083, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    9. Andrea Scozzari & Fabio Tardella & Sandra Paterlini & Thiemo Krink, 2012. "Exact and heuristic approaches for the index tracking problem with UCITS constraints," Center for Economic Research (RECent) 081, University of Modena and Reggio E., Dept. of Economics "Marco Biagi".
    10. Mahdi Moeini, 2022. "Solving the index tracking problem: a continuous optimization approach," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(2), pages 807-835, June.
    11. Costanza Torricelli & Eleonora Pellati, 2022. "Social Bonds and the “Social Premiumâ€," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0085, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    12. Doering, Jana & Kizys, Renatas & Juan, Angel A. & Fitó, Àngels & Polat, Onur, 2019. "Metaheuristics for rich portfolio optimisation and risk management: Current state and future trends," Operations Research Perspectives, Elsevier, vol. 6(C).
    13. Ardia, David & Boudt, Kris & Carl, Peter & Mullen, Katharine M. & Peterson, Brian, 2010. "Differential Evolution (DEoptim) for Non-Convex Portfolio Optimization," MPRA Paper 22135, University Library of Munich, Germany.
    14. Thiemo Krink & Sandra Paterlini, 2011. "Multiobjective optimization using differential evolution for real-world portfolio optimization," Computational Management Science, Springer, vol. 8(1), pages 157-179, April.
    15. Stefano Cosma & Elisabetta Gualandri, 2013. "The sovereign debt crisis: the impact on the intermediation model of Italian banks," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0042, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    16. Meihua Wang & Chengxian Xu & Fengmin Xu & Hongang Xue, 2012. "A mixed 0–1 LP for index tracking problem with CVaR risk constraints," Annals of Operations Research, Springer, vol. 196(1), pages 591-609, July.
    17. Billio, Monica & Caporin, Massimiliano & Costola, Michele, 2015. "Backward/forward optimal combination of performance measures for equity screening," The North American Journal of Economics and Finance, Elsevier, vol. 34(C), pages 63-83.
    18. Chiara Pederzoli & Costanza Torricelli, 2019. "The impact of the Fundamental Review of the Trading Book: A preliminary assessment on a stylized portfolio," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0075, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    19. Elisabetta Gualandri, 2011. "Basel 3, Pillar 2: the role of banks’ internal governance and control function," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0027, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    20. Elisabetta Gualandri & Mario Noera, 2014. "Monitoring Systemic Risk: A Survey Of The Available Macroprudential Toolkit," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0050, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    21. Marianna Brunetti & Roberta de Luca, 2022. "Pre-selection in cointegration-based pairs trading," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0089, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    22. Sant’Anna, Leonardo R. & Filomena, Tiago P. & Caldeira, João F., 2017. "Index tracking and enhanced indexing using cointegration and correlation with endogenous portfolio selection," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 146-157.
    23. Leonardo Riegel Sant’Anna & Tiago Pascoal Filomena & Pablo Cristini Guedes & Denis Borenstein, 2017. "Index tracking with controlled number of assets using a hybrid heuristic combining genetic algorithm and non-linear programming," Annals of Operations Research, Springer, vol. 258(2), pages 849-867, November.
    24. Francesca Arnaboldi, Francesca Gioia, 2019. "Portfolio choice: Evidence from new-borns," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0078, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    25. Gnägi, M. & Strub, O., 2020. "Tracking and outperforming large stock-market indices," Omega, Elsevier, vol. 90(C).
    26. Chen, Wei, 2015. "Artificial bee colony algorithm for constrained possibilistic portfolio optimization problem," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 125-139.
    27. Jules Clement Mba & Sutene Mwambi, 2020. "A Markov-switching COGARCH approach to cryptocurrency portfolio selection and optimization," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(2), pages 199-214, June.
    28. Liang-chuan Wu & I-chan Tsai, 2014. "Three fuzzy goal programming models for index portfolios," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(8), pages 1155-1169, August.
    29. Dean Altshuler & Carlo Alberto Magni, 2015. "Introducing Aggregate Return on Investment as a Solution to the Contradiction Between Some PME Metrics and IRR," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0056, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    30. Marianna Lyra, 2010. "Heuristic Strategies in Finance – An Overview," Working Papers 045, COMISEF.
    31. Bj�rn Fastrich & Sandra Paterlini & Peter Winker, 2014. "Cardinality versus q -norm constraints for index tracking," Quantitative Finance, Taylor & Francis Journals, vol. 14(11), pages 2019-2032, November.
    32. Elisabetta Gualandri & Valeria Venturelli, 2013. "The financing of Italian firms and the credit crunch: findings and exit strategies," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0041, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    33. Massimo Baldini & Giovanni Gallo & Costanza Torricelli, 2017. "Past Income Scarcity and Current Perception of Financial Fragility," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0064, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    34. H Mezali & J E Beasley, 2013. "Quantile regression for index tracking and enhanced indexation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 64(11), pages 1676-1692, November.
    35. Carlo Alberto Magni, 2015. "Pseudo-naïve approaches to investment performance measurement," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0051, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    36. Jules Clement Mba & Edson Pindza & Ur Koumba, 2018. "A differential evolution copula-based approach for a multi-period cryptocurrency portfolio optimization," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 32(4), pages 399-418, November.
    37. Emilio Ricardo Carvalhais & Antonio Marcos Duarte Júnior, 2015. "Indexation of Fixed-Income Portfolios to the IMA-B," Brazilian Business Review, Fucape Business School, vol. 12(3), pages 116-142, May.
    38. Costanza Torricelli & Fabio Ferrari, 2022. "Climate Stress Test: bad (or good) news for the market? An Event Study Analysis on Euro Zone Banks," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0086, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    39. Björn Fastrich & Peter Winker, 2014. "Combining Forecasts with Missing Data: Making Use of Portfolio Theory," Computational Economics, Springer;Society for Computational Economics, vol. 44(2), pages 127-152, August.
    40. Chiara Pederzoli & Costanza Torricelli, 2010. "A parsimonious default prediction model for Italian SMEs," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0022, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    41. Enrico Rubaltelli & Sergio Agnoli & Michela Rancan & Tiziana Pozzoli, 2015. "Emotional Intelligence and risk taking in investment decision-making," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0053, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    42. Costanza Torricelli & Beatrice Bertelli, 2022. "ESG compliant optimal portfolios: The impact of ESG constraints on portfolio optimization in a sample of European stocks," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0088, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    43. Stefano Cosma & Francesca Pancotto & Paola Vezzani, 2018. "Customer Complaining and Probability of Default in Consumer Credit," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0068, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".

  16. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).

    Cited by:

    1. 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.
    2. Philippe Charlot & Olivier Darné & Zakaria Moussa, 2014. "Commodity returns co-movements: Fundamentals or "style" effect?," Working Papers hal-01093631, HAL.
    3. Jammazi, Rania, 2012. "Oil shock transmission to stock market returns: Wavelet-multivariate Markov switching GARCH approach," Energy, Elsevier, vol. 37(1), pages 430-454.
    4. Daniel King & Ferdi Botha, 2014. "Modelling Stock Return Volatility Dynamics in Selected African Markets," Working Papers 410, Economic Research Southern Africa.
    5. Su, EnDer, 2013. "Stock index hedge using trend and volatility regime switch model considering hedging cost," MPRA Paper 49190, University Library of Munich, Germany.
    6. Jin, Xin & Maheu, John M., 2016. "Modeling covariance breakdowns in multivariate GARCH," Journal of Econometrics, Elsevier, vol. 194(1), pages 1-23.
    7. Su, EnDer, 2017. "Stock index hedging using a trend and volatility regime-switching model involving hedging cost," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 233-254.

  17. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2008. "Asymmetric multivariate normal mixture GARCH," CFS Working Paper Series 2008/07, Center for Financial Studies (CFS).

    Cited by:

    1. Gambacciani, Marco & Paolella, Marc S., 2017. "Robust normal mixtures for financial portfolio allocation," Econometrics and Statistics, Elsevier, vol. 3(C), pages 91-111.
    2. Augustyniak, Maciej, 2014. "Maximum likelihood estimation of the Markov-switching GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 61-75.
    3. Krishnakumar, Jaya & Kabili, Andi & Roko, Ilir, 2012. "Estimation of SEM with GARCH errors," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3153-3181.
    4. Sang‐Kuck Chung, 2009. "Out‐of‐sample Hedge Performances for Risk Management in China Commodity Futures Markets," Asian Economic Journal, East Asian Economic Association, vol. 23(3), pages 349-372, September.
    5. Broda, Simon A. & Haas, Markus & Krause, Jochen & Paolella, Marc S. & Steude, Sven C., 2013. "Stable mixture GARCH models," Journal of Econometrics, Elsevier, vol. 172(2), pages 292-306.
    6. Alp, Tansel & Demetrescu, Matei, 2010. "Joint forecasts of Dow Jones stocks under general multivariate loss function," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2360-2371, November.
    7. Ruili Sun & Tiefeng Ma & Shuangzhe Liu & Milind Sathye, 2019. "Improved Covariance Matrix Estimation for Portfolio Risk Measurement: A Review," JRFM, MDPI, vol. 12(1), pages 1-34, March.
    8. Thomas Chuffart, 2013. "Selection Criteria in Regime Switching Conditional Volatility Models," AMSE Working Papers 1339, Aix-Marseille School of Economics, France, revised 14 Jul 2013.
    9. Marc S. Paolella, 2017. "The Univariate Collapsing Method for Portfolio Optimization," Econometrics, MDPI, vol. 5(2), pages 1-33, May.
    10. Otranto, Edoardo, 2010. "Identifying financial time series with similar dynamic conditional correlation," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 1-15, January.
    11. Markus Haas & Jochen Krause & Marc S. Paolella & Sven C. Steude, 2013. "Time-Varying Mixture GARCH Models and Asymmetric Volatility," Swiss Finance Institute Research Paper Series 13-04, Swiss Finance Institute.
    12. Santos, André A.P. & Moura, Guilherme V., 2014. "Dynamic factor multivariate GARCH model," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 606-617.
    13. 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.
    14. Francq, Christian & Jiménez Gamero, Maria Dolores & Meintanis, Simos, 2015. "Tests for sphericity in multivariate garch models," MPRA Paper 67411, University Library of Munich, Germany.
    15. Boudt, Kris & Croux, Christophe, 2010. "Robust M-estimation of multivariate GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2459-2469, November.
    16. Andrey A. Gnidchenko & Vladimir A. Salnikov, 2015. "Net Comparative Advantage Index: Overcoming the Drawbacks of the Existing Indices," HSE Working papers WP BRP 119/EC/2015, National Research University Higher School of Economics.
    17. Marc S. Paolella, 2016. "Stable-GARCH Models for Financial Returns: Fast Estimation and Tests for Stability," Econometrics, MDPI, vol. 4(2), pages 1-28, May.
    18. Carla Mascarenhas & Anderson Rei Galvão & Carla Susana Marques, 2022. "How Perceived Organizational Support, Identification with Organization and Work Engagement Influence Job Satisfaction: A Gender-Based Perspective," Administrative Sciences, MDPI, vol. 12(2), pages 1-15, May.
    19. Paolella, Marc S. & Polak, Paweł & Walker, Patrick S., 2019. "Regime switching dynamic correlations for asymmetric and fat-tailed conditional returns," Journal of Econometrics, Elsevier, vol. 213(2), pages 493-515.
    20. Achraf Ghorbel & Ahmed Jeribi, 2021. "Volatility spillovers and contagion between energy sector and financial assets during COVID-19 crisis period," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 11(3), pages 449-467, September.
    21. Francq, C. & Jiménez-Gamero, M.D. & Meintanis, S.G., 2017. "Tests for conditional ellipticity in multivariate GARCH models," Journal of Econometrics, Elsevier, vol. 196(2), pages 305-319.
    22. Arismendi, J.C., 2013. "Multivariate truncated moments," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 41-75.

  18. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).

    Cited by:

    1. 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.
    2. Philippe Charlot & Olivier Darné & Zakaria Moussa, 2014. "Commodity returns co-movements: Fundamentals or "style" effect?," Working Papers hal-01093631, HAL.
    3. Jammazi, Rania, 2012. "Oil shock transmission to stock market returns: Wavelet-multivariate Markov switching GARCH approach," Energy, Elsevier, vol. 37(1), pages 430-454.
    4. Daniel King & Ferdi Botha, 2014. "Modelling Stock Return Volatility Dynamics in Selected African Markets," Working Papers 410, Economic Research Southern Africa.
    5. Su, EnDer, 2013. "Stock index hedge using trend and volatility regime switch model considering hedging cost," MPRA Paper 49190, University Library of Munich, Germany.
    6. Jin, Xin & Maheu, John M., 2016. "Modeling covariance breakdowns in multivariate GARCH," Journal of Econometrics, Elsevier, vol. 194(1), pages 1-23.
    7. Su, EnDer, 2017. "Stock index hedging using a trend and volatility regime-switching model involving hedging cost," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 233-254.

  19. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2006. "Multivariate normal mixture GARCH," CFS Working Paper Series 2006/09, Center for Financial Studies (CFS).

    Cited by:

    1. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    2. Chung, Sang-Kuck, 2009. "Bivariate mixed normal GARCH models and out-of-sample hedge performances," Finance Research Letters, Elsevier, vol. 6(3), pages 130-137, September.
    3. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2008. "Asymmetric multivariate normal mixture GARCH," CFS Working Paper Series 2008/07, Center for Financial Studies (CFS).
    4. Giorgio Canarella & Stephen M. Miller & Stephen K. Pollard, 2009. "Dynamic Stock Market Interactions between the Canadian, Mexican, and the United States Markets: The NAFTA Experience," Working Papers 0905, University of Nevada, Las Vegas , Department of Economics.

  20. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2006. "Multivariate normal mixture GARCH," CFS Working Paper Series 2006/09, Center for Financial Studies (CFS).

    Cited by:

    1. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    2. Chung, Sang-Kuck, 2009. "Bivariate mixed normal GARCH models and out-of-sample hedge performances," Finance Research Letters, Elsevier, vol. 6(3), pages 130-137, September.
    3. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2008. "Asymmetric multivariate normal mixture GARCH," CFS Working Paper Series 2008/07, Center for Financial Studies (CFS).
    4. Giorgio Canarella & Stephen M. Miller & Stephen K. Pollard, 2009. "Dynamic Stock Market Interactions between the Canadian, Mexican, and the United States Markets: The NAFTA Experience," Working Papers 0905, University of Nevada, Las Vegas , Department of Economics.

  21. Doganoglu, Toker & Hartz, Christoph & Mittnik, Stefan, 2006. "Portfolio optimization when risk factors are conditionally varying and heavy tailed," CFS Working Paper Series 2006/24, Center for Financial Studies (CFS).

    Cited by:

    1. Clara Calvo & Carlos Ivorra & Vicente Liern & Blanca Pérez-Gladish, 2021. "Grading Investment Diversification Options in Presence of Non-Historical Financial Information," Mathematics, MDPI, vol. 9(6), pages 1-11, March.
    2. Broda, Simon A. & Haas, Markus & Krause, Jochen & Paolella, Marc S. & Steude, Sven C., 2013. "Stable mixture GARCH models," Journal of Econometrics, Elsevier, vol. 172(2), pages 292-306.
    3. Margherita Giuzio & Sandra Paterlini, 2019. "Un-diversifying during crises: Is it a good idea?," Computational Management Science, Springer, vol. 16(3), pages 401-432, July.
    4. Salhi, Khaled & Deaconu, Madalina & Lejay, Antoine & Champagnat, Nicolas & Navet, Nicolas, 2016. "Regime switching model for financial data: Empirical risk analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 148-157.
    5. Thiemo Krink & Sandra Paterlini, 2008. "Differential Evolution for Multiobjective Portfolio Optimization," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0007, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    6. Mainik, Georg & Mitov, Georgi & Rüschendorf, Ludger, 2015. "Portfolio optimization for heavy-tailed assets: Extreme Risk Index vs. Markowitz," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 115-134.
    7. Calzolari, Giorgio & Halbleib, Roxana, 2018. "Estimating stable latent factor models by indirect inference," Journal of Econometrics, Elsevier, vol. 205(1), pages 280-301.
    8. Marc S. Paolella, 2016. "Stable-GARCH Models for Financial Returns: Fast Estimation and Tests for Stability," Econometrics, MDPI, vol. 4(2), pages 1-28, May.
    9. Georg Mainik & Georgi Mitov & Ludger Ruschendorf, 2015. "Portfolio optimization for heavy-tailed assets: Extreme Risk Index vs. Markowitz," Papers 1505.04045, arXiv.org.
    10. K. Liagkouras & K. Metaxiotis, 2019. "Improving the performance of evolutionary algorithms: a new approach utilizing information from the evolutionary process and its application to the fuzzy portfolio optimization problem," Annals of Operations Research, Springer, vol. 272(1), pages 119-137, January.
    11. Matteo Bonato, 2012. "Modeling fat tails in stock returns: a multivariate stable-GARCH approach," Computational Statistics, Springer, vol. 27(3), pages 499-521, September.

  22. Doganoglu, Toker & Hartz, Christoph & Mittnik, Stefan, 2006. "Portfolio optimization when risk factors are conditionally varying and heavy tailed," CFS Working Paper Series 2006/24, Center for Financial Studies (CFS).

    Cited by:

    1. Clara Calvo & Carlos Ivorra & Vicente Liern & Blanca Pérez-Gladish, 2021. "Grading Investment Diversification Options in Presence of Non-Historical Financial Information," Mathematics, MDPI, vol. 9(6), pages 1-11, March.
    2. Broda, Simon A. & Haas, Markus & Krause, Jochen & Paolella, Marc S. & Steude, Sven C., 2013. "Stable mixture GARCH models," Journal of Econometrics, Elsevier, vol. 172(2), pages 292-306.
    3. Margherita Giuzio & Sandra Paterlini, 2019. "Un-diversifying during crises: Is it a good idea?," Computational Management Science, Springer, vol. 16(3), pages 401-432, July.
    4. Salhi, Khaled & Deaconu, Madalina & Lejay, Antoine & Champagnat, Nicolas & Navet, Nicolas, 2016. "Regime switching model for financial data: Empirical risk analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 148-157.
    5. Thiemo Krink & Sandra Paterlini, 2008. "Differential Evolution for Multiobjective Portfolio Optimization," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 0007, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
    6. Mainik, Georg & Mitov, Georgi & Rüschendorf, Ludger, 2015. "Portfolio optimization for heavy-tailed assets: Extreme Risk Index vs. Markowitz," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 115-134.
    7. Calzolari, Giorgio & Halbleib, Roxana, 2018. "Estimating stable latent factor models by indirect inference," Journal of Econometrics, Elsevier, vol. 205(1), pages 280-301.
    8. Marc S. Paolella, 2016. "Stable-GARCH Models for Financial Returns: Fast Estimation and Tests for Stability," Econometrics, MDPI, vol. 4(2), pages 1-28, May.
    9. Georg Mainik & Georgi Mitov & Ludger Ruschendorf, 2015. "Portfolio optimization for heavy-tailed assets: Extreme Risk Index vs. Markowitz," Papers 1505.04045, arXiv.org.
    10. K. Liagkouras & K. Metaxiotis, 2019. "Improving the performance of evolutionary algorithms: a new approach utilizing information from the evolutionary process and its application to the fuzzy portfolio optimization problem," Annals of Operations Research, Springer, vol. 272(1), pages 119-137, January.
    11. Matteo Bonato, 2012. "Modeling fat tails in stock returns: a multivariate stable-GARCH approach," Computational Statistics, Springer, vol. 27(3), pages 499-521, September.

  23. Corsi, Fulvio & Kretschmer, Uta & Mittnik, Stefan & Pigorsch, Christian, 2005. "The volatility of realized volatility," CFS Working Paper Series 2005/33, Center for Financial Studies (CFS).

    Cited by:

    1. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
    2. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    3. Chao Liang & Yin Liao & Feng Ma & Bo Zhu, 2022. "United States Oil Fund volatility prediction: the roles of leverage effect and jumps," Empirical Economics, Springer, vol. 62(5), pages 2239-2262, May.
    4. Paul Wohlfarth, 2018. "Measuring the Impact of Monetary Policy Attention on Global Asset Volatility Using Search Data," Birkbeck Working Papers in Economics and Finance 1803, Birkbeck, Department of Economics, Mathematics & Statistics.
    5. Tim Bollerslev & Uta Kretschmer & Christian Pigorsch & George Tauchen, 2010. "A Discrete-Time Model for Daily S&P500 Returns and Realized Variations: Jumps and Leverage Effects," Working Papers 10-06, Duke University, Department of Economics.
    6. Uwe Hassler & Paulo M.M. Rodrigues & Antonio Rubia, 2016. "Quantile Regression for Long Memory Testing: A Case of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(4), pages 693-724.
    7. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Post-Print halshs-02505861, HAL.
    8. Filip Žikeš & Jozef Baruník, 2016. "Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 185-226.
    9. Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    10. Matteo Luciani & David Veredas, 2012. "A model for vast panels of volatilities," Working Papers 1230, Banco de España.
    11. Cubadda, Gianluca & Guardabascio, Barbara & Hecq, Alain, 2017. "A vector heterogeneous autoregressive index model for realized volatility measures," International Journal of Forecasting, Elsevier, vol. 33(2), pages 337-344.
    12. Rossi, Eduardo & Santucci de Magistris, Paolo, 2013. "Long memory and tail dependence in trading volume and volatility," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 94-112.
    13. B. Zhang & J. Wang & W. Zhang & G. C. Wang, 2020. "Nonlinear Scaling Behavior of Visible Volatility Duration for Financial Statistical Physics Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 373-389, August.
    14. Chevallier, Julien & Sévi, Benoît, 2012. "On the volatility–volume relationship in energy futures markets using intraday data," Energy Economics, Elsevier, vol. 34(6), pages 1896-1909.
    15. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2014. "Precious Metals Under the Microscope: A High-Frequency Analysis," Working Papers on Finance 1409, University of St. Gallen, School of Finance.
    16. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
    17. Lazar, Emese & Xue, Xiaohan, 2020. "Forecasting risk measures using intraday data in a generalized autoregressive score framework," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1057-1072.
    18. Massimiliano Caporin & Gabriel G. Velo, 2011. "Modeling and forecasting realized range volatility," "Marco Fanno" Working Papers 0128, Dipartimento di Scienze Economiche "Marco Fanno".
    19. Zheng, Tingguo & Zuo, Haomiao, 2013. "Reexamining the time-varying volatility spillover effects: A Markov switching causality approach," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 643-662.
    20. Isao Ishida & Toshiaki Watanabe, 2009. "Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model," CARF F-Series CARF-F-145, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    21. Hadhri, Sinda & Ftiti, Zied, 2019. "Commonality in liquidity among Middle East and North Africa emerging stock markets: Does it really matter?," Economic Systems, Elsevier, vol. 43(3).
    22. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    23. Evzen Kocenda & Vit Bubak & Filip Zikes, 2011. "Volatility Transmission in Emerging European Foreign Exchange Markets," William Davidson Institute Working Papers Series wp1020, William Davidson Institute at the University of Michigan.
    24. Clements, Michael P. & Galvão, Ana Beatriz & Kim, Jae H., 2006. "Quantile Forecasts of Daily Exchange Rate Returns from Forecasts of Realized Volatility," The Warwick Economics Research Paper Series (TWERPS) 777, University of Warwick, Department of Economics.
    25. Wen Cheong Chin & Min Cherng Lee, 2018. "S&P500 volatility analysis using high-frequency multipower variation volatility proxies," Empirical Economics, Springer, vol. 54(3), pages 1297-1318, May.
    26. Gustavo Fruet Dias & Karsten Schweiker, 2024. "Integrated Variance Estimation for Assets Traded in Multiple Venues," University of East Anglia School of Economics Working Paper Series 2024-04, School of Economics, University of East Anglia, Norwich, UK..
    27. David E. Allen & Michael McAleer & Marcel Scharth, 2010. "Realized Volatility Risk," KIER Working Papers 753, Kyoto University, Institute of Economic Research.
    28. Ait-Sahalia, Yacine & Mykland, Per A. & Zhang, Lan, 2005. "Ultra high frequency volatility estimation with dependent microstructure noise," Discussion Paper Series 1: Economic Studies 2005,30, Deutsche Bundesbank.
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    182. Ole E. Barndorff-Nielsen & Almut E. D. Veraart, 2009. "Stochastic volatility of volatility in continuous time," CREATES Research Papers 2009-25, Department of Economics and Business Economics, Aarhus University.
    183. Zhang, Bo & Wang, Jun & Fang, Wen, 2015. "Volatility behavior of visibility graph EMD financial time series from Ising interacting system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 301-314.
    184. Wang, Xunxiao & Wu, Chongfeng & Xu, Weidong, 2015. "Volatility forecasting: The role of lunch-break returns, overnight returns, trading volume and leverage effects," International Journal of Forecasting, Elsevier, vol. 31(3), pages 609-619.
    185. Chun Liu & John M Maheu, 2010. "Intraday Dynamics of Volatility and Duration: Evidence from the Chinese Stock Market," Working Papers tecipa-401, University of Toronto, Department of Economics.
    186. Todorova, Neda & Souček, Michael, 2014. "Overnight information flow and realized volatility forecasting," Finance Research Letters, Elsevier, vol. 11(4), pages 420-428.
    187. Todorova, Neda, 2015. "The course of realized volatility in the LME non-ferrous metal market," Economic Modelling, Elsevier, vol. 51(C), pages 1-12.
    188. 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.
    189. Ke Yang & Langnan Chen, 2014. "Realized Volatility Forecast: Structural Breaks, Long Memory, Asymmetry, and Day-of-the-Week Effect," International Review of Finance, International Review of Finance Ltd., vol. 14(3), pages 345-392, September.
    190. Xuan Yao & Xiaofeng Hui & Kaican Kang, 2021. "Can night trading sessions improve forecasting performance of gold futures' volatility in China?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 849-860, August.
    191. Vít Bubák & Filip Žikeš, 2009. "Distribution and Dynamics of Central-European Exchange Rates: Evidence from Intraday Data," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 59(4), pages 334-359, Oktober.
    192. Ding, Yi & Kambouroudis, Dimos & McMillan, David G., 2021. "Forecasting realised volatility: Does the LASSO approach outperform HAR?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    193. Nicholas Taylor, 2015. "Realized volatility forecasting in an international context," Applied Economics Letters, Taylor & Francis Journals, vol. 22(6), pages 503-509, April.
    194. Dimitrios P. Louzis & Spyros Xanthopoulos - Sissinis & Apostolos P. Refenes, 2012. "Stock index Value-at-Risk forecasting: A realized volatility extreme value theory approach," Economics Bulletin, AccessEcon, vol. 32(1), pages 981-991.
    195. Philip L. H. Yu & W. K. Li & F. C. Ng, 2017. "The Generalized Conditional Autoregressive Wishart Model for Multivariate Realized Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 513-527, October.
    196. Jonathan R. Stroud & Michael S. Johannes, 2014. "Bayesian Modeling and Forecasting of 24-Hour High-Frequency Volatility," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1368-1384, December.
    197. Ahoniemi, Katja & Lanne, Markku, 2013. "Overnight stock returns and realized volatility," International Journal of Forecasting, Elsevier, vol. 29(4), pages 592-604.
    198. Naimoli, Antonio & Gerlach, Richard & Storti, Giuseppe, 2022. "Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators," Economic Modelling, Elsevier, vol. 107(C).
    199. Dimitrios Louzis & Spyros Xanthopoulos-Sisinis & Apostolos Refenes, 2011. "Stock index realized volatility forecasting in the presence of heterogeneous leverage effects and long range dependence in the volatility of realized volatility," Post-Print hal-00709559, HAL.
    200. Luo, Jiawen & Wang, Shengquan, 2019. "The asymmetric high-frequency volatility transmission across international stock markets," Finance Research Letters, Elsevier, vol. 31(C), pages 104-109.
    201. Heinen, Florian & Willert, Juliane, 2011. "Monitoring a change in persistence of a long range dependent time series," Hannover Economic Papers (HEP) dp-479, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    202. Fulvio Corsi & Francesco Audrino, 2007. "Realized Correlation Tick-by-Tick," University of St. Gallen Department of Economics working paper series 2007 2007-02, Department of Economics, University of St. Gallen.
    203. Mykland, Per A. & Zhang, Lan, 2016. "Between data cleaning and inference: Pre-averaging and robust estimators of the efficient price," Journal of Econometrics, Elsevier, vol. 194(2), pages 242-262.
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    207. Mike Buckle & Jing Chen & Julian Williams, 2014. "How Predictable Are Equity Covariance Matrices? Evidence from High‐Frequency Data for Four Markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(7), pages 542-557, November.
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  24. Haas, Markus & Mittnik, Stefan & Mizrach, Bruce, 2005. "Assessing central bank credibility during the EMS crises: Comparing option and spot market-based forecasts," CFS Working Paper Series 2005/09, Center for Financial Studies (CFS).

    Cited by:

    1. Chen Yu-Fu & Funke Michael & Glanemann Nicole, 2013. "Off-the-record target zones: theory with an application to Hong Kong’s currency board," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 373-393, September.
    2. Li, Liuling & Mizrach, Bruce, 2010. "Tail return analysis of Bear Stearns' credit default swaps," Economic Modelling, Elsevier, vol. 27(6), pages 1529-1536, November.
    3. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    4. Peter Christoffersen & Kris Jacobs & Bo Young Chang, 2011. "Forecasting with Option Implied Information," CREATES Research Papers 2011-46, Department of Economics and Business Economics, Aarhus University.
    5. Markus Haas & Jochen Krause & Marc S. Paolella & Sven C. Steude, 2013. "Time-Varying Mixture GARCH Models and Asymmetric Volatility," Swiss Finance Institute Research Paper Series 13-04, Swiss Finance Institute.
    6. Bruce Mizrach, 2006. "The Enron Bankruptcy: When did the options market in Enron lose it’s smirk?," Review of Quantitative Finance and Accounting, Springer, vol. 27(4), pages 365-382, December.
    7. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2008. "Asymmetric multivariate normal mixture GARCH," CFS Working Paper Series 2008/07, Center for Financial Studies (CFS).
    8. Michael Funke & Julius Loermann & Richhild Moessner, 2017. "The discontinuation of the EUR/CHF minimum exchange rate in January 2015: was it expected?," BIS Working Papers 652, Bank for International Settlements.
    9. Bruce Mizrach, 2007. "Recovering Probabilistic Information From Options Prices and the Underlying," Departmental Working Papers 200702, Rutgers University, Department of Economics.

  25. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2005. "Modeling and predicting market risk with Laplace-Gaussian mixture distributions," CFS Working Paper Series 2005/11, Center for Financial Studies (CFS).

    Cited by:

    1. 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.
    2. Stoyanov, Stoyan V. & Rachev, Svetlozar T. & Fabozzi, Frank J., 2011. "CVaR sensitivity with respect to tail thickness," Working Paper Series in Economics 29, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    3. Saissi Hassani, Samir & Dionne, Georges, 2021. "The New International Regulation of Market Risk: Roles of VaR and CVaR in Model Validation," Working Papers 21-1, HEC Montreal, Canada Research Chair in Risk Management.
    4. Leopoldo Catania, 2016. "Dynamic Adaptive Mixture Models," Papers 1603.01308, arXiv.org, revised Jan 2023.
    5. BOUADDI, Mohammed & ROMBOUTS, Jeroen V.K., 2007. "Mixed exponential power asymmetric conditional heteroskedasticity," LIDAM Discussion Papers CORE 2007097, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. 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).
    7. Gel, Yulia R., 2010. "Test of fit for a Laplace distribution against heavier tailed alternatives," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 958-965, April.
    8. Kaldasch, Joachim, 2014. "Evolutionary model of stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 449-462.
    9. Mahmood Ul Hassan & Pär Stockhammar, 2016. "Fitting probability distributions to economic growth: a maximum likelihood approach," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(9), pages 1583-1603, July.
    10. Yining Chen, 2015. "Semiparametric Time Series Models with Log-concave Innovations: Maximum Likelihood Estimation and its Consistency," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 42(1), pages 1-31, March.
    11. John Douglas (J.D.) Opdyke, 2007. "Comparing Sharpe ratios: So where are the p-values?," Journal of Asset Management, Palgrave Macmillan, vol. 8(5), pages 308-336, December.

  26. Haas, Markus & Mittnik, Stefan & Mizrach, Bruce, 2005. "Assessing central bank credibility during the EMS crises: Comparing option and spot market-based forecasts," CFS Working Paper Series 2005/09, Center for Financial Studies (CFS).

    Cited by:

    1. Chen Yu-Fu & Funke Michael & Glanemann Nicole, 2013. "Off-the-record target zones: theory with an application to Hong Kong’s currency board," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 17(4), pages 373-393, September.
    2. Li, Liuling & Mizrach, Bruce, 2010. "Tail return analysis of Bear Stearns' credit default swaps," Economic Modelling, Elsevier, vol. 27(6), pages 1529-1536, November.
    3. Haas, Markus & Mittnik, Stefan, 2008. "Multivariate regimeswitching GARCH with an application to international stock markets," CFS Working Paper Series 2008/08, Center for Financial Studies (CFS).
    4. Peter Christoffersen & Kris Jacobs & Bo Young Chang, 2011. "Forecasting with Option Implied Information," CREATES Research Papers 2011-46, Department of Economics and Business Economics, Aarhus University.
    5. Markus Haas & Jochen Krause & Marc S. Paolella & Sven C. Steude, 2013. "Time-Varying Mixture GARCH Models and Asymmetric Volatility," Swiss Finance Institute Research Paper Series 13-04, Swiss Finance Institute.
    6. Bruce Mizrach, 2006. "The Enron Bankruptcy: When did the options market in Enron lose it’s smirk?," Review of Quantitative Finance and Accounting, Springer, vol. 27(4), pages 365-382, December.
    7. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2008. "Asymmetric multivariate normal mixture GARCH," CFS Working Paper Series 2008/07, Center for Financial Studies (CFS).
    8. Michael Funke & Julius Loermann & Richhild Moessner, 2017. "The discontinuation of the EUR/CHF minimum exchange rate in January 2015: was it expected?," BIS Working Papers 652, Bank for International Settlements.
    9. Bruce Mizrach, 2007. "Recovering Probabilistic Information From Options Prices and the Underlying," Departmental Working Papers 200702, Rutgers University, Department of Economics.

  27. Corsi, Fulvio & Kretschmer, Uta & Mittnik, Stefan & Pigorsch, Christian, 2005. "The volatility of realized volatility," CFS Working Paper Series 2005/33, Center for Financial Studies (CFS).

    Cited by:

    1. Wang, Yudong & Hao, Xianfeng, 2023. "Forecasting the real prices of crude oil: What is the role of parameter instability?," Energy Economics, Elsevier, vol. 117(C).
    2. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2017. "The contribution of jumps to forecasting the density of returns," Post-Print halshs-01442618, HAL.
    3. Chao Liang & Yin Liao & Feng Ma & Bo Zhu, 2022. "United States Oil Fund volatility prediction: the roles of leverage effect and jumps," Empirical Economics, Springer, vol. 62(5), pages 2239-2262, May.
    4. Paul Wohlfarth, 2018. "Measuring the Impact of Monetary Policy Attention on Global Asset Volatility Using Search Data," Birkbeck Working Papers in Economics and Finance 1803, Birkbeck, Department of Economics, Mathematics & Statistics.
    5. Tim Bollerslev & Uta Kretschmer & Christian Pigorsch & George Tauchen, 2010. "A Discrete-Time Model for Daily S&P500 Returns and Realized Variations: Jumps and Leverage Effects," Working Papers 10-06, Duke University, Department of Economics.
    6. Uwe Hassler & Paulo M.M. Rodrigues & Antonio Rubia, 2016. "Quantile Regression for Long Memory Testing: A Case of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(4), pages 693-724.
    7. Christophe Chorro & Florian Ielpo & Benoît Sévi, 2020. "The contribution of intraday jumps to forecasting the density of returns," Post-Print halshs-02505861, HAL.
    8. Filip Žikeš & Jozef Baruník, 2016. "Semi-parametric Conditional Quantile Models for Financial Returns and Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 14(1), pages 185-226.
    9. Fabrizio Cipollini & Giampiero M. Gallo & Edoardo Otranto, 2019. "Realized Volatility Forecasting: Robustness to Measurement Errors," Econometrics Working Papers Archive 2019_04, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    10. Matteo Luciani & David Veredas, 2012. "A model for vast panels of volatilities," Working Papers 1230, Banco de España.
    11. Cubadda, Gianluca & Guardabascio, Barbara & Hecq, Alain, 2017. "A vector heterogeneous autoregressive index model for realized volatility measures," International Journal of Forecasting, Elsevier, vol. 33(2), pages 337-344.
    12. Rossi, Eduardo & Santucci de Magistris, Paolo, 2013. "Long memory and tail dependence in trading volume and volatility," Journal of Empirical Finance, Elsevier, vol. 22(C), pages 94-112.
    13. B. Zhang & J. Wang & W. Zhang & G. C. Wang, 2020. "Nonlinear Scaling Behavior of Visible Volatility Duration for Financial Statistical Physics Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 373-389, August.
    14. Chevallier, Julien & Sévi, Benoît, 2012. "On the volatility–volume relationship in energy futures markets using intraday data," Energy Economics, Elsevier, vol. 34(6), pages 1896-1909.
    15. Caporin, Massimiliano & Ranaldo, Angelo & Velo, Gabriel G., 2014. "Precious Metals Under the Microscope: A High-Frequency Analysis," Working Papers on Finance 1409, University of St. Gallen, School of Finance.
    16. Catania, Leopoldo & Proietti, Tommaso, 2020. "Forecasting volatility with time-varying leverage and volatility of volatility effects," International Journal of Forecasting, Elsevier, vol. 36(4), pages 1301-1317.
    17. Lazar, Emese & Xue, Xiaohan, 2020. "Forecasting risk measures using intraday data in a generalized autoregressive score framework," International Journal of Forecasting, Elsevier, vol. 36(3), pages 1057-1072.
    18. Massimiliano Caporin & Gabriel G. Velo, 2011. "Modeling and forecasting realized range volatility," "Marco Fanno" Working Papers 0128, Dipartimento di Scienze Economiche "Marco Fanno".
    19. Zheng, Tingguo & Zuo, Haomiao, 2013. "Reexamining the time-varying volatility spillover effects: A Markov switching causality approach," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 643-662.
    20. Isao Ishida & Toshiaki Watanabe, 2009. "Modeling and Forecasting the Volatility of the Nikkei 225 Realized Volatility Using the ARFIMA-GARCH Model," CARF F-Series CARF-F-145, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo.
    21. Hadhri, Sinda & Ftiti, Zied, 2019. "Commonality in liquidity among Middle East and North Africa emerging stock markets: Does it really matter?," Economic Systems, Elsevier, vol. 43(3).
    22. Fengler, Matthias R. & Okhrin, Ostap, 2016. "Managing risk with a realized copula parameter," Computational Statistics & Data Analysis, Elsevier, vol. 100(C), pages 131-152.
    23. Evzen Kocenda & Vit Bubak & Filip Zikes, 2011. "Volatility Transmission in Emerging European Foreign Exchange Markets," William Davidson Institute Working Papers Series wp1020, William Davidson Institute at the University of Michigan.
    24. Clements, Michael P. & Galvão, Ana Beatriz & Kim, Jae H., 2006. "Quantile Forecasts of Daily Exchange Rate Returns from Forecasts of Realized Volatility," The Warwick Economics Research Paper Series (TWERPS) 777, University of Warwick, Department of Economics.
    25. Wen Cheong Chin & Min Cherng Lee, 2018. "S&P500 volatility analysis using high-frequency multipower variation volatility proxies," Empirical Economics, Springer, vol. 54(3), pages 1297-1318, May.
    26. Gustavo Fruet Dias & Karsten Schweiker, 2024. "Integrated Variance Estimation for Assets Traded in Multiple Venues," University of East Anglia School of Economics Working Paper Series 2024-04, School of Economics, University of East Anglia, Norwich, UK..
    27. David E. Allen & Michael McAleer & Marcel Scharth, 2010. "Realized Volatility Risk," KIER Working Papers 753, Kyoto University, Institute of Economic Research.
    28. Ait-Sahalia, Yacine & Mykland, Per A. & Zhang, Lan, 2005. "Ultra high frequency volatility estimation with dependent microstructure noise," Discussion Paper Series 1: Economic Studies 2005,30, Deutsche Bundesbank.
    29. Štefan Lyócsa & Peter Molnár, 2016. "Volatility forecasting of strategically linked commodity ETFs: gold-silver," Quantitative Finance, Taylor & Francis Journals, vol. 16(12), pages 1809-1822, December.
    30. David E. Allen & Michael McAleer & Marcel Scharth, 2014. "Asymmetric Realized Volatility Risk," Tinbergen Institute Discussion Papers 14-075/III, Tinbergen Institute.
    31. Oleg Sokolinskiy & Dick van Dijk, 2011. "Forecasting Volatility with Copula-Based Time Series Models," Tinbergen Institute Discussion Papers 11-125/4, Tinbergen Institute.
    32. Ding, Yashuang (Dexter), 2023. "A simple joint model for returns, volatility and volatility of volatility," Journal of Econometrics, Elsevier, vol. 232(2), pages 521-543.
    33. Weber, Enzo, 2013. "Simultaneous stochastic volatility transmission across American equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(1), pages 53-60.
    34. Tian, Fengping & Yang, Ke & Chen, Langnan, 2017. "Realized volatility forecasting of agricultural commodity futures using the HAR model with time-varying sparsity," International Journal of Forecasting, Elsevier, vol. 33(1), pages 132-152.
    35. Aitor Ciarreta & Peru Muniain & Ainhoa Zarraga, 2020. "Realized volatility and jump testing in the Japanese electricity spot market," Empirical Economics, Springer, vol. 58(3), pages 1143-1166, March.
    36. Xiangjin B. Chen & Jiti Gao & Degui Li & Param Silvapulle, 2013. "Nonparametric Estimation and Parametric Calibration of Time-Varying Coefficient Realized Volatility Models," Monash Econometrics and Business Statistics Working Papers 21/13, Monash University, Department of Econometrics and Business Statistics.
    37. Jeremy Large, 2007. "Estimating Quadratic Variation When Quoted Prices Change by a Constant Increment," Economics Series Working Papers 340, University of Oxford, Department of Economics.
    38. Fulvio Corsi, 2009. "A Simple Approximate Long-Memory Model of Realized Volatility," Journal of Financial Econometrics, Oxford University Press, vol. 7(2), pages 174-196, Spring.
    39. Ma, Feng & Liu, Jing & Huang, Dengshi & Chen, Wang, 2017. "Forecasting the oil futures price volatility: A new approach," Economic Modelling, Elsevier, vol. 64(C), pages 560-566.
    40. Fulvio Corsi & Francesco Audrino, 2012. "Realized Covariance Tick-by-Tick in Presence of Rounded Time Stamps and General Microstructure Effects," Journal of Financial Econometrics, Oxford University Press, vol. 10(4), pages 591-616, September.
    41. Lyócsa, Štefan & Molnár, Peter & Todorova, Neda, 2017. "Volatility forecasting of non-ferrous metal futures: Covariances, covariates or combinations?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 51(C), pages 228-247.
    42. Allen, David & Lazarov, Zdravetz & McAleer, Michael & Peiris, Shelton, 2009. "Comparison of alternative ACD models via density and interval forecasts: Evidence from the Australian stock market," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 79(8), pages 2535-2555.
    43. Yanhui Chen & Kin Lai & Jiangze Du, 2014. "Modeling and forecasting Hang Seng index volatility with day-of-week effect, spillover effect based on ARIMA and HAR," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 4(2), pages 113-132, December.
    44. Ying Chen & Wolfgang Härdle & Uta Pigorsch, 2009. "Localized Realized Volatility Modelling," SFB 649 Discussion Papers SFB649DP2009-003, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    45. Hwang, Eunju & Shin, Dong Wan, 2014. "Infinite-order, long-memory heterogeneous autoregressive models," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 339-358.
    46. D. Delpini & G. Bormetti, 2015. "Stochastic volatility with heterogeneous time scales," Quantitative Finance, Taylor & Francis Journals, vol. 15(10), pages 1597-1608, October.
    47. Ahoniemi, Katja & Lanne, Markku, 2010. "Realized volatility and overnight returns," Bank of Finland Research Discussion Papers 19/2010, Bank of Finland.
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    184. Wang, Xunxiao & Wu, Chongfeng & Xu, Weidong, 2015. "Volatility forecasting: The role of lunch-break returns, overnight returns, trading volume and leverage effects," International Journal of Forecasting, Elsevier, vol. 31(3), pages 609-619.
    185. Chun Liu & John M Maheu, 2010. "Intraday Dynamics of Volatility and Duration: Evidence from the Chinese Stock Market," Working Papers tecipa-401, University of Toronto, Department of Economics.
    186. Todorova, Neda & Souček, Michael, 2014. "Overnight information flow and realized volatility forecasting," Finance Research Letters, Elsevier, vol. 11(4), pages 420-428.
    187. Todorova, Neda, 2015. "The course of realized volatility in the LME non-ferrous metal market," Economic Modelling, Elsevier, vol. 51(C), pages 1-12.
    188. 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.
    189. Ke Yang & Langnan Chen, 2014. "Realized Volatility Forecast: Structural Breaks, Long Memory, Asymmetry, and Day-of-the-Week Effect," International Review of Finance, International Review of Finance Ltd., vol. 14(3), pages 345-392, September.
    190. Xuan Yao & Xiaofeng Hui & Kaican Kang, 2021. "Can night trading sessions improve forecasting performance of gold futures' volatility in China?," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(5), pages 849-860, August.
    191. Vít Bubák & Filip Žikeš, 2009. "Distribution and Dynamics of Central-European Exchange Rates: Evidence from Intraday Data," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 59(4), pages 334-359, Oktober.
    192. Ding, Yi & Kambouroudis, Dimos & McMillan, David G., 2021. "Forecasting realised volatility: Does the LASSO approach outperform HAR?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
    193. Nicholas Taylor, 2015. "Realized volatility forecasting in an international context," Applied Economics Letters, Taylor & Francis Journals, vol. 22(6), pages 503-509, April.
    194. Dimitrios P. Louzis & Spyros Xanthopoulos - Sissinis & Apostolos P. Refenes, 2012. "Stock index Value-at-Risk forecasting: A realized volatility extreme value theory approach," Economics Bulletin, AccessEcon, vol. 32(1), pages 981-991.
    195. Philip L. H. Yu & W. K. Li & F. C. Ng, 2017. "The Generalized Conditional Autoregressive Wishart Model for Multivariate Realized Volatility," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 513-527, October.
    196. Jonathan R. Stroud & Michael S. Johannes, 2014. "Bayesian Modeling and Forecasting of 24-Hour High-Frequency Volatility," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(508), pages 1368-1384, December.
    197. Ahoniemi, Katja & Lanne, Markku, 2013. "Overnight stock returns and realized volatility," International Journal of Forecasting, Elsevier, vol. 29(4), pages 592-604.
    198. Naimoli, Antonio & Gerlach, Richard & Storti, Giuseppe, 2022. "Improving the accuracy of tail risk forecasting models by combining several realized volatility estimators," Economic Modelling, Elsevier, vol. 107(C).
    199. Dimitrios Louzis & Spyros Xanthopoulos-Sisinis & Apostolos Refenes, 2011. "Stock index realized volatility forecasting in the presence of heterogeneous leverage effects and long range dependence in the volatility of realized volatility," Post-Print hal-00709559, HAL.
    200. Luo, Jiawen & Wang, Shengquan, 2019. "The asymmetric high-frequency volatility transmission across international stock markets," Finance Research Letters, Elsevier, vol. 31(C), pages 104-109.
    201. Heinen, Florian & Willert, Juliane, 2011. "Monitoring a change in persistence of a long range dependent time series," Hannover Economic Papers (HEP) dp-479, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
    202. Fulvio Corsi & Francesco Audrino, 2007. "Realized Correlation Tick-by-Tick," University of St. Gallen Department of Economics working paper series 2007 2007-02, Department of Economics, University of St. Gallen.
    203. Mykland, Per A. & Zhang, Lan, 2016. "Between data cleaning and inference: Pre-averaging and robust estimators of the efficient price," Journal of Econometrics, Elsevier, vol. 194(2), pages 242-262.
    204. Dimitrios Vortelinos & Dimitrios Thomakos, 2009. "Realized Volatility and Jumps in the Athens Stock Exchange," Working Papers 00044, University of Peloponnese, Department of Economics.
    205. Eric. W. K. See-To & Yang Yang, 2017. "Market sentiment dispersion and its effects on stock return and volatility," Electronic Markets, Springer;IIM University of St. Gallen, vol. 27(3), pages 283-296, August.
    206. Xin Du & Kai Moriyama & Kumiko Tanaka-Ishii, 2023. "Co-Training Realized Volatility Prediction Model with Neural Distributional Transformation," Papers 2310.14536, arXiv.org.
    207. Mike Buckle & Jing Chen & Julian Williams, 2014. "How Predictable Are Equity Covariance Matrices? Evidence from High‐Frequency Data for Four Markets," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 33(7), pages 542-557, November.
    208. Chen, Zhonglu & Liang, Chao & Umar, Muhammad, 2021. "Is investor sentiment stronger than VIX and uncertainty indices in predicting energy volatility?," Resources Policy, Elsevier, vol. 74(C).
    209. Wang, Jianxin, 2013. "Liquidity commonality among Asian equity markets," Pacific-Basin Finance Journal, Elsevier, vol. 21(1), pages 1209-1231.
    210. Czado, Claudia & Ivanov, Eugen & Okhrin, Yarema, 2019. "Modelling temporal dependence of realized variances with vines," Econometrics and Statistics, Elsevier, vol. 12(C), pages 198-216.
    211. Xiangjin B. Chen & Jiti Gao & Degui Li & Param Silvapulle, 2018. "Nonparametric Estimation and Forecasting for Time-Varying Coefficient Realized Volatility Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 36(1), pages 88-100, January.
    212. Danyan Wen & Mengxi He & Yaojie Zhang & Yudong Wang, 2022. "Forecasting realized volatility of Chinese stock market: A simple but efficient truncated approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 230-251, March.
    213. Guglielmo Maria Caporale & Menelaos Karanasos & Stavroula Yfanti, 2019. "Macro-Financial Linkages in the High-Frequency Domain: The Effects of Uncertainty on Realized Volatility," CESifo Working Paper Series 8000, CESifo.
    214. Massimiliano Frezza & Sergio Bianchi & Augusto Pianese, 2022. "Forecasting Value-at-Risk in turbulent stock markets via the local regularity of the price process," Computational Management Science, Springer, vol. 19(1), pages 99-132, January.
    215. Haugom, Erik & Westgaard, Sjur & Solibakke, Per Bjarte & Lien, Gudbrand, 2011. "Realized volatility and the influence of market measures on predictability: Analysis of Nord Pool forward electricity data," Energy Economics, Elsevier, vol. 33(6), pages 1206-1215.
    216. Barbaglia, Luca & Croux, Christophe & Wilms, Ines, 2020. "Volatility spillovers in commodity markets: A large t-vector autoregressive approach," Energy Economics, Elsevier, vol. 85(C).
    217. Wang, Yudong & Ma, Feng & Wei, Yu & Wu, Chongfeng, 2016. "Forecasting realized volatility in a changing world: A dynamic model averaging approach," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 136-149.

  28. Stefan Mittnik & Peter A. Zadrozny, 2004. "Forecasting Quarterly German GDP at Monthly Intervals Using Monthly IFO Business Conditions Data," CESifo Working Paper Series 1203, CESifo.

    Cited by:

    1. Qian, Hang, 2012. "Essays on statistical inference with imperfectly observed data," ISU General Staff Papers 201201010800003618, Iowa State University, Department of Economics.
    2. Elena Andreou & Eric Ghysels & Andros Kourtellos, 2010. "Should macroeconomic forecasters use daily financial data and how?," University of Cyprus Working Papers in Economics 09-2010, University of Cyprus Department of Economics.
    3. Cecilia Frale & Libero Monteforte, "undated". "FaMIDAS: A Mixed Frequency Factor Model with MIDAS structure," Working Papers 3, Department of the Treasury, Ministry of the Economy and of Finance.
    4. Kholodilin Konstantin Arkadievich & Siliverstovs Boriss, 2006. "On the Forecasting Properties of the Alternative Leading Indicators for the German GDP: Recent Evidence," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 226(3), pages 234-259, June.
    5. Reichlin, Lucrezia & Giannone, Domenico & Modugno, Michele & Banbura, Marta, 2012. "Now-casting and the real-time data flow," CEPR Discussion Papers 9112, C.E.P.R. Discussion Papers.
    6. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.
    7. Michael W. McCracken & Michael T. Owyang & Tatevik Sekhposyan, 2021. "Real-Time Forecasting and Scenario Analysis Using a Large Mixed-Frequency Bayesian VAR," International Journal of Central Banking, International Journal of Central Banking, vol. 17(71), pages 1-41, December.
    8. Klaus Abberger & Gebhard Flaig & Wolfgang Nierhaus, 2007. "ifo Konjunkturumfragen und Konjunkturanalyse : ausgewählte methodische Aufsätze aus dem ifo Schnelldienst," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 33.
    9. Konstantin A. Kholodilin & Boriss Siliverstovs & Stefan Kooths, 2007. "A Dynamic Panel Data Approach to the Forecasting of the GDP of German Länder," Discussion Papers of DIW Berlin 664, DIW Berlin, German Institute for Economic Research.
    10. Klaus Abberger, 2007. "Forecasting Quarter-on-Quarter Changes of German GDP with Monthly Business Tendency Survey Results," ifo Working Paper Series 40, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    11. 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.
    12. Oscar Claveria & Enric Monte & Salvador Torra, 2017. "“Let the data do the talking: Empirical modelling of survey-based expectations by means of genetic programming”," AQR Working Papers 201706, University of Barcelona, Regional Quantitative Analysis Group, revised May 2017.
    13. Seong, Byeongchan, 2020. "Smoothing and forecasting mixed-frequency time series with vector exponential smoothing models," Economic Modelling, Elsevier, vol. 91(C), pages 463-468.
    14. Byeongchan Seong & Sung K. Ahn & Peter Zadrozny, 2007. "Cointegration Analysis with Mixed-Frequency Data," CESifo Working Paper Series 1939, CESifo.
    15. Lenza, Michele & Cimadomo, Jacopo & Giannone, Domenico & Monti, Francesca & Sokol, Andrej, 2021. "Nowcasting with Large Bayesian Vector Autoregressions," CEPR Discussion Papers 15854, C.E.P.R. Discussion Papers.
    16. Klaus Abberger, 2005. "Qualitative Business Surveys and the Assessment of Employment A Case Study for Germany," ifo Working Paper Series 11, ifo Institute - Leibniz Institute for Economic Research at the University of Munich.
    17. Qian, Hang, 2012. "A Flexible State Space Model and its Applications," MPRA Paper 38455, University Library of Munich, Germany.
    18. Oscar Claveria & Enric Monte & Salvador Torra, 2019. "Empirical modelling of survey-based expectations for the design of economic indicators in five European regions," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 46(2), pages 205-227, May.
    19. Wolfgang Nierhaus & Timo Wollmershäuser, 2016. "ifo Konjunkturumfragen und Konjunkturanalyse: Band II," ifo Forschungsberichte, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 72.
    20. Schumacher, Christian & Marcellino, Massimiliano & Kuzin, Vladimir, 2009. "MIDAS vs. mixed-frequency VAR: Nowcasting GDP in the Euro Area," CEPR Discussion Papers 7445, C.E.P.R. Discussion Papers.
    21. Gani Ramadani & Magdalena Petrovska & Vesna Bucevska, 2021. "Evaluation of mixed frequency approaches for tracking near-term economic developments in North Macedonia," Working Papers 2021-03, National Bank of the Republic of North Macedonia.
    22. Klaus Wohlrabe, 2009. "Macroeconomic forecasting with mixed frequencies," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(21), pages 22-33, November.
    23. Heinisch Katja & Scheufele Rolf, 2019. "Should Forecasters Use Real-Time Data to Evaluate Leading Indicator Models for GDP Prediction? German Evidence," German Economic Review, De Gruyter, vol. 20(4), pages 170-200, December.
    24. Ramadani Gani & Petrovska Magdalena & Bucevska Vesna, 2021. "Evaluation of Mixed Frequency Approaches for Tracking Near-Term Economic Developments in North Macedonia," South East European Journal of Economics and Business, Sciendo, vol. 16(2), pages 43-52, December.
    25. Ghysels, Eric, 2016. "Macroeconomics and the reality of mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 294-314.
    26. Kuzin, Vladimir N. & Marcellino, Massimiliano & Schumacher, Christian, 2009. "MIDAS versus mixed-frequency VAR: nowcasting GDP in the euro area," Discussion Paper Series 1: Economic Studies 2009,07, Deutsche Bundesbank.
    27. Blasques, F. & Koopman, S.J. & Mallee, M. & Zhang, Z., 2016. "Weighted maximum likelihood for dynamic factor analysis and forecasting with mixed frequency data," Journal of Econometrics, Elsevier, vol. 193(2), pages 405-417.
    28. Cecilia Frale, Serena Teobaldo, Marco Cacciotti, Alessandra Caretta, 2013. "A Quarterly Measure Of Potential Output In The New European Fiscal Framework," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 67(2), pages 181-197, April-Jun.
    29. Kai Carstensen & Steffen Henzel & Johannes Mayr & Klaus Wohlrabe, 2009. "IFOCAST: Methods of the Ifo short-term forecast," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 62(23), pages 15-28, December.
    30. Sieds, 2013. "Complete Volume LXVII n.2 2013," RIEDS - Rivista Italiana di Economia, Demografia e Statistica - The Italian Journal of Economic, Demographic and Statistical Studies, SIEDS Societa' Italiana di Economia Demografia e Statistica, vol. 67(2), pages 1-197, April-Jun.
    31. Anna Sophia Ciesielski & Klaus Wohlrabe, 2011. "Sector-based Forecasts in Manufacturing," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 64(22), pages 27-35, November.
    32. Franco, Ray John Gabriel & Mapa, Dennis S., 2014. "The Dynamics of Inflation and GDP Growth: A Mixed Frequency Model Approach," MPRA Paper 55858, University Library of Munich, Germany.
    33. 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.
    34. Bjørn Eraker & Ching Wai (Jeremy) Chiu & Andrew T. Foerster & Tae Bong Kim & Hernán D. Seoane, 2015. "Bayesian Mixed Frequency VARs," Journal of Financial Econometrics, Oxford University Press, vol. 13(3), pages 698-721.
    35. Qian, Hang, 2013. "Vector Autoregression with Mixed Frequency Data," MPRA Paper 47856, University Library of Munich, Germany.
    36. 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.
    37. Ojogho, Osaihiomwan & Egware, Robert Awotu, 2015. "Price Generating Process And Volatility In Nigerian Agricultural Commodities Market," International Journal of Food and Agricultural Economics (IJFAEC), Alanya Alaaddin Keykubat University, Department of Economics and Finance, vol. 3(4), pages 1-10, October.
    38. Schumacher, Christian & Breitung, Jörg, 2008. "Real-time forecasting of German GDP based on a large factor model with monthly and quarterly data," International Journal of Forecasting, Elsevier, vol. 24(3), pages 386-398.
    39. Heinisch, Katja, 2016. "A real-time analysis on the importance of hard and soft data for nowcasting German GDP," VfS Annual Conference 2016 (Augsburg): Demographic Change 145864, Verein für Socialpolitik / German Economic Association.
    40. Daniel Roash & Tanya Suhoy, 2019. "Sentiment Indicators Based on a Short Business Tendency Survey," Bank of Israel Working Papers 2019.11, Bank of Israel.
    41. Neville Francis & Eric Ghysels & Michael T. Owyang, 2011. "The low-frequency impact of daily monetary policy shocks," Working Papers 2011-009, Federal Reserve Bank of St. Louis.
    42. Klaus Abberger & Klaus Wohlrabe, 2006. "Forecasting qualities of the Ifo Business Climate Index - a look at recent studies," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 59(22), pages 19-26, November.
    43. Neville Francis, 2012. "The Low-Frequency Impact of Daily Monetary Policy Shock," 2012 Meeting Papers 198, Society for Economic Dynamics.
    44. Chen, Pu, 2009. "A Note on Updating Forecasts When New Information Arrives between Two Periods," Economics Discussion Papers 2009-22, Kiel Institute for the World Economy (IfW Kiel).
    45. Vermeulen, Philip, 2014. "An evaluation of business survey indices for short-term forecasting: Balance method versus Carlson–Parkin method," International Journal of Forecasting, Elsevier, vol. 30(4), pages 882-897.

  29. Mittnik, Stefan & Paolella, Marc S., 2003. "Prediction of Financial Downside-Risk with Heavy-Tailed Conditional Distributions," CFS Working Paper Series 2003/04, Center for Financial Studies (CFS).

    Cited by:

    1. 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.
    2. Paolella, Marc S. & Taschini, Luca, 2008. "An econometric analysis of emission allowance prices," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2022-2032, October.
    3. Sung Ik Kim, 2022. "ARMA–GARCH model with fractional generalized hyperbolic innovations," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    4. Stoyanov, Stoyan V. & Rachev, Svetlozar T. & Fabozzi, Frank J., 2011. "CVaR sensitivity with respect to tail thickness," Working Paper Series in Economics 29, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    5. Vacca, Gianmarco & Zoia, Maria Grazia & Bagnato, Luca, 2022. "Forecasting in GARCH models with polynomially modified innovations," International Journal of Forecasting, Elsevier, vol. 38(1), pages 117-141.
    6. José Curto & José Pinto & Gonçalo Tavares, 2009. "Modeling stock markets’ volatility using GARCH models with Normal, Student’s t and stable Paretian distributions," Statistical Papers, Springer, vol. 50(2), pages 311-321, March.
    7. Mittnik, Stefan & Paolella, Marc S. & Rachev, Svetlozar T., 2002. "Stationarity of stable power-GARCH processes," Journal of Econometrics, Elsevier, vol. 106(1), pages 97-107, January.
    8. Broda, Simon A. & Haas, Markus & Krause, Jochen & Paolella, Marc S. & Steude, Sven C., 2013. "Stable mixture GARCH models," Journal of Econometrics, Elsevier, vol. 172(2), pages 292-306.
    9. Lampros Kalyvas & Athanasios Sfetsos, 2006. "Does The Application Of Innovative Internal Models Diminish Regulatory Capital?," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 9(02), pages 217-226.
    10. Fausto Pacicco & Luigi Vena & Andrea Venegoni, 2017. "Full disclosure and financial stability: how does the market digest the transparency shock?," LIUC Papers in Economics 305, Cattaneo University (LIUC).
    11. ZHU, Dongming & ZINDE-WALSH, Victoria, 2007. "Properties and Estimation of Asymmetric Exponential Power Distribution," Cahiers de recherche 13-2007, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
    12. John Galbraith & Dongming Zhu, 2009. "Forecasting Expected Shortfall With A Generalized Asymmetric Student-T Distribution," Departmental Working Papers 2009-01, McGill University, Department of Economics.
    13. Xing Yu, 2012. "The optimal portfolio model based on multivariate t distribution with linear weighted sum method," E3 Journal of Business Management and Economics., E3 Journals, vol. 3(1), pages 044-047.
    14. Klar, B. & Lindner, F. & Meintanis, S.G., 2012. "Specification tests for the error distribution in GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3587-3598.
    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. Dongming Zhu & John W. Galbraith, 2009. "A Generalized Asymmetric Student-t Distribution with Application to Financial Econometrics," CIRANO Working Papers 2009s-13, CIRANO.
    17. Calzolari, Giorgio & Halbleib, Roxana, 2018. "Estimating stable latent factor models by indirect inference," Journal of Econometrics, Elsevier, vol. 205(1), pages 280-301.
    18. Pacicco, Fausto & Vena, Luigi & Venegoni, Andrea, 2020. "Communication and financial supervision: How does disclosure affect market stability?," Journal of Empirical Finance, Elsevier, vol. 57(C), pages 1-15.
    19. Marc S. Paolella, 2016. "Stable-GARCH Models for Financial Returns: Fast Estimation and Tests for Stability," Econometrics, MDPI, vol. 4(2), pages 1-28, May.
    20. 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.
    21. Bentes, Sónia R., 2014. "Measuring persistence in stock market volatility using the FIGARCH approach," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 408(C), pages 190-197.
    22. Slim, Skander & Koubaa, Yosra & BenSaïda, Ahmed, 2017. "Value-at-Risk under Lévy GARCH models: Evidence from global stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 30-53.
    23. Zhu, Dongming & Galbraith, John W., 2011. "Modeling and forecasting expected shortfall with the generalized asymmetric Student-t and asymmetric exponential power distributions," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 765-778, September.

  30. Claessen, Holger & Mittnik, Stefan, 2002. "Forecasting stock market volatility and the informational efficiency of the DAX-index options market," CFS Working Paper Series 2002/04, Center for Financial Studies (CFS).

    Cited by:

    1. Leonardo Quero Virla, 2023. "An empirical characterization of volatility in the German stock market," SN Business & Economics, Springer, vol. 3(7), pages 1-19, July.
    2. Haas, Markus & Mittnik, Stefan & Mizrach, Bruce, 2005. "Assessing central bank credibility during the EMS crises: Comparing option and spot market-based forecasts," CFS Working Paper Series 2005/09, Center for Financial Studies (CFS).
    3. Peng, Qing & Li, Jie & Zhao, Yu & Wu, Han, 2021. "The informational content of implied volatility: Application to the USD/JPY exchange rates," Journal of Asian Economics, Elsevier, vol. 76(C).
    4. Mittnik, Stefan & Robinzonov, Nikolay & Spindler, Martin, 2015. "Stock market volatility: Identifying major drivers and the nature of their impact," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 1-14.
    5. GIOT, Pierre, 2003. "The information content of implied volatility indexes for forecasting volatility and market risk," LIDAM Discussion Papers CORE 2003027, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    6. Tanuj Nandan & Puja Agrawal, 2016. "Pricing Efficiency in CNX Nifty Index Options Using the Black–Scholes Model: A Comparative Study of Alternate Volatility Measures," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 10(2), pages 281-304, May.
    7. Wilkens, Sascha & Roder, Klaus, 2006. "The informational content of option-implied distributions: Evidence from the Eurex index and interest rate futures options market," Global Finance Journal, Elsevier, vol. 17(1), pages 50-74, September.
    8. Kaufmann Sylvia & Scheicher Martin, 2006. "A Switching ARCH Model for the German DAX Index," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 10(4), pages 1-37, December.
    9. Emmanouil Karakostas, 2023. "The Macroeconomic Determinants of the Stock Market Index Performance: The Case of DAX Index," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(3), pages 21-38.
    10. Wagner, Niklas & Szimayer, Alexander, 2004. "Local and spillover shocks in implied market volatility: evidence for the U.S. and Germany," Research in International Business and Finance, Elsevier, vol. 18(3), pages 237-251, September.
    11. Yu, Wayne W. & Lui, Evans C.K. & Wang, Jacqueline W., 2010. "The predictive power of the implied volatility of options traded OTC and on exchanges," Journal of Banking & Finance, Elsevier, vol. 34(1), pages 1-11, January.
    12. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2019. "Forecasting the KOSPI200 spot volatility using various volatility measures," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 514(C), pages 156-166.
    13. Imlak Shaikh & Puja Padhi, 2014. "The forecasting performance of implied volatility index: evidence from India VIX," Economic Change and Restructuring, Springer, vol. 47(4), pages 251-274, November.
    14. GIOT, Pierre, 2003. "The Asian financial crisis : the start of a regime switch in volatility," LIDAM Discussion Papers CORE 2003078, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Ewa Ratuszny, 2015. "Risk Modeling of Commodities using CAViaR Models, the Encompassing Method and the Combined Forecasts," Dynamic Econometric Models, Uniwersytet Mikolaja Kopernika, vol. 15, pages 129-156.
    16. Bruce Burton & Satish Kumar & Nitesh Pandey, 2020. "Twenty-five years of The European Journal of Finance (EJF): a retrospective analysis," The European Journal of Finance, Taylor & Francis Journals, vol. 26(18), pages 1817-1841, December.
    17. Chao Liang & Yi Zhang & Yaojie Zhang, 2022. "Forecasting the volatility of the German stock market: New evidence," Applied Economics, Taylor & Francis Journals, vol. 54(9), pages 1055-1070, February.
    18. Virla, Leonardo Quero, 2021. "An empirical characterization of volatility dynamics in the DAX," IPE Working Papers 167/2021, Berlin School of Economics and Law, Institute for International Political Economy (IPE).
    19. Chan, Chia-Ying & de Peretti, Christian & Qiao, Zhuo & Wong, Wing-Keung, 2012. "Empirical test of the efficiency of the UK covered warrants market: Stochastic dominance and likelihood ratio test approach," Journal of Empirical Finance, Elsevier, vol. 19(1), pages 162-174.
    20. André Schöne, 2010. "Zum Informationsgehalt der Volatilitätsindizes VDAX und VDAX-New der Deutsche Börse AG," Schmalenbach Journal of Business Research, Springer, vol. 62(6), pages 625-661, September.

  31. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2002. "Mixed normal conditional heteroskedasticity," CFS Working Paper Series 2002/10, Center for Financial Studies (CFS).

    Cited by:

    1. Wang, Yudong & Wu, Chongfeng, 2012. "Forecasting energy market volatility using GARCH models: Can multivariate models beat univariate models?," Energy Economics, Elsevier, vol. 34(6), pages 2167-2181.
    2. 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.
    3. Yang Minxian, 2011. "Volatility Feedback and Risk Premium in GARCH Models with Generalized Hyperbolic Distributions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(3), pages 1-21, May.
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Articles

  1. Cheng Peng & Young Shin Kim & Stefan Mittnik, 2022. "Portfolio Optimization on Multivariate Regime-Switching GARCH Model with Normal Tempered Stable Innovation," JRFM, MDPI, vol. 15(5), pages 1-23, May.
    See citations under working paper version above.
  2. Stefan Mittnik & Willi Semmler & Alexander Haider, 2020. "Climate Disaster Risks—Empirics and a Multi-Phase Dynamic Model," Econometrics, MDPI, vol. 8(3), pages 1-27, August.
    See citations under working paper version above.
  3. Stoyan V. Stoyanov & Svetlozar T. Rachev & Stefan Mittnik & Frank J. Fabozzi, 2019. "Pricing Derivatives In Hermite Markets," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 22(06), pages 1-27, September.
    See citations under working paper version above.
  4. Mittnik, Stefan & Semmler, Willi, 2018. "Overleveraging, Financial Fragility, And The Banking–Macro Link: Theory And Empirical Evidence," Macroeconomic Dynamics, Cambridge University Press, vol. 22(1), pages 4-32, January.
    See citations under working paper version above.
  5. 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.

    Cited by:

    1. Ernst, Ekkehard & Semmler, Willi & Haider, Alexander, 2016. "Debt deflation, financial market stress and regime change: Evidence from Europe using MRVAR," ZEW Discussion Papers 16-030, ZEW - Leibniz Centre for European Economic Research.
    2. Pu Chen & Willi Semmler, 2018. "Short and Long Effects of Productivity on Unemployment," Open Economies Review, Springer, vol. 29(4), pages 853-878, September.
    3. Ekkehard Ernst, 2019. "Finance and Jobs: How Financial Markets and Prudential Regulation Shape Unemployment Dynamics," JRFM, MDPI, vol. 12(1), pages 1-30, January.

  6. Mittnik, Stefan & Robinzonov, Nikolay & Spindler, Martin, 2015. "Stock market volatility: Identifying major drivers and the nature of their impact," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 1-14.

    Cited by:

    1. Kim Christensen & Mathias Siggaard & Bezirgen Veliyev, 2021. "A machine learning approach to volatility forecasting," CREATES Research Papers 2021-03, Department of Economics and Business Economics, Aarhus University.
    2. Dai, Zhifeng & Chang, Xiaoming, 2021. "Forecasting stock market volatility: Can the risk aversion measure exert an important role?," The North American Journal of Economics and Finance, Elsevier, vol. 58(C).
    3. Rangan Gupta & Jacobus Nel & Christian Pierdzioch, 2021. "Investor Confidence and Forecastability of US Stock Market Realized Volatility : Evidence from Machine Learning," Working Papers 202118, University of Pretoria, Department of Economics.
    4. Ballinari, Daniele & Audrino, Francesco & Sigrist, Fabio, 2022. "When does attention matter? The effect of investor attention on stock market volatility around news releases," International Review of Financial Analysis, Elsevier, vol. 82(C).
    5. Caporale, Guglielmo Maria & Kyriacou, Kyriacos & Spagnolo, Nicola, 2023. "Aggregate insider trading and stock market volatility in the UK," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).
    6. Zhu, Haibin & Bai, Lu & He, Lidan & Liu, Zhi, 2023. "Forecasting realized volatility with machine learning: Panel data perspective," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 251-271.
    7. Bai, Lan & Wei, Yu & Wei, Guiwu & Li, Xiafei & Zhang, Songyun, 2021. "Infectious disease pandemic and permanent volatility of international stock markets: A long-term perspective," Finance Research Letters, Elsevier, vol. 40(C).
    8. Fang, Libing & Yu, Honghai & Xiao, Wen, 2018. "Forecasting gold futures market volatility using macroeconomic variables in the United States," Economic Modelling, Elsevier, vol. 72(C), pages 249-259.
    9. Vo, Xuan Vinh, 2016. "Does institutional ownership increase stock return volatility? Evidence from Vietnam," International Review of Financial Analysis, Elsevier, vol. 45(C), pages 54-61.
    10. Torben G. Andersen & Rasmus T. Varneskov, 2021. "Consistent Inference for Predictive Regressions in Persistent Economic Systems," NBER Working Papers 28568, National Bureau of Economic Research, Inc.
    11. Liang, Chao & Ma, Feng & Li, Ziyang & Li, Yan, 2020. "Which types of commodity price information are more useful for predicting US stock market volatility?," Economic Modelling, Elsevier, vol. 93(C), pages 642-650.
    12. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
    13. Lu, Fei & Ma, Feng & Guo, Qiang, 2023. "Less is more? New evidence from stock market volatility predictability," International Review of Financial Analysis, Elsevier, vol. 89(C).
    14. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2020. "Economic indicators and stock market volatility in an emerging economy," Economic Systems, Elsevier, vol. 44(2).
    15. Theu Dinh & Stéphane Goutte & Khuong Nguyen & Thomas Walther, 2022. "Economic drivers of volatility and correlation in precious metal markets," Working Papers halshs-03672469, HAL.
    16. Thampanya, Natthinee & Wu, Junjie & Nasir, Muhammad Ali & Liu, Jia, 2020. "Fundamental and behavioural determinants of stock return volatility in ASEAN-5 countries," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 65(C).
    17. Risse, Marian & Ohl, Ludwig, 2017. "Using dynamic model averaging in state space representation with dynamic Occam’s window and applications to the stock and gold market," Journal of Empirical Finance, Elsevier, vol. 44(C), pages 158-176.
    18. Risse, Marian, 2019. "Combining wavelet decomposition with machine learning to forecast gold returns," International Journal of Forecasting, Elsevier, vol. 35(2), pages 601-615.
    19. Constandina Koki & Loukia Meligkotsidou & Ioannis Vrontos, 2020. "Forecasting under model uncertainty: Non‐homogeneous hidden Markov models with Pòlya‐Gamma data augmentation," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(4), pages 580-598, July.
    20. M. Karanasos & S. Yfanti & J. Hunter, 2022. "Emerging stock market volatility and economic fundamentals: the importance of US uncertainty spillovers, financial and health crises," Annals of Operations Research, Springer, vol. 313(2), pages 1077-1116, June.
    21. Liang, Chao & Luo, Qin & Li, Yan & Huynh, Luu Duc Toan, 2023. "Global financial stress index and long-term volatility forecast for international stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
    22. Emrich, Eike & Pierdzioch, Christian, 2015. "Public goods, private consumption, and human-capital formation: On the economics of volunteer labour supply," Working Papers of the European Institute for Socioeconomics 14, European Institute for Socioeconomics (EIS), Saarbrücken.
    23. Conrad, Christian & Glas, Alexander, 2018. "‘Déjà vol’ revisited: Survey forecasts of macroeconomic variables predict volatility in the cross-section of industry portfolios," Working Papers 0655, University of Heidelberg, Department of Economics.
    24. Li Liu & Yudong Wang, 2021. "Forecasting aggregate market volatility: The role of good and bad uncertainties," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(1), pages 40-61, January.
    25. Torben G. Andersen & Rasmus T. Varneskov, 2018. "Consistent Inference for Predictive Regressions in Persistent VAR Economies," CREATES Research Papers 2018-09, Department of Economics and Business Economics, Aarhus University.
    26. Ye Luo & Martin Spindler, 2017. "$L_2$Boosting for Economic Applications," Papers 1702.03244, arXiv.org.
    27. Caglayan, Mustafa Onur & Xue, Wenjun & Zhang, Liwen, 2020. "Global investigation on the country-level idiosyncratic volatility and its determinants," Journal of Empirical Finance, Elsevier, vol. 55(C), pages 143-160.
    28. Libo Yin, 2022. "The role of intermediary capital risk in predicting oil volatility," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 401-416, January.
    29. Souropanis, Ioannis & Vivian, Andrew, 2023. "Forecasting realized volatility with wavelet decomposition," Journal of Empirical Finance, Elsevier, vol. 74(C).
    30. Chao Liang & Yu Wei & Yaojie Zhang, 2020. "Is implied volatility more informative for forecasting realized volatility: An international perspective," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1253-1276, December.
    31. Emrich Eike & Pierdzioch Christian, 2016. "Public Goods, Private Consumption, and Human Capital: Using Boosted Regression Trees to Model Volunteer Labour Supply," Review of Economics, De Gruyter, vol. 67(3), pages 263-283, December.
    32. Jörg Döpke & Ulrich Fritsche & Christian Pierdzioch, 2015. "Predicting Recessions With Boosted Regression Trees," Working Papers 2015-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    33. Crimmel, Jeremy & Elyasiani, Elyas, 2021. "The association between financial market volatility and banking market structure," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 335-349.
    34. Asgharian, Hossein & Christiansen, Charlotte & Hou, Ai Jun, 2023. "The effect of uncertainty on stock market volatility and correlation," Journal of Banking & Finance, Elsevier, vol. 154(C).
    35. Amit K. Sinha, 2021. "The reliability of geometric Brownian motion forecasts of S&P500 index values," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1444-1462, December.
    36. Nan Hu & Jian Li & Alexis Meyer-Cirkel, 2019. "Completing the Market: Generating Shadow CDS Spreads by Machine Learning," IMF Working Papers 2019/292, International Monetary Fund.
    37. Albaity, Mohamed & Shah, Syed Faisal & Al-Tamimi, Hussein A.Hassan & Rahman, Mahfuzur & Thangavelu, Shanmugam, 2023. "Country risk and bank returns: Evidence from MENA countries," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).
    38. Jörg Döpke & Ulrich Fritsche & Christian Pierdzioch, 2015. "Predicting Recessions in Germany With Boosted Regression Trees," Macroeconomics and Finance Series 201505, University of Hamburg, Department of Socioeconomics.
    39. Audrino, Francesco & Sigrist, Fabio & Ballinari, Daniele, 2020. "The impact of sentiment and attention measures on stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 334-357.
    40. Feng He & Libo Yin, 2021. "Shocks to the equity capital ratio of financial intermediaries and the predictability of stock return volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(6), pages 945-962, September.

  7. Kim, Young Shin & Lee, Jaesung & Mittnik, Stefan & Park, Jiho, 2015. "Quanto option pricing in the presence of fat tails and asymmetric dependence," Journal of Econometrics, Elsevier, vol. 187(2), pages 512-520.

    Cited by:

    1. Young Shin Kim & Kum-Hwan Roh & Raphael Douady, 2020. "Tempered Stable Processes with Time Varying Exponential Tails," Papers 2006.07669, arXiv.org, revised Aug 2020.
    2. Lin, Lisha & Li, Yaqiong & Gao, Rui & Wu, Jianhong, 2021. "The numerical simulation of Quanto option prices using Bayesian statistical methods," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 567(C).
    3. Bošnjak Mile & Novak Ivan & Vlajčić Davor, 2021. "Market Efficiency of Euro Exchange Rates and Trading Strategies," Naše gospodarstvo/Our economy, Sciendo, vol. 67(2), pages 10-19, June.
    4. Gong, Xiaoli & Zhuang, Xintian, 2017. "American option valuation under time changed tempered stable Lévy processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 57-68.
    5. Young Shin Kim, 2022. "Portfolio optimization and marginal contribution to risk on multivariate normal tempered stable model," Annals of Operations Research, Springer, vol. 312(2), pages 853-881, May.
    6. Kurosaki, Tetsuo & Kim, Young Shin, 2022. "Cryptocurrency portfolio optimization with multivariate normal tempered stable processes and Foster-Hart risk," Finance Research Letters, Elsevier, vol. 45(C).
    7. Young Shin Kim, 2020. "Portfolio Optimization on the Dispersion Risk and the Asymmetric Tail Risk," Papers 2007.13972, arXiv.org, revised Sep 2020.
    8. Young Shin Kim, 2019. "Tempered stable process, first passage time, and path-dependent option pricing," Computational Management Science, Springer, vol. 16(1), pages 187-215, February.
    9. Tetsuo Kurosaki & Young Shin Kim, 2020. "Cryptocurrency portfolio optimization with multivariate normal tempered stable processes and Foster-Hart risk," Papers 2010.08900, arXiv.org.
    10. Holger Fink & Stefan Mittnik, 2021. "Quanto Pricing beyond Black–Scholes," JRFM, MDPI, vol. 14(3), pages 1-27, March.
    11. Chia-Lin Chang & Michael McAleer, 2014. "Econometric Analysis of Financial Derivatives: An Overview," Working Papers in Economics 14/29, University of Canterbury, Department of Economics and Finance.
    12. Kim, Sung Ik, 2023. "A comparative study of firm value models: Default risk of corporate bonds," Finance Research Letters, Elsevier, vol. 56(C).
    13. Tiantian Li & Young Shin Kim & Qi Fan & Fumin Zhu, 2021. "Aumann–Serrano index of risk in portfolio optimization," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 94(2), pages 197-217, October.
    14. Battauz, Anna & De Donno, Marzia & Sbuelz, Alessandro, 2022. "On the exercise of American quanto options," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    15. Chang, C-L. & McAleer, M.J., 2014. "Econometric Analysis of Financial Derivatives," Econometric Institute Research Papers EI 2015-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    16. Sung Ik Kim & Young Shin Kim, 2018. "Tempered stable structural model in pricing credit spread and credit default swap," Review of Derivatives Research, Springer, vol. 21(1), pages 119-148, April.
    17. Young Shin Kim & Hyun-Gyoon Kim, 2024. "Quanto Option Pricing on a Multivariate Levy Process Model with a Generative Artificial Intelligence," Papers 2402.17919, arXiv.org, revised Mar 2024.
    18. Hasan A. Fallahgoul & Young S. Kim & Frank J. Fabozzi & Jiho Park, 2019. "Quanto Option Pricing with Lévy Models," Computational Economics, Springer;Society for Computational Economics, vol. 53(3), pages 1279-1308, March.
    19. Lisha Lin & Yaqiong Li & Rui Gao & Jianhong Wu, 2019. "The Numerical Simulation of Quanto Option Prices Using Bayesian Statistical Methods," Papers 1910.04075, arXiv.org.
    20. Young Shin Kim, 2023. "Portfolio Optimization with Relative Tail Risk," Papers 2303.12209, arXiv.org, revised Mar 2023.
    21. Li, Zhe & Zhang, Wei-Guo & Liu, Yong-Jun, 2018. "European quanto option pricing in presence of liquidity risk," The North American Journal of Economics and Finance, Elsevier, vol. 45(C), pages 230-244.

  8. Mittnik, Stefan, 2014. "VaR-implied tail-correlation matrices," Economics Letters, Elsevier, vol. 122(1), pages 69-73.
    See citations under working paper version above.
  9. Stefan Mittnik & Nikolay Robinzonov & Klaus Wohlrabe, 2013. "What Moves the DAX?," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(23), pages 32-36, December.

    Cited by:

    1. Sauer,Stefan & Klaus Wohlrabe & Stefan Sauer, 2019. "CEO or Intern − Who Actually Answers the Questionnaires in the ifo Business Survey?," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 20(02), pages 29-31, July.
    2. Stefan Sauer & Klaus Wohlrabe, 2019. "Boss or Trainee – Who Actually Answers the Questionnaires in the ifo Business Surveys?," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 72(03), pages 30-32, February.
    3. Stefan Sauer & Klaus Wohlrabe, 2018. "The New ifo Business Climate Index for Germany," CESifo Forum, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 19(02), pages 59-64, July.

  10. Mittnik, Stefan & Semmler, Willi, 2013. "The real consequences of financial stress," Journal of Economic Dynamics and Control, Elsevier, vol. 37(8), pages 1479-1499.
    See citations under working paper version above.
  11. Mittnik, Stefan & Semmler, Willi, 2012. "Regime dependence of the fiscal multiplier," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 502-522.

    Cited by:

    1. Mario Alloza, 2017. "Is fiscal policy more effective in uncertain times or during recessions?," Working Papers 1730, Banco de España.
    2. Mittnik, Stefan & Semmler, Willi, 2013. "The real consequences of financial stress," Journal of Economic Dynamics and Control, Elsevier, vol. 37(8), pages 1479-1499.
    3. Julien Albertini & Stéphane Auray & Hafedh Bouakez & Aurélien Eyquem, 2019. "Taking off into the Wind: Unemployment Risk and State-Dependent Government Spending Multipliers," Post-Print halshs-02503455, HAL.
    4. Kim, Hyeongwoo, 2018. "Fiscal Policy, Wages, and Jobs in the U.S," MPRA Paper 89763, University Library of Munich, Germany.
    5. 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.
    6. Tommaso Ferraresi & Andrea Roventini & Willi Semmler, 2016. "Macroeconomic Regimes, Technological Shocks and Employment Dynamics," Sciences Po publications 2016-19, Sciences Po.
    7. Sims, Eric & Wolff, Jonathan, 2018. "The state-dependent effects of tax shocks," European Economic Review, Elsevier, vol. 107(C), pages 57-85.
    8. Giovanni Caggiano & Efrem Castelnuovo & Olivier Damette & Antoine Parent & Giovanni Pellegrino, 2017. "Liquidity traps and large-scale financial crises," Post-Print halshs-01675562, HAL.
    9. Yifei Lyu & Eul Noh, 2022. "Cyclical variation in US government spending multipliers," Economic Inquiry, Western Economic Association International, vol. 60(2), pages 831-846, April.
    10. Efrem Castelnuovo & Guay Lim, 2019. "What Do We Know About the Macroeconomic Effects of Fiscal Policy? A Brief Survey of the Literature on Fiscal Multipliers," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 52(1), pages 78-93, March.
    11. Kim, Hyeongwoo & Shao, Peng & Zhang, Shuwei, 2023. "Policy coordination and the effectiveness of fiscal stimulus," Journal of Macroeconomics, Elsevier, vol. 75(C).
    12. Julia M. Puaschunder, 2020. "Heterodox Economic Cycles Theories," Proceedings of the 20th International RAIS Conference, December 6-7, 2020 019jp, Research Association for Interdisciplinary Studies.
    13. Eduardo Garzón Espinosa & Bibiana Medialdea García & Esteban Cruz Hidalgo, 2021. "Fiscal Policy Approaches: An Inquiring Look From The Modern Monetary Theory," Journal of Economic Issues, Taylor & Francis Journals, vol. 55(4), pages 999-1022, October.
    14. Gustav A. Horn & Sebastian Gechert & Katja Rietzler & Kai D. Schmid, 2014. "Streitfall Fiskalpolitik," IMK Report 92-2014, IMK at the Hans Boeckler Foundation, Macroeconomic Policy Institute.
    15. Sofia São Marcos & Sofia Vale, 2024. "Is there a nonlinear relationship between public investment and private investment? Evidence from 21 Organization for Economic Cooperation and Development countries," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(1), pages 887-902, January.
    16. Christophe Blot & Marion Cochard & Jérôme Creel & Bruno Ducoudre & Danielle Schweisguth & Xavier Timbeau, 2014. "Fiscal consolidation in times of crisis: is the sooner really the better?," Sciences Po publications info:hdl:2441/2g7mhju69b9, Sciences Po.
    17. Bijie Jia & Hyeongwoo Kim, 2016. "Government Spending Shocks and Private Activity: The Role of Sentiments," Auburn Economics Working Paper Series auwp2016-04, Department of Economics, Auburn University.
    18. 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.
    19. Proaño, Christian R. & Schoder, Christian & Semmler, Willi, 2014. "Financial stress, sovereign debt and economic activity in industrialized countries: Evidence from dynamic threshold regressions," Journal of International Money and Finance, Elsevier, vol. 45(C), pages 17-37.
    20. Willi Semmler & Brigitte Young, 2017. "Re-Booting Europe: What kind of Fiscal Union - What kind of Social Union?," Working Papers 1713, New School for Social Research, Department of Economics.
    21. Kunzmann Vanessa, 2022. "Effects of Cross Country Fiscal Interdependence on Multipliers within a Monetary Union," Working Papers 216, Bavarian Graduate Program in Economics (BGPE).
    22. Semmler, Willi & Haider, Alexander, 2015. "The perils of debt deflation in the euro area: A multi regime model," ZEW Discussion Papers 15-071, ZEW - Leibniz Centre for European Economic Research.
    23. Samar Issa, 2020. "Life after Debt: The Effects of Overleveraging on Conventional and Islamic Banks," JRFM, MDPI, vol. 13(6), pages 1-46, June.
    24. 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.
    25. Mario Alloza, 2022. "Is Fiscal Policy More Effective During Recessions?," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(3), pages 1271-1292, August.
    26. Eric Sims & Jonathan Wolff, 2013. "The Output and Welfare Effects of Government Spending Shocks over the Business Cycle," NBER Working Papers 19749, National Bureau of Economic Research, Inc.
    27. Andrea Boitani & Salvatore Perdichizzi, 2018. "Public Expenditure Multipliers in recessions. Evidence from the Eurozone," DISCE - Working Papers del Dipartimento di Economia e Finanza def068, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    28. Gilles Dufrénot & Aurélia Jambois & Laurine Jambois & Guillaume Khayat, 2016. "Regime-Dependent Fiscal Multipliers in the United States," Post-Print hal-01447865, HAL.
    29. Bogdan Muraraşu & Cristina Anghelescu & Robert Adrian Grecu, 2023. "Assessing fiscal multipliers in times of crisis: evidence from selected CEE countries," Empirical Economics, Springer, vol. 65(4), pages 1627-1654, October.
    30. Mao, Jie & Shen, Guanxiong & Yan, Jingzhou, 2023. "A continuous-time macro-finance model with Knightian uncertainty," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).
    31. Ernst, Ekkehard & Semmler, Willi & Haider, Alexander, 2016. "Debt deflation, financial market stress and regime change: Evidence from Europe using MRVAR," ZEW Discussion Papers 16-030, ZEW - Leibniz Centre for European Economic Research.
    32. Choi, Sangyup & Shin, Junhyeok, 2023. "Household indebtedness and the macroeconomic effects of tax changes," Journal of Economic Behavior & Organization, Elsevier, vol. 209(C), pages 22-52.
    33. Steven Fazzari & James Morley & Irina Panovska, 2013. "State-Dependent Effects of Fiscal Policy," Discussion Papers 2012-27B, School of Economics, The University of New South Wales.
    34. Hyeongwoo Kim & Shuwei Zhang, 2019. "Understanding Why Fiscal Stimulus Can Fail through the Lens of the Survey of Professional Forecasters," Auburn Economics Working Paper Series auwp2019-06, Department of Economics, Auburn University.
    35. Mark Setterfield, 2015. "Time variation in the size of the multiplier: a Kalecki-Harrod approach," Working Papers 1522, New School for Social Research, Department of Economics, revised Jan 2017.
    36. Agata Szymańska, 2018. "Wpływ polityki fiskalnej na PKB w krajach Unii Europejskiej spoza strefy euro," Gospodarka Narodowa. The Polish Journal of Economics, Warsaw School of Economics, issue 3, pages 49-74.
    37. Schleer, Frauke & Semmler, Willi, 2013. "Financial sector-output dynamics in the euro area: Non-linearities reconsidered," ZEW Discussion Papers 13-068, ZEW - Leibniz Centre for European Economic Research.
    38. Demirel, Ufuk Devrim, 2021. "The short-term effects of tax changes: The role of state dependence," Journal of Monetary Economics, Elsevier, vol. 117(C), pages 918-934.
    39. Pu Chen & Willi Semmler, 2018. "Short and Long Effects of Productivity on Unemployment," Open Economies Review, Springer, vol. 29(4), pages 853-878, September.
    40. Piotr Krajewski & Agata Szymanska, 2019. "The effectiveness of fiscal policy within business cycle-Ricardians vs. non-Ricardians approach," Baltic Journal of Economics, Baltic International Centre for Economic Policy Studies, vol. 19(2), pages 195-215.
    41. Chacko George & Florian Kuhn, 2019. "Business Cycle Implications of Capacity Constraints under Demand Shocks," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 32, pages 94-121, April.
    42. António Afonso & Jaromír Baxa & Michal Slavík, 2011. "Fiscal developments and financial stress: a threshold VAR analysis," Working Papers IES 2011/16, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, revised Aug 2011.
    43. Jerow, Sam & Wolff, Jonathan, 2022. "Fiscal policy and uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 145(C).
    44. Hory, Marie-Pierre, 2016. "Fiscal multipliers in Emerging Market Economies: Can we learn something from Advanced Economies?," International Economics, Elsevier, vol. 146(C), pages 59-84.
    45. Steven Fazzari & James Morley & Irina Panovska, 2014. "State-Dependent Effects of Fiscal Policy," Discussion Papers 2012-27C, School of Economics, The University of New South Wales.
    46. Willi Semmler & Lucas Bernard, 2011. "Boom-Bust Cycles: Leveraging, Complex Securities, and Asset Prices," DEGIT Conference Papers c016_034, DEGIT, Dynamics, Economic Growth, and International Trade.
    47. Sylvérie Herbert, 2014. "Econometric analysis of regime switches and of fiscal multipliers," Documents de Travail de l'OFCE 2014-01, Observatoire Francais des Conjonctures Economiques (OFCE).
    48. Goldberg, Andrew & Romalis, John, 2015. "Public Debt and Growth in U.S. States," Working Papers 2015-10, University of Sydney, School of Economics.
    49. Salvatore Perdichizzi, 2017. "Estimating Fiscal multipliers in the Eurozone. A Nonlinear Panel Data Approach," DISCE - Working Papers del Dipartimento di Economia e Finanza def058, Università Cattolica del Sacro Cuore, Dipartimenti e Istituti di Scienze Economiche (DISCE).
    50. Samar Issa, 2022. "Financial Crises and Business Cycle Implications for Islamic and Non-Islamic Bank Lending in Indonesia," JRFM, MDPI, vol. 15(7), pages 1-32, June.
    51. Jerome Creel & Paul Hubert & Francesco Saraceno, 2012. "An assessment of Stability and Growth Pact Reform Proposals in a Small-Scale Macro Framework," Documents de Travail de l'OFCE 2012-04, Observatoire Francais des Conjonctures Economiques (OFCE).
    52. Kamalyan, Hayk, 2021. "Phase-Dependent Monetary and Fiscal Policy," MPRA Paper 110341, University Library of Munich, Germany.
    53. Barbu Cristian - Marian, 2017. "In Romania, the Buzzing Economy is Unable to Attenuate the Uproar Caused by Economic Backslides," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(2), pages 150-155, December.

  12. Stefan Mittnik & Irina Starobinskaya, 2010. "Modeling Dependencies in Operational Risk with Hybrid Bayesian Networks," Methodology and Computing in Applied Probability, Springer, vol. 12(3), pages 379-390, September.

    Cited by:

    1. Cornwell, Nikki & Bilson, Christopher & Gepp, Adrian & Stern, Steven & Vanstone, Bruce J., 2023. "Modernising operational risk management in financial institutions via data-driven causal factors analysis: A pre-registered report," Pacific-Basin Finance Journal, Elsevier, vol. 77(C).
    2. Garvey, Myles D. & Carnovale, Steven & Yeniyurt, Sengun, 2015. "An analytical framework for supply network risk propagation: A Bayesian network approach," European Journal of Operational Research, Elsevier, vol. 243(2), pages 618-627.
    3. Kaghazchi, Afsaneh & Hashemy Shahdany, S. Mehdy & Roozbahani, Abbas, 2021. "Simulation and evaluation of agricultural water distribution and delivery systems with a Hybrid Bayesian network model," Agricultural Water Management, Elsevier, vol. 245(C).
    4. Xu, Chi & Zheng, Chunling & Wang, Donghua & Ji, Jingru & Wang, Nuan, 2019. "Double correlation model for operational risk: Evidence from Chinese commercial banks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 516(C), pages 327-339.
    5. Yash Daultani & Mohit Goswami & Omkarprasad S. Vaidya & Sushil Kumar, 2019. "Inclusive risk modeling for manufacturing firms: a Bayesian network approach," Journal of Intelligent Manufacturing, Springer, vol. 30(8), pages 2789-2803, December.

  13. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2009. "Asymmetric multivariate normal mixture GARCH," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 2129-2154, April.
    See citations under working paper version above.
  14. Thiemo Krink & Stefan Mittnik & Sandra Paterlini, 2009. "Differential evolution and combinatorial search for constrained index-tracking," Annals of Operations Research, Springer, vol. 172(1), pages 153-176, November.
    See citations under working paper version above.
  15. Fulvio Corsi & Stefan Mittnik & Christian Pigorsch & Uta Pigorsch, 2008. "The Volatility of Realized Volatility," Econometric Reviews, Taylor & Francis Journals, vol. 27(1-3), pages 46-78.
    See citations under working paper version above.
  16. Toker Doganoglu & Christoph Hartz & Stefan Mittnik, 2007. "Portfolio optimization when risk factors are conditionally varying and heavy tailed," Computational Economics, Springer;Society for Computational Economics, vol. 29(3), pages 333-354, May.
    See citations under working paper version above.
  17. Haas, Markus & Mittnik, Stefan & Mizrach, Bruce, 2006. "Assessing central bank credibility during the ERM crises: Comparing option and spot market-based forecasts," Journal of Financial Stability, Elsevier, vol. 2(1), pages 28-54, April.
    See citations under working paper version above.
  18. Keith Kuester & Stefan Mittnik & Marc S. Paolella, 2006. "Value-at-Risk Prediction: A Comparison of Alternative Strategies," Journal of Financial Econometrics, Oxford University Press, vol. 4(1), pages 53-89.

    Cited by:

    1. Grigory Franguridi, 2014. "Higher order conditional moment dynamics and forecasting value-at-risk (in Russian)," Quantile, Quantile, issue 12, pages 69-82, February.
    2. Hammoudeh, S.M. & Malik, F. & McAleer, M.J., 2010. "Risk management of precious metals," Econometric Institute Research Papers EI 2010-48, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. Kulp-Tåg, Sofie, 2007. "An Empirical Investigation of Value-at-Risk in Long and Short Trading Positions," Working Papers 526, Hanken School of Economics.
    4. Wang, Guochang & Zhu, Ke & Li, Guodong & Li, Wai Keung, 2022. "Hybrid quantile estimation for asymmetric power GARCH models," Journal of Econometrics, Elsevier, vol. 227(1), pages 264-284.
    5. 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.
    6. Stavros Degiannakis & Pamela Dent & Christos Floros, 2014. "A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification," Manchester School, University of Manchester, vol. 82(1), pages 71-102, January.
    7. Alexander, Carol & Han, Yang & Meng, Xiaochun, 2023. "Static and dynamic models for multivariate distribution forecasts: Proper scoring rule tests of factor-quantile versus multivariate GARCH models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1078-1096.
    8. Gery Geenens & Richard Dunn, 2017. "A nonparametric copula approach to conditional Value-at-Risk," Papers 1712.05527, arXiv.org, revised Oct 2019.
    9. Asai, M. & McAleer, M.J. & Medeiros, M.C., 2010. "Asymmetry and Long Memory in Volatility Modelling," Econometric Institute Research Papers EI 2010-60, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    10. Berens, Tobias & Weiß, Gregor N.F. & Wied, Dominik, 2015. "Testing for structural breaks in correlations: Does it improve Value-at-Risk forecasting?," Journal of Empirical Finance, Elsevier, vol. 32(C), pages 135-152.
    11. Herrera, Rodrigo & González, Nicolás, 2014. "The modeling and forecasting of extreme events in electricity spot markets," International Journal of Forecasting, Elsevier, vol. 30(3), pages 477-490.
    12. Cathy W. S. Chen & Richard Gerlach & Bruce B. K. Hwang & Michael McAleer, 2011. "Forecasting Value-at-Risk Using Nonlinear Regression Quantiles and the Intra-day Range," KIER Working Papers 775, Kyoto University, Institute of Economic Research.
    13. Oliver Ledoit & Michael Wolf, 2008. "Robust Performance Hypothesis Testing with the Sharpe Ratio," IEW - Working Papers 320, Institute for Empirical Research in Economics - University of Zurich.
    14. Hamidi, Benjamin & Maillet, Bertrand & Prigent, Jean-Luc, 2014. "A dynamic autoregressive expectile for time-invariant portfolio protection strategies," Journal of Economic Dynamics and Control, Elsevier, vol. 46(C), pages 1-29.
    15. Fuertes, Ana-Maria & Olmo, Jose, 2013. "Optimally harnessing inter-day and intra-day information for daily value-at-risk prediction," International Journal of Forecasting, Elsevier, vol. 29(1), pages 28-42.
    16. Alex Huang, 2013. "Value at risk estimation by quantile regression and kernel estimator," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 225-251, August.
    17. Loriano Mancini & Fabio Trojani, 2011. "Robust Value at Risk Prediction," Journal of Financial Econometrics, Oxford University Press, vol. 9(2), pages 281-313, Spring.
    18. Olivier Ledoit & Michael Wolf, 2018. "Robust performance hypothesis testing with smooth functions of population moments," ECON - Working Papers 305, Department of Economics - University of Zurich.
    19. Marita Kuhlmann, 2022. "Eine empirische Analyse der Skalierung von Value-at-Risk Schaetzungen," Papers 2205.02123, arXiv.org.
    20. Del Brio, Esther B. & Mora-Valencia, Andrés & Perote, Javier, 2014. "VaR performance during the subprime and sovereign debt crises: An application to emerging markets," Emerging Markets Review, Elsevier, vol. 20(C), pages 23-41.
    21. Wentao Hu, 2019. "calculation worst-case Value-at-Risk prediction using empirical data under model uncertainty," Papers 1908.00982, arXiv.org.
    22. Stoyanov, Stoyan V. & Rachev, Svetlozar T. & Fabozzi, Frank J., 2011. "CVaR sensitivity with respect to tail thickness," Working Paper Series in Economics 29, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    23. Jimenez-Martin, Juan-Angel & McAleer, Michael & Pérez-Amaral, Teodosio & Santos, Paulo Araújo, 2013. "GFC-robust risk management under the Basel Accord using extreme value methodologies," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 94(C), pages 223-237.
    24. Fei, Fei & Fuertes, Ana-Maria & Kalotychou, Elena, 2017. "Dependence in credit default swap and equity markets: Dynamic copula with Markov-switching," International Journal of Forecasting, Elsevier, vol. 33(3), pages 662-678.
    25. Dimitrakopoulos, Dimitris N. & Kavussanos, Manolis G. & Spyrou, Spyros I., 2010. "Value at risk models for volatile emerging markets equity portfolios," The Quarterly Review of Economics and Finance, Elsevier, vol. 50(4), pages 515-526, November.
    26. Rui Zhou & Johnny Siu-Hang Li & Jeffrey Pai, 2019. "Pricing temperature derivatives with a filtered historical simulation approach," The European Journal of Finance, Taylor & Francis Journals, vol. 25(15), pages 1462-1484, October.
    27. Asai, Manabu & Brugal, Ivan, 2013. "Forecasting volatility via stock return, range, trading volume and spillover effects: The case of Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 202-213.
    28. Wilson Calmon & Eduardo Ferioli & Davi Lettieri & Johann Soares & Adrian Pizzinga, 2021. "An Extensive Comparison of Some Well‐Established Value at Risk Methods," International Statistical Review, International Statistical Institute, vol. 89(1), pages 148-166, April.
    29. Mawuli Segnon & Mark Trede, 2017. "Forecasting Market Risk of Portfolios: Copula-Markov Switching Multifractal Approach," CQE Working Papers 6617, Center for Quantitative Economics (CQE), University of Muenster.
    30. Marco Rocco, 2011. "Extreme value theory for finance: a survey," Questioni di Economia e Finanza (Occasional Papers) 99, Bank of Italy, Economic Research and International Relations Area.
    31. Marius Lux & Wolfgang Karl Hardle & Stefan Lessmann, 2020. "Data driven value-at-risk forecasting using a SVR-GARCH-KDE hybrid," Papers 2009.06910, arXiv.org.
    32. Krzysztof Echaust & Małgorzata Just, 2020. "Value at Risk Estimation Using the GARCH-EVT Approach with Optimal Tail Selection," Mathematics, MDPI, vol. 8(1), pages 1-24, January.
    33. Trucíos, Carlos & Ruiz Ortega, Esther & Hotta, Luiz, 2015. "Robust bootstrap forecast densities for GARCH models: returns, volatilities and value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws1523, Universidad Carlos III de Madrid. Departamento de Estadística.
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    Cited by:

    1. Stavros Degiannakis & Pamela Dent & Christos Floros, 2014. "A Monte Carlo Simulation Approach to Forecasting Multi-period Value-at-Risk and Expected Shortfall Using the FIGARCH-skT Specification," Manchester School, University of Manchester, vol. 82(1), pages 71-102, January.
    2. Beutner, Eric & Heinemann, Alexander & Smeekes, Stephan, 2024. "A residual bootstrap for conditional Value-at-Risk," Journal of Econometrics, Elsevier, vol. 238(2).
    3. Trucíos, Carlos & Ruiz Ortega, Esther & Hotta, Luiz, 2015. "Robust bootstrap forecast densities for GARCH models: returns, volatilities and value-at-risk," DES - Working Papers. Statistics and Econometrics. WS ws1523, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Mahsa Gorji & Rasoul Sajjad, 2017. "Improving Value-at-Risk Estimation from the Normal EGARCH Model," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 11(1), March.
    5. Christophe Hurlin & Sébastien Laurent & Rogier Quaedvlieg & Stephan Smeekes, 2017. "Risk Measure Inference," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 499-512, October.
    6. Müller, Fernanda Maria & Santos, Samuel Solgon & Righi, Marcelo Brutti, 2023. "A description of the COVID-19 outbreak role in financial risk forecasting," The North American Journal of Economics and Finance, Elsevier, vol. 66(C).
    7. Emese Lazar & Ning Zhang, 2017. "Model Risk of Expected Shortfall," ICMA Centre Discussion Papers in Finance icma-dp2017-10, Henley Business School, University of Reading.
    8. Wagner Piazza Gaglianone & Luiz Renato Lima & Oliver Linton & Daniel R. Smith, 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 29(1), pages 150-160, January.
    9. Dilip Kumar & S. Maheswaran, 2013. "Return, Volatility and Risk Spillover from Oil Prices and the US Dollar Exchange Rate to the Indian Industrial Sectors," Margin: The Journal of Applied Economic Research, National Council of Applied Economic Research, vol. 7(1), pages 61-91, February.
    10. Christophe Boucher & Jon Danielsson & Patrick Kouontchou & Bertrand Maillet, 2014. "Risk models-at-risk," Post-Print hal-02312332, HAL.
    11. d’Addona, Stefano & Khanom, Najrin, 2022. "Estimating tail-risk using semiparametric conditional variance with an application to meme stocks," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 241-260.
    12. Meriem Rjiba & Michail Tsagris & Hedi Mhalla, 2015. "Bootstrap for Value at Risk Prediction," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 4(6), pages 362-371.
    13. Nieto, Maria Rosa & Ruiz, Esther, 2016. "Frontiers in VaR forecasting and backtesting," International Journal of Forecasting, Elsevier, vol. 32(2), pages 475-501.
    14. Fan, Ying & Zhang, Yue-Jun & Tsai, Hsien-Tang & Wei, Yi-Ming, 2008. "Estimating 'Value at Risk' of crude oil price and its spillover effect using the GED-GARCH approach," Energy Economics, Elsevier, vol. 30(6), pages 3156-3171, November.
    15. Wynand Smit & Gary van Vuuren and Paul Styger, 2011. "Economic capital for credit risk in the trading book," South African Journal of Economic and Management Sciences, University of Pretoria, Faculty of Economic and Management Sciences, vol. 14(2), pages 138-152, June.
    16. Radu Tunaru, 2015. "Model Risk in Financial Markets:From Financial Engineering to Risk Management," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 9524, June.
    17. Fernanda Maria Müller & Marcelo Brutti Righi, 2024. "Comparison of Value at Risk (VaR) Multivariate Forecast Models," Computational Economics, Springer;Society for Computational Economics, vol. 63(1), pages 75-110, January.
    18. Alicia Pérez Alonso, 2006. "A Bootstrap Approach To Test The Conditional Symmetry In Time Series Models," Working Papers. Serie AD 2006-18, Instituto Valenciano de Investigaciones Económicas, S.A. (Ivie).
    19. Weronika Ormaniec & Marcin Pitera & Sajad Safarveisi & Thorsten Schmidt, 2022. "Estimating value at risk: LSTM vs. GARCH," Papers 2207.10539, arXiv.org.
    20. Carol Alexander & Jose Maria Sarabia, 2010. "Endogenizing Model Risk to Quantile Estimates," ICMA Centre Discussion Papers in Finance icma-dp2010-07, Henley Business School, University of Reading.
    21. Taewook Lee & Moosup Kim & Changryong Baek, 2015. "Tests for Volatility Shifts in Garch Against Long-Range Dependence," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(2), pages 127-153, March.
    22. Fresoli, Diego Eduardo & Ruiz Ortega, Esther, 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.
    23. Hussein Khraibani & Bilal Nehme & Olivier Strauss, 2018. "Interval Estimation of Value-at-Risk Based on Nonparametric Models," Econometrics, MDPI, vol. 6(4), pages 1-30, December.
    24. Zili Zhang & Saralees Nadarajah, 2021. "A Statistical Analysis of the Colombo Stock Returns," Global Business Review, International Management Institute, vol. 22(1), pages 101-118, February.
    25. Nieto, María Rosa & Ruiz Ortega, Esther, 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.
    26. Eric Beutner & Alexander Heinemann & Stephan Smeekes, 2018. "A Residual Bootstrap for Conditional Value-at-Risk," Papers 1808.09125, arXiv.org, revised Aug 2023.
    27. Broda, Simon & Paolella, Marc S., 2007. "Saddlepoint approximations for the doubly noncentral t distribution," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2907-2918, March.
    28. Shimizu Kenichi, 2013. "The bootstrap does not alwayswork for heteroscedasticmodels," Statistics & Risk Modeling, De Gruyter, vol. 30(3), pages 189-204, August.
    29. Tomáš Jeøábek, 2020. "The Efficiency of GARCH Models in Realizing Value at Risk Estimates," ACTA VSFS, University of Finance and Administration, vol. 14(1), pages 32-50.
    30. Nieto, María Rosa & Ruiz Ortega, Esther, 2010. "Bootstrap prediction intervals for VaR and ES in the context of GARCH models," DES - Working Papers. Statistics and Econometrics. WS ws102814, Universidad Carlos III de Madrid. Departamento de Estadística.
    31. Ian Laker & Chun-Kai Huang & Allan Ernest Clark, 2017. "Dependent bootstrapping for value-at-risk and expected shortfall," Risk Management, Palgrave Macmillan, vol. 19(4), pages 301-322, November.
    32. Köksal, Bülent & Orhan, Mehmet, 2012. "Market risk of developed and developing countries during the global financial crisis," MPRA Paper 37523, University Library of Munich, Germany.
    33. Giannikis, D. & Vrontos, I.D. & Dellaportas, P., 2008. "Modelling nonlinearities and heavy tails via threshold normal mixture GARCH models," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1549-1571, January.
    34. Lönnbark, Carl, 2008. "A Corrected Value-at-Risk Predictor," Umeå Economic Studies 734, Umeå University, Department of Economics.
    35. Stéphane Goutte & David Guerreiro & Bilel Sanhaji & Sophie Saglio & Julien Chevallier, 2019. "International Financial Markets," Post-Print halshs-02183053, HAL.

  20. Stefan Mittnik & Thorsten Neumann, 2003. "Time-Series Evidence on the Nonlinearity Hypothesis for Public Spending," Economic Inquiry, Western Economic Association International, vol. 41(4), pages 565-573, October.

    Cited by:

    1. François Facchini & Mickaël Melki, 2013. "Efficient government size: France in the 20 th century," Post-Print hal-01286723, HAL.
    2. Tamoya Christie, 2014. "The Effect Of Government Spending On Economic Growth: Testing The Non-Linear Hypothesis," Bulletin of Economic Research, Wiley Blackwell, vol. 66(2), pages 183-204, April.
    3. Ayşegül Durucan, 2022. "Testing The Validity Of The Bars Curve For Turkey," Economic Annals, Faculty of Economics and Business, University of Belgrade, vol. 67(232), pages 153-192, January –.
    4. d'Agostino, Giorgio & Daddi, Pierluigi & Pieroni, Luca & Steinbrueck, Eric, 2014. "Does military spending stimulate growth? An empirical investigation in Italy," MPRA Paper 58290, University Library of Munich, Germany.
    5. Rajkumar, Andrew Sunil & Swaroop, Vinaya, 2008. "Public spending and outcomes: Does governance matter?," Journal of Development Economics, Elsevier, vol. 86(1), pages 96-111, April.
    6. François Facchini & Mickaël Melki, 2013. "Political Ideology and Economic Growth: Evidence from the French Democracy," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00917617, HAL.
    7. d'Agostino, G. & Dunne, J.P. & Pieroni, L., 2011. "Optimal military spending in the US: A time series analysis," Economic Modelling, Elsevier, vol. 28(3), pages 1068-1077, May.
    8. Iana Paliova & Robert McNown & Grant Nülle, 2019. "Multiple Dimensions of Human Development Index and Public Social Spending for Sustainable Development," IMF Working Papers 2019/204, International Monetary Fund.
    9. Ratbek Dzhumashev, 2014. "The Two-Way Relationship Between Government Spending And Corruption And Its Effects On Economic Growth," Contemporary Economic Policy, Western Economic Association International, vol. 32(2), pages 403-419, April.
    10. François Facchini & Mickaël Melki, 2013. "Political Ideology and Economic Growth: Evidence from the French Democracy," Documents de travail du Centre d'Economie de la Sorbonne 13077, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    11. Hüseyin Şen & Ayşe Kaya & Ayşegül Durucan, 2023. "New insights into the growth-maximizing size of government: evidence and implications for Turkey," Economic Change and Restructuring, Springer, vol. 56(4), pages 2243-2296, August.
    12. d'Agostino, G. & Dunne, J.P. & Pieroni, L., 2016. "Corruption and growth in Africa," European Journal of Political Economy, Elsevier, vol. 43(C), pages 71-88.
    13. Thibaut Dort & Pierre-Guillaume Méon & Khalid Sekkat, 2013. "Does investment spur growth everywhere? Not where institutions are weak," Working Papers CEB 13-030, ULB -- Universite Libre de Bruxelles.
    14. Fiseha Gebregziabher & Miguel Niño-Zarazúa, 2014. "Social Spending and Aggregate Welfare in Developing and Transition Economies," WIDER Working Paper Series wp-2014-082, World Institute for Development Economic Research (UNU-WIDER).
    15. François Facchini & Mickaël Melki, 2011. "Optimal government size and economic growth in France (1871-2008) : An explanation by the State and market failures," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00654363, HAL.
    16. Milad Zarin-Nejadan, 2011. "Government and Growth," IRENE Working Papers 11-02, IRENE Institute of Economic Research.

  21. Holger Claessen & Stefan Mittnik, 2002. "Forecasting stock market volatility and the informational efficiency of the DAX-index options market," The European Journal of Finance, Taylor & Francis Journals, vol. 8(3), pages 302-321.
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  22. Mittnik, Stefan & Paolella, Marc S. & Rachev, Svetlozar T., 2002. "Stationarity of stable power-GARCH processes," Journal of Econometrics, Elsevier, vol. 106(1), pages 97-107, January.

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    1. Budi Setiawan & Marwa Ben Abdallah & Maria Fekete-Farkas & Robert Jeyakumar Nathan & Zoltan Zeman, 2021. "GARCH (1,1) Models and Analysis of Stock Market Turmoil during COVID-19 Outbreak in an Emerging and Developed Economy," JRFM, MDPI, vol. 14(12), pages 1-19, December.
    2. 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.
    3. Paolella, Marc S. & Taschini, Luca, 2008. "An econometric analysis of emission allowance prices," Journal of Banking & Finance, Elsevier, vol. 32(10), pages 2022-2032, October.
    4. Alex Huang, 2013. "Value at risk estimation by quantile regression and kernel estimator," Review of Quantitative Finance and Accounting, Springer, vol. 41(2), pages 225-251, August.
    5. Stoyanov, Stoyan V. & Rachev, Svetlozar T. & Fabozzi, Frank J., 2011. "CVaR sensitivity with respect to tail thickness," Working Paper Series in Economics 29, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    6. Sun, Wei & Rachev, Svetlozar & Fabozzi, Frank J., 2007. "Fractals or I.I.D.: Evidence of long-range dependence and heavy tailedness from modeling German equity market returns," Journal of Economics and Business, Elsevier, vol. 59(6), pages 575-595.
    7. Broda, Simon A. & Haas, Markus & Krause, Jochen & Paolella, Marc S. & Steude, Sven C., 2013. "Stable mixture GARCH models," Journal of Econometrics, Elsevier, vol. 172(2), pages 292-306.
    8. Nolan, John P., 2018. "Truncated fractional moments of stable laws," Statistics & Probability Letters, Elsevier, vol. 137(C), pages 312-318.
    9. Huang, Alex YiHou & Peng, Sheng-Pen & Li, Fangjhy & Ke, Ching-Jie, 2011. "Volatility forecasting of exchange rate by quantile regression," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 591-606, October.
    10. Bekaert, Geert & Engstrom, Eric & Ermolov, Andrey, 2015. "Bad environments, good environments: A non-Gaussian asymmetric volatility model," Journal of Econometrics, Elsevier, vol. 186(1), pages 258-275.
    11. Calzolari, Giorgio & Halbleib, Roxana & Parrini, Alessandro, 2014. "Estimating GARCH-type models with symmetric stable innovations: Indirect inference versus maximum likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 158-171.
    12. LOMBARDI, Marco & VEREDAS, David, 2007. "Indirect estimation of elliptical stable distributions," LIDAM Discussion Papers CORE 2007018, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    13. Xing Yu, 2012. "The optimal portfolio model based on multivariate t distribution with linear weighted sum method," E3 Journal of Business Management and Economics., E3 Journals, vol. 3(1), pages 044-047.
    14. BOUADDI, Mohammed & ROMBOUTS, Jeroen V.K., 2007. "Mixed exponential power asymmetric conditional heteroskedasticity," LIDAM Discussion Papers CORE 2007097, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Dennis Kristensen, 2009. "On stationarity and ergodicity of the bilinear model with applications to GARCH models," Journal of Time Series Analysis, Wiley Blackwell, vol. 30(1), pages 125-144, January.
    16. Huang, Alex YiHou, 2010. "An optimization process in Value-at-Risk estimation," Review of Financial Economics, Elsevier, vol. 19(3), pages 109-116, August.
    17. Ramona Serrano Bautista & Leovardo Mata Mata, 2018. "Estimación del VaR mediante un modelo condicional multivariado bajo la hipótesis α-estable sub-Gaussiana. (A conditional approach to VaR with multivariate α-stable sub-Gaussian distributions)," Ensayos Revista de Economia, Universidad Autonoma de Nuevo Leon, Facultad de Economia, vol. 0(1), pages 43-76, May.
    18. Calzolari, Giorgio & Halbleib, Roxana, 2018. "Estimating stable latent factor models by indirect inference," Journal of Econometrics, Elsevier, vol. 205(1), pages 280-301.
    19. 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.
    20. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, December.
    21. Sio Chong U & Jacky So & Deng Ding & Lihong Liu, 2016. "An efficient Fourier expansion method for the calculation of value-at-risk: Contributions of extra-ordinary risks," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 3(01), pages 1-27, March.
    22. Wei Sun & Svetlozar Rachev & Frank Fabozzi & Petko Kalev, 2009. "A new approach to modeling co-movement of international equity markets: evidence of unconditional copula-based simulation of tail dependence," Empirical Economics, Springer, vol. 36(1), pages 201-229, February.
    23. 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.
    24. 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.
    25. URAL, Mert & DEMİRELİ, Erhan, 2018. "Modeling Asymmetric Volatility In The Chicago Board Options Exchange Volatility Index," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 22(1), pages 20-31.
    26. Gonçalves, E. & Leite, J. & Mendes-Lopes, N., 2012. "On the probabilistic structure of power threshold generalized arch stochastic processes," Statistics & Probability Letters, Elsevier, vol. 82(8), pages 1597-1609.
    27. Tae-Hwy Lee & Yong Bao & Burak Saltoglu, 2006. "Evaluating predictive performance of value-at-risk models in emerging markets: a reality check," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 25(2), pages 101-128.
    28. Bellini, Fabio & Bottolo, Leonardo, 2007. "Stationarity domains for [delta]-power Garch process with heavy tails," Statistics & Probability Letters, Elsevier, vol. 77(13), pages 1418-1427, July.

  23. Chiarella Carl & Semmler Willi & Mittnik Stefan & Zhu Peiyuan, 2002. "Stock Market, Interest Rate and Output: A Model and Estimation for US Time Series Data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(1), pages 1-39, April.

    Cited by:

    1. Raberto, Marco & Teglio, Andrea & Cincotti, Silvano, 2006. "A dynamic general disequilibrium model of a sequential monetary production economy," Chaos, Solitons & Fractals, Elsevier, vol. 29(3), pages 566-577.
    2. Willi Semmler, 2011. "Asset Prices, Booms and Recessions," Springer Books, Springer, number 978-3-642-20680-1, September.
    3. Angelos Kanas & Christos Ioannidis, 2010. "Causality from real stock returns to real activity: evidence of regime-dependence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 15(2), pages 180-197.
    4. Carl Chiarella & Peter Flaschel & Willi Semmler, 2001. "Real-Financial Interaction: A Reconsideration of the Blanchard Model with a State-of-Market Dependent Reaction Coefficient," Working Paper Series 111, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    5. Lambert, Dayton M. & Lowenberg-DeBoer, James & Malzer, Gary L., 2004. "A Systems Approach For Evaluating On-Farm Site-Specific Management Trials: A Case Study With Variable Rate Manure And Crop Quality Response To Inputs," 2004 Annual meeting, August 1-4, Denver, CO 20091, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    6. Carl Chiarella & Peter Flaschel & Reiner Franke & Willi Semmler, 2000. "Output, Financial Markets and Growth," Working Paper Series 108, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    7. F. Cavalli & A. Naimzada & N. Pecora, 2022. "A stylized macro-model with interacting real, monetary and stock markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(1), pages 225-257, January.
    8. Harper, David C. & Lambert, Dayton M. & Larson, James A. & Gwathmey, C. Owen, 2012. "Potassium carryover dynamics and optimal application policies in cotton production," Agricultural Systems, Elsevier, vol. 106(1), pages 84-93.
    9. Peter Woehrmann, "undated". "A dynamic model of the financial�real interaction as a model selection criterion for nonparametric stock market prediction," IEW - Working Papers 226, Institute for Empirical Research in Economics - University of Zurich.

  24. Stefan Mittnik & Thorsten Neumann, 2001. "Dynamic effects of public investment: Vector autoregressive evidence from six industrialized countries," Empirical Economics, Springer, vol. 26(2), pages 429-446.

    Cited by:

    1. Jordi Pons-i-Novell & Ramon Tremosa-i-Balcells, 2005. "Macroeconomic effects of Catalan fiscal deficit with the Spanish state (2002-2010)," Applied Economics, Taylor & Francis Journals, vol. 37(13), pages 1455-1463.
    2. Ibrahim, Taofki, 2018. "Does Public Capital Influence Output Growth? Further Evidence from Nigeria," MPRA Paper 88635, University Library of Munich, Germany, revised 22 Jul 2018.
    3. Ibrahim Ari & Muammer Koc, 2020. "Economic Growth, Public and Private Investment: A Comparative Study of China and the United States," Sustainability, MDPI, vol. 12(6), pages 1-19, March.
    4. Sergio Destefanis & Mario Di Serio & Matteo Fragetta, 2020. "Regional multipliers across the Italian regions," Discussion Paper series in Regional Science & Economic Geography 2020-04, Gran Sasso Science Institute, Social Sciences, revised Jul 2020.
    5. Gadatsch, Niklas & Hauzenberger, Klemens & Stähler, Nikolai, 2015. "German and the rest of euro area fiscal policy during the crisis," Discussion Papers 05/2015, Deutsche Bundesbank.
    6. Christophe Kamps, 2004. "New Estimates of Government Net Capital Stocks for 22 OECD Countries 1960-2001," IMF Working Papers 2004/067, International Monetary Fund.
    7. Batool, Irem & Goldmann, Kathrin, 2021. "The role of public and private transport infrastructure capital in economic growth. Evidence from Pakistan," Research in Transportation Economics, Elsevier, vol. 88(C).
    8. Syed Ammad & Qazi Masood Ahmed, 2014. "Dynamic Effects of Energy Sector Public Investment on Sectoral Economic Growth: Experience from Pakistan Economy," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 53(4), pages 403-421.
    9. Alfredo M. Pereira & Jorge M. Andraz, 2013. "On The Economic Effects Of Public Infrastructure Investment: A Survey Of The International Evidence," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 38(4), pages 1-37, December.
    10. Jérôme Creel & Paola Monperrus‐Veroni & Francesco Saraceno, 2009. "On The Long‐Term Effects Of Fiscal Policy In The United Kingdom: The Case For A Golden Rule," Scottish Journal of Political Economy, Scottish Economic Society, vol. 56(5), pages 580-607, November.
    11. António Afonso & Miguel St. Aubyn, 2009. "Macroeconomic Rates Of Return Of Public And Private Investment: Crowding‐In And Crowding‐Out Effects," Manchester School, University of Manchester, vol. 77(s1), pages 21-39, September.
    12. Gadatsch, Niklas & Hauzenberger, Klemens & Stähler, Nikolai, 2016. "Fiscal policy during the crisis: A look on Germany and the Euro area with GEAR," Economic Modelling, Elsevier, vol. 52(PB), pages 997-1016.
    13. Romp, Ward & de Haan, Jakob, 2005. "Public capital and economic growth: a critical survey," EIB Papers 2/2005, European Investment Bank, Economics Department.
    14. Trofimov, Ivan D., 2020. "Public capital and productive economy profits: evidence from OECD economies," MPRA Paper 106848, University Library of Munich, Germany.
    15. Salwa Trabelsi, 2018. "Public Education Spending and Economic Growth: The Governance Threshold Effect," Journal of Economic Development, Chung-Ang Unviersity, Department of Economics, vol. 43(1), pages 101-124, March.
    16. Christophe Kamps, 2005. "The Dynamic Effects of Public Capital: VAR Evidence for 22 OECD Countries," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 12(4), pages 533-558, August.
    17. Alexandre Manuel Angelo da Silva & José Oswaldo Cândido Júnior, 2009. "Impactos Macroeconômicos dos Gastos Públicos na América Latina," Discussion Papers 1434, Instituto de Pesquisa Econômica Aplicada - IPEA.
    18. Ms. Anita Tuladhar & Markus Bruckner, 2010. "Public Investment as a Fiscal Stimulus: Evidence from Japan’s Regional Spending During the 1990s," IMF Working Papers 2010/110, International Monetary Fund.
    19. Valter Di Giacinto & Giacinto Micucci & Pasqualino Montanaro, 2009. "Dynamic macroeconomic effects of public capital: evidence from regional Italian data," Temi di discussione (Economic working papers) 733, Bank of Italy, Economic Research and International Relations Area.
    20. Nusrat Akber & Megha Gupta & Kirtti Ranjan Paltasingh, 2020. "The Crowding-in/ out Debate in Investments in India: Fresh Evidence from NARDL Application," South Asian Journal of Macroeconomics and Public Finance, , vol. 9(2), pages 167-189, December.
    21. Mathias A. Chuba, 2021. "Crowding-Out and Crowding-In Effects of Public Borrowing on Private Domestic Investment in Nigeria," International Journal of Research and Innovation in Social Science, International Journal of Research and Innovation in Social Science (IJRISS), vol. 5(11), pages 439-448, November.
    22. Inácia Pimentel & Miguel St.Aubyn & Nuno Ribeiro, 2017. "The impact of investment in Public Private Partnerships on Public, Private investment and GDP in Portugal," Working Papers Department of Economics 2017/13, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    23. Mario Alloza & Danilo Leiva-León & Alberto Urtasun, 2022. "The response of private investment to an increase in public investment," Economic Bulletin, Banco de España, issue 2/2022.
    24. Agenor, Pierre-Richard & Nabli, Mustapha K. & Yousef, Tarik M., 2005. "Public infrastructure and private investment in the Middle East and North Africa," Policy Research Working Paper Series 3661, The World Bank.
    25. Anca-Stefania Sava & Bogdan-Gabriel Zugravu, 2010. "Analysis of the Correlations Between Public Capital Investments and Economic Development in Romania," Studies and Scientific Researches. Economics Edition, "Vasile Alecsandri" University of Bacau, Faculty of Economic Sciences, issue 15.
    26. Dai, Meixing & Sidiropoulos, Moïse, 2010. "Monetary and fiscal policy interactions with central bank transparency and public investment," MPRA Paper 23704, University Library of Munich, Germany.
    27. Sachverständigenrat zur Begutachtung der gesamtwirtschaftlichen Entwicklung (ed.), 2007. "Staatsverschuldung wirksam begrenzen. Expertise im Auftrag des Bundesministers für Wirtschaft und Technologie," Occasional Reports / Expertisen, German Council of Economic Experts / Sachverständigenrat zur Begutachtung der gesamtwirtschaftlichen Entwicklung, number 75368, September.
    28. Oukhallou, Youssef, 2016. "Analyzing economic growth: what role for public investment?," MPRA Paper 69772, University Library of Munich, Germany.
    29. Valter Di Giacinto & Giacinto Micucci & Pasqualino Montanaro, 2012. "The Macroeconomic Impact of Infrastructures: A Literature Review and Empirical Analysis on the Case of Italy," QA - Rivista dell'Associazione Rossi-Doria, Associazione Rossi Doria, issue 1, March.
    30. João Sousa Andrade & António Portugal Duarte, 2014. "Crowding-in and Crowding-out Effects of Public Investments in the Portuguese Economy," GEMF Working Papers 2014-24, GEMF, Faculty of Economics, University of Coimbra.
    31. Ahmed, Qazi Masood & Ali, Syed Ammad, 2014. "Public investment efficiency and sectoral economic growth in Pakistan:," PSSP working papers 22, International Food Policy Research Institute (IFPRI).
    32. Cheteni, Priviledge, 2013. "Transport Infrastructure Investment and Transport Sector Productivity on Economic Growth in South Africa (1975-2011)," MPRA Paper 53175, University Library of Munich, Germany, revised 18 Jul 2013.
    33. Ozkan, F Gulcin & Ismihan, Mustafa, 2007. "Public investment: a remedy or a curse? Examining the Role of Public Investment for Macroeconomic Performance," CEPR Discussion Papers 6139, C.E.P.R. Discussion Papers.
    34. Federici, Andrea, 2018. "Il rapporto tra capitale pubblico e altre variabili macroeconomiche: un'applicazione empirica [The relationship between public capital and other macroeconomic variables: an empirical application]," MPRA Paper 88516, University Library of Munich, Germany.
    35. Torrisi, Gianpiero, 2009. "Infrastructures and economic performance: a critical comparison across four approaches," MPRA Paper 18688, University Library of Munich, Germany.
    36. Stephanos Papadamou & Eleftherios Spyromitros & Panagiotis Tsintzos, 2017. "Public investment, inflation persistence and central bank independence," Journal of Economic Studies, Emerald Group Publishing Limited, vol. 44(6), pages 976-986, November.
    37. Olanrewaju Makinde Hassan, 2015. "The Impact of Monetary Policy on Private Capital Formation in Nigeria," Journal of Empirical Economics, Research Academy of Social Sciences, vol. 4(3), pages 138-153.
    38. Luigi Marattin & Simone Salotti, 2014. "Consumption multipliers of different types of public spending: a structural vector error correction analysis for the UK," Empirical Economics, Springer, vol. 46(4), pages 1197-1220, June.
    39. Federici, Andrea, 2018. "Il rapporto tra capitale pubblico e altre variabili macroeconomiche: analisi della letteratura [The relationship between public capital and other macroeconomic variable: a literature review]," MPRA Paper 88515, University Library of Munich, Germany.
    40. Torrisi, Gianpiero, 2009. "Public infrastructure: definition, classification and measurement issues," MPRA Paper 12990, University Library of Munich, Germany.
    41. Baussola, Maurizio & Carvelli, Gianni, 2023. "Public and private investments: Long-run asymmetric effects in France and the US," Finance Research Letters, Elsevier, vol. 58(PA).
    42. Hicham GOUMRHAR & Youssef OUKHALLOU, 2017. "Public Investment and GDP Growth in Developing and Advanced Countries: A Panel Data Analysis," Journal of Economics Bibliography, KSP Journals, vol. 4(1), pages 77-86, March.
    43. Rafiq Sohrab, 2012. "Is Discretionary Fiscal Policy in Japan Effective?," The B.E. Journal of Macroeconomics, De Gruyter, vol. 12(1), pages 1-49, August.
    44. Ejaz Ghani & Musleh-Ud Din, 2006. "The Impact of Public Investment on Economic Growth in Pakistan," The Pakistan Development Review, Pakistan Institute of Development Economics, vol. 45(1), pages 87-98.

  25. Mittnik, Stefan & Paolella, Marc S. & Rachev, Svetlozar T., 2000. "Diagnosing and treating the fat tails in financial returns data," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 389-416, November.

    Cited by:

    1. 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.
    2. john cotter & kevin dowd, 2011. "The tail risks of FX return distributions: a comparison of the returns associated with limit orders and market orders," Papers 1103.5661, arXiv.org.
    3. Sun, Wei & Rachev, Svetlozar & Fabozzi, Frank J., 2007. "Fractals or I.I.D.: Evidence of long-range dependence and heavy tailedness from modeling German equity market returns," Journal of Economics and Business, Elsevier, vol. 59(6), pages 575-595.
    4. Gong, Xiaoli & Zhuang, Xintian, 2017. "American option valuation under time changed tempered stable Lévy processes," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 466(C), pages 57-68.
    5. Kevin Dowd & John Cotter, 2011. "Intra-Day Seasonality in Foreign Market Transactions," Working Papers 200746, Geary Institute, University College Dublin.
    6. Choi, Pilsun & Nam, Kiseok, 2008. "Asymmetric and leptokurtic distribution for heteroscedastic asset returns: The SU-normal distribution," Journal of Empirical Finance, Elsevier, vol. 15(1), pages 41-63, January.
    7. de Vries, Casper & Hartmann, Philipp & Straetmans, Stefan, 2004. "Fundamentals and Joint Currency Crises," CEPR Discussion Papers 4338, C.E.P.R. Discussion Papers.
    8. Lehnert, Thorsten & Wolff, Christian C. P., 2004. "Scale-consistent Value-at-Risk," Finance Research Letters, Elsevier, vol. 1(2), pages 127-134, June.
    9. J. Baixauli & Susana Alvarez, 2006. "Evaluating effects of excess kurtosis on VaR estimates: Evidence for international stock indices," Review of Quantitative Finance and Accounting, Springer, vol. 27(1), pages 27-46, August.
    10. Zoia, Maria Grazia & Biffi, Paola & Nicolussi, Federica, 2018. "Value at risk and expected shortfall based on Gram-Charlier-like expansions," Journal of Banking & Finance, Elsevier, vol. 93(C), pages 92-104.
    11. Kim, Young Shin & Lee, Jaesung & Mittnik, Stefan & Park, Jiho, 2015. "Quanto option pricing in the presence of fat tails and asymmetric dependence," Journal of Econometrics, Elsevier, vol. 187(2), pages 512-520.
    12. Timotheos Angelidis & Alexandros Benos & Stavros Degiannakis, 2007. "A robust VaR model under different time periods and weighting schemes," Review of Quantitative Finance and Accounting, Springer, vol. 28(2), pages 187-201, February.
    13. Talla M Aldeehani, 2019. "Have Stock Markets Become Less Volatile After the Great Recession?," Research in World Economy, Research in World Economy, Sciedu Press, vol. 10(3), pages 10-25, December.
    14. Gimeno, Ricardo & Gonzalez, Clara I., 2012. "An automatic procedure for the estimation of the tail index," MPRA Paper 37023, University Library of Munich, Germany.
    15. Tokat, Yesim & Rachev, Svetlozar T. & Schwartz, Eduardo S., 2003. "The stable non-Gaussian asset allocation: a comparison with the classical Gaussian approach," Journal of Economic Dynamics and Control, Elsevier, vol. 27(6), pages 937-969, April.
    16. Hallin, Marc & Swan, Yvik & Verdebout, Thomas & Veredas, David, 2013. "One-step R-estimation in linear models with stable errors," Journal of Econometrics, Elsevier, vol. 172(2), pages 195-204.
    17. Mai, Nhat Chi, 2016. "The Influence Of Macroeconomic Announcements Into Vietnamese Stock Market Volatility," OSF Preprints ydmhx, Center for Open Science.
    18. Anatolyev Stanislav, 2019. "Volatility filtering in estimation of kurtosis (and variance)," Dependence Modeling, De Gruyter, vol. 7(1), pages 1-23, February.
    19. Bams, Dennis & Lehnert, Thorsten & Wolff, Christian C.P., 2005. "An evaluation framework for alternative VaR-models," Journal of International Money and Finance, Elsevier, vol. 24(6), pages 944-958, October.
    20. Calzolari, Giorgio & Halbleib, Roxana & Parrini, Alessandro, 2014. "Estimating GARCH-type models with symmetric stable innovations: Indirect inference versus maximum likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 158-171.
    21. Hemei Li & Zhenya Liu & Shixuan Wang, 2022. "Vines climbing higher: Risk management for commodity futures markets using a regular vine copula approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(2), pages 2438-2457, April.
    22. Munir Khamis & Dalal Aassouli, 2023. "The Eligibility of Green Bonds as Safe Haven Assets: A Systematic Review," Sustainability, MDPI, vol. 15(8), pages 1-27, April.
    23. 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).
    24. Tokat, Yesim & Rachev, Svetlozar T. & Schwartz, Eduardo, 2000. "The Stable non-Gaussian Asset Allocation: A Comparison with the Classical Gaussian Approach," University of California at Santa Barbara, Economics Working Paper Series qt9ph6b5gp, Department of Economics, UC Santa Barbara.
    25. Choe, Kwang-il & Choi, Pilsun & Nam, Kiseok & Vahid, Farshid, 2012. "Testing financial contagion on heteroskedastic asset returns in time-varying conditional correlation," Pacific-Basin Finance Journal, Elsevier, vol. 20(2), pages 271-291.
    26. Heitham Al-Hajieh & Hashem AlNemer & Timothy Rodgers & Jacek Niklewski, 2015. "Forecasting the Jordanian stock index: modelling asymmetric volatility and distribution effects within a GARCH framework," Copernican Journal of Finance & Accounting, Uniwersytet Mikolaja Kopernika, vol. 4(2), pages 9-26.
    27. Marc S. Paolella, 2016. "Stable-GARCH Models for Financial Returns: Fast Estimation and Tests for Stability," Econometrics, MDPI, vol. 4(2), pages 1-28, May.
    28. Mittnik, Stefan & Paolella, Marc S., 2003. "Prediction of Financial Downside-Risk with Heavy-Tailed Conditional Distributions," CFS Working Paper Series 2003/04, Center for Financial Studies (CFS).
    29. Garcia, René & Renault, Eric & Veredas, David, 2011. "Estimation of stable distributions by indirect inference," Journal of Econometrics, Elsevier, vol. 161(2), pages 325-337, April.
    30. Matteo Bonato, 2012. "Modeling fat tails in stock returns: a multivariate stable-GARCH approach," Computational Statistics, Springer, vol. 27(3), pages 499-521, September.
    31. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2002. "Mixed normal conditional heteroskedasticity," CFS Working Paper Series 2002/10, Center for Financial Studies (CFS).
    32. Paolella, Marc S., 2017. "Asymmetric stable Paretian distribution testing," Econometrics and Statistics, Elsevier, vol. 1(C), pages 19-39.
    33. Bonato, Matteo, 2011. "Robust estimation of skewness and kurtosis in distributions with infinite higher moments," Finance Research Letters, Elsevier, vol. 8(2), pages 77-87, June.
    34. René Garcia & Éric Renault & Georges Tsafack, 2007. "Proper Conditioning for Coherent VaR in Portfolio Management," Management Science, INFORMS, vol. 53(3), pages 483-494, March.
    35. Dominicy, Yves & Veredas, David, 2013. "The method of simulated quantiles," Journal of Econometrics, Elsevier, vol. 172(2), pages 235-247.

  26. Stefan Mittnik & Sascha Rieken, 2000. "Lower‐boundary violations and market efficiency: Evidence from the German DAX‐index options market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 20(5), pages 405-424, May.

    Cited by:

    1. Debaditya Mohanti & P. K. Priyan, 2014. "An Empirical Test of Market Efficiency of Indian Index Options Market Using the Black–Scholes Model and Dynamic Hedging Strategy," Paradigm, , vol. 18(2), pages 221-237, December.
    2. Martin Husák, 2022. "Do Damodaran's Multiples Value a Company Accurately? Evidence from Germany," European Financial and Accounting Journal, Prague University of Economics and Business, vol. 2022(3), pages 5-21.
    3. Zhang, Huiming & Watada, Junzo, 2019. "An analysis of the arbitrage efficiency of the Chinese SSE 50ETF options market," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 474-489.
    4. Yueh-Neng Lin & Shih-Kuo Yeh & Shih-Ching Chuan & Steven J. Jordan, 2008. "The link between intraday signals and call warrant mispricing," The Service Industries Journal, Taylor & Francis Journals, vol. 30(13), pages 2273-2288, November.

  27. Stefan Mittnik & Marc Paolella & Svetlozar Rachev, 1998. "Unconditional and Conditional Distributional Models for the Nikkei Index," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 5(2), pages 99-128, May.

    Cited by:

    1. Sung Ik Kim, 2022. "ARMA–GARCH model with fractional generalized hyperbolic innovations," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-25, December.
    2. José Curto & José Pinto & Gonçalo Tavares, 2009. "Modeling stock markets’ volatility using GARCH models with Normal, Student’s t and stable Paretian distributions," Statistical Papers, Springer, vol. 50(2), pages 311-321, March.
    3. José Dias Curto & João Tomaz & José Castro Pinto, 2009. "A new approach to bad news effects on volatility: the multiple-sign-volume sensitive regime EGARCH model (MSV-EGARCH)," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 8(1), pages 23-36, April.
    4. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2008. "Partial Likelihood-Based Scoring Rules for Evaluating Density Forecasts in Tails," Discussion Papers 2008-10, School of Economics, The University of New South Wales.
    5. Fischer, Matthias J., 2002. "Skew generalized secant hyperbolic distributions: unconditional and conditional fit to asset returns," Discussion Papers 46/2002, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
    6. Cees Diks & Valentyn Panchenko & Dick van Dijk, 2011. "Likelihood-based scoring rules for comparing density forecasts in tails," Post-Print hal-00834423, HAL.
    7. Fischer, Matthias J. & Vaughan, David, 2002. "Classes of skew generalized hyperbolic secant distributions," Discussion Papers 45/2002, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
    8. Peter Bossaerts & Shijie Huang & Nitin Yadav, 2020. "Exploiting Distributional Temporal Difference Learning to Deal with Tail Risk," Risks, MDPI, vol. 8(4), pages 1-20, October.
    9. Mittnik, Stefan & Paolella, Marc S. & Rachev, Svetlozar T., 2000. "Diagnosing and treating the fat tails in financial returns data," Journal of Empirical Finance, Elsevier, vol. 7(3-4), pages 389-416, November.
    10. Fischer, Matthias J., 2000. "The folded EGB2 distribution and its application to financial return data," Discussion Papers 32/2000, Friedrich-Alexander University Erlangen-Nuremberg, Chair of Statistics and Econometrics.
    11. Corsi, Fulvio & Kretschmer, Uta & Mittnik, Stefan & Pigorsch, Christian, 2005. "The volatility of realized volatility," CFS Working Paper Series 2005/33, Center for Financial Studies (CFS).
    12. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2005. "Modeling and predicting market risk with Laplace-Gaussian mixture distributions," CFS Working Paper Series 2005/11, Center for Financial Studies (CFS).
    13. Marc S. Paolella, 2016. "Stable-GARCH Models for Financial Returns: Fast Estimation and Tests for Stability," Econometrics, MDPI, vol. 4(2), pages 1-28, May.
    14. Broda, Simon & Paolella, Marc S., 2007. "Saddlepoint approximations for the doubly noncentral t distribution," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2907-2918, March.
    15. Gel, Yulia R., 2010. "Test of fit for a Laplace distribution against heavier tailed alternatives," Computational Statistics & Data Analysis, Elsevier, vol. 54(4), pages 958-965, April.
    16. Haas, Markus & Mittnik, Stefan & Paolella, Marc S., 2002. "Mixed normal conditional heteroskedasticity," CFS Working Paper Series 2002/10, Center for Financial Studies (CFS).
    17. Lee, Tae-Hwy & Saltoglu, Burak, 2002. "Assessing the risk forecasts for Japanese stock market," Japan and the World Economy, Elsevier, vol. 14(1), pages 63-85, January.

  28. Mittnik, Stefan & Rachev, Svetlozar T. & Kim, Jeong-Ryeol, 1998. "Chi-Square-Type Distributions For Heavy-Tailed Variates," Econometric Theory, Cambridge University Press, vol. 14(3), pages 339-354, June.

    Cited by:

    1. Hill, Jonathan B. & Aguilar, Mike, 2013. "Moment condition tests for heavy tailed time series," Journal of Econometrics, Elsevier, vol. 172(2), pages 255-274.
    2. Hansen, Gerd, 2000. "The German labour market and the unification shock," Economic Modelling, Elsevier, vol. 17(3), pages 439-454, August.
    3. Kurz-Kim, Jeong-Ryeol & Loretan, Mico, 2014. "On the properties of the coefficient of determination in regression models with infinite variance variables," Journal of Econometrics, Elsevier, vol. 181(1), pages 15-24.
    4. Hansen, Gerd & Kim, Jeong-Ryeol & Mittnik, Stefan, 1998. "Testing cointegrating coefficients in vector autoregressive error correction models," Economics Letters, Elsevier, vol. 58(1), pages 1-5, January.

  29. Hansen, Gerd & Kim, Jeong-Ryeol & Mittnik, Stefan, 1998. "Testing cointegrating coefficients in vector autoregressive error correction models," Economics Letters, Elsevier, vol. 58(1), pages 1-5, January.

    Cited by:

    1. Carstensen, Kai & Hawellek, J., 2003. "Forecasting Inflation from the Term Structure," Munich Reprints in Economics 19949, University of Munich, Department of Economics.
    2. Joerg Breitung & M. Hashem Pesaran, 2005. "Unit Roots and Cointegration in Panels," CESifo Working Paper Series 1565, CESifo.
    3. Hansen, Gerd, 2000. "The German labour market and the unification shock," Economic Modelling, Elsevier, vol. 17(3), pages 439-454, August.
    4. Julián Ramajo Hernández(1) & Montserrat Ferré Carracedo(2), "undated". "Testing For Long-Run Purchasing Power Parity In The Post Bretton Woods Era: Evidence From Old And New Tests," Working Papers 24-05 Classification-JEL , Instituto de Estudios Fiscales.
    5. Kurita, Takamitsu, 2010. "Effects of a signal-to-noise ratio on finite sample inference for cointegrating vectors," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 80(10), pages 2033-2039.

  30. Kim Jeong-Ryeol & Mittnik Stefan & Rachev Svetlozar T., 1996. "Detecting Asymmetries in Observed Linear Time Series and Unobserved Disturbances," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 1(3), pages 1-15, October.

    Cited by:

    1. Belaire-Franch Jorge & Peiro Amado, 2003. "Conditional and Unconditional Asymmetry in U.S. Macroeconomic Time Series," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(1), pages 1-19, April.
    2. Jagric Timotej, 2003. "A Nonlinear Approach to Forecasting with Leading Economic Indicators," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(2), pages 1-20, July.
    3. W A Razzak, 1998. "Business cycle asymmetries and the nominal exchange rate regimes," Reserve Bank of New Zealand Discussion Paper Series G98/4, Reserve Bank of New Zealand.
    4. Luke Hartigan, 2016. "Testing for Symmetry in Weakly Dependent Time Series," Discussion Papers 2016-18, School of Economics, The University of New South Wales.
    5. Dufour, Jean-Marie & Kurz-Kim, Jeong-Ryeol, 2010. "Exact inference and optimal invariant estimation for the stability parameter of symmetric [alpha]-stable distributions," Journal of Empirical Finance, Elsevier, vol. 17(2), pages 180-194, March.
    6. W.A. Razzak, 2001. "Business Cycle Asymmetries: International Evidence," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 4(1), pages 230-243, January.
    7. Randal J. Verbrugge, 1998. "A cross-country investigation of macroeconomic asymmetries," Macroeconomics 9809017, University Library of Munich, Germany, revised 30 Sep 1998.

  31. Mittnik, Stefan & Zadrozny, Peter A, 1993. "Asymptotic Distributions of Impulse Responses, Step Responses, and Variance Decompositions of Estimated Linear Dynamic Models," Econometrica, Econometric Society, vol. 61(4), pages 857-870, July.

    Cited by:

    1. Stefan Mittnik & Nikolay Robinzonov & Klaus Wohlrabe, 2013. "The Micro Dynamics of Macro Announcements," CESifo Working Paper Series 4421, CESifo.
    2. Mittnik, Stefan & Semmler, Willi, 2013. "The real consequences of financial stress," Journal of Economic Dynamics and Control, Elsevier, vol. 37(8), pages 1479-1499.
    3. André Klein & Guy Melard & Toufik Zahaf, 1998. "Computation of the exact information matrix of Gaussian dynamic regression time series models," ULB Institutional Repository 2013/13738, ULB -- Universite Libre de Bruxelles.
    4. Mittnik, Stefan & Semmler, Willi, 2018. "Overleveraging, Financial Fragility, And The Banking–Macro Link: Theory And Empirical Evidence," Macroeconomic Dynamics, Cambridge University Press, vol. 22(1), pages 4-32, January.
    5. Chiarella Carl & Semmler Willi & Mittnik Stefan & Zhu Peiyuan, 2002. "Stock Market, Interest Rate and Output: A Model and Estimation for US Time Series Data," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 6(1), pages 1-39, April.
    6. Uhlig, Harald, 1999. "What are the Effects of Monetary Policy on Output? Results from an Agnostic Identification Procedure," CEPR Discussion Papers 2137, C.E.P.R. Discussion Papers.
    7. Chevillon, Guillaume & Mavroeidis, Sophocles & Zhan, Zhaoguo, 2016. "Robust inference in structural VARs with long-run restrictions," ESSEC Working Papers WP1702, ESSEC Research Center, ESSEC Business School.
    8. Christopher A. Sims & Tao Zha, 1995. "Error bands for impulse responses," FRB Atlanta Working Paper 95-6, Federal Reserve Bank of Atlanta.
    9. Rubio-Ramírez, Juan Francisco & Schorfheide, Frank & Fernández-Villaverde, Jesús, 2015. "Solution and Estimation Methods for DSGE Models," CEPR Discussion Papers 11032, C.E.P.R. Discussion Papers.
    10. Inoue, Atsushi & Kilian, Lutz, 2013. "Inference on impulse response functions in structural VAR models," Journal of Econometrics, Elsevier, vol. 177(1), pages 1-13.
    11. Huh, Hyeon-seung & Kim, David, 2013. "An empirical test of exogenous versus endogenous growth models for the G-7 countries," Economic Modelling, Elsevier, vol. 32(C), pages 262-272.
    12. 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.
    13. 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.
    14. Stefan Mittnik & Nikolay Robinzonov & Klaus Wohlrabe, 2013. "What Moves the DAX?," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(23), pages 32-36, December.
    15. Hyeon-Seung Huh, 2013. "A Monte Carlo test for the identifying assumptions of the Blanchard and Quah (1989) model," Applied Economics Letters, Taylor & Francis Journals, vol. 20(6), pages 601-605, April.
    16. André Klein & Guy Melard, 2004. "An algorithm for computing the asymptotic Fisher information matrix for seasonal SISO models," ULB Institutional Repository 2013/13746, ULB -- Universite Libre de Bruxelles.
    17. Gabriele Fiorentini & Enrique Sentana, 2020. "Discrete Mixtures of Normals Pseudo Maximum Likelihood Estimators of Structural Vector Autoregressions," Working Papers wp2020_2023, CEMFI.
    18. Renata Wróbel-Rotter, 2016. "Impulse Response Functions in the Dynamic Stochastic General Equilibrium Vector Autoregression Model," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 8(2), pages 93-114, June.
    19. Mittnik, Stefan & Semmler, Willi, 2012. "Regime dependence of the fiscal multiplier," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 502-522.
    20. Mounir Ben Mbarek & Samia Nasreen & Rochdi Feki, 2017. "The contribution of nuclear energy to economic growth in France: short and long run," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(1), pages 219-238, January.
    21. Uhlig, H.F.H.V.S., 1999. "What are the Effects of Monetary Policy on Output? Results from an Agnostic Identification Procedure," Other publications TiSEM 2e0fa8dd-ead5-4c6b-97cb-1, Tilburg University, School of Economics and Management.
    22. Kirstin Hubrich & Peter Vlaar, 2004. "Monetary transmission in Germany: Lessons for the Euro area," Empirical Economics, Springer, vol. 29(2), pages 383-414, May.
    23. Chung, Ching-Fan, 2001. "Calculating and analyzing impulse responses for the vector ARFIMA model," Economics Letters, Elsevier, vol. 71(1), pages 17-25, April.
    24. Willi Semmler & Stefan Mittnik, 2012. "Estimating a Banking-Macro Model for Europe Using a Multi-Regime VAR," EcoMod2012 4122, EcoMod.
    25. Stefan Mittnik & Willi Semmler, 2011. "The Instability of the Banking Sector and Macrodynamics: Theory and Empirics," DEGIT Conference Papers c016_080, DEGIT, Dynamics, Economic Growth, and International Trade.
    26. Zhou, Mo & Buongiorno, Joseph, 2005. "Price transmission between products at different stages of manufacturing in forest industries," Journal of Forest Economics, Elsevier, vol. 11(1), pages 5-19, June.

  32. Braun, Phillip A. & Mittnik, Stefan, 1993. "Misspecifications in vector autoregressions and their effects on impulse responses and variance decompositions," Journal of Econometrics, Elsevier, vol. 59(3), pages 319-341, October.

    Cited by:

    1. Thomas Gries & Tim Krieger & Daniel Meierrieks, 2009. "Causal Linkages Between Domestic Terrorism and Economic Growth," Working Papers CIE 20, Paderborn University, CIE Center for International Economics.
    2. Leonardo Nogueira Ferreira & Silvia Miranda-Agrippino & Giovanni Ricco, 2023. "Bayesian Local Projections," Working Papers Series 581, Central Bank of Brazil, Research Department.
    3. Maswana, Jean-Claude, 2006. "An empirical investigation around the finance-growth puzzle in China with a particular focus on causality and efficiency considerations," MPRA Paper 3946, University Library of Munich, Germany, revised Apr 2006.
    4. Dupasquier, Chantal & Guay, Alain & St-Amant, Pierre, 1999. "A Survey of Alternative Methodologies for Estimating Potential Output and the Output Gap," Journal of Macroeconomics, Elsevier, vol. 21(3), pages 577-595, July.
    5. Gutierrez, Carlos Enrique Carrasco & Souza, Reinaldo Castro & Guillén, Osmani Teixeira de Carvalho, 2009. "Selection of Optimal Lag Length in Cointegrated VAR Models with Weak Form of Common Cyclical Features," Brazilian Review of Econometrics, Sociedade Brasileira de Econometria - SBE, vol. 29(1), May.
    6. Shinya Sugawara & Tsunehiro Ishihara & Susumu Kunisawa & Etsu Goto & Yuichi Imanaka, 2024. "A panel vector autoregression analysis for the dynamics of medical and long‐term care expenditures," Health Economics, John Wiley & Sons, Ltd., vol. 33(4), pages 748-763, April.
    7. Ricco, Giovanni & Miranda-Agrippino, Silvia, 2018. "The Transmission of Monetary Policy Shocks," CEPR Discussion Papers 13396, C.E.P.R. Discussion Papers.
    8. Pentecôte, J.-S., 2010. "Long-run identifying restrictions on VARs within the AS-AD framework," MPRA Paper 34660, University Library of Munich, Germany.
    9. Neri, Stefano, 2023. "Long-term inflation expectations and monetary policy in the euro area before the pandemic," European Economic Review, Elsevier, vol. 154(C).
    10. Benjamin Auer & Frank Schuhmacher, 2013. "RETRACTED ARTICLE: Investor sentiment, stock market valuation and merger activity," International Review of Economics, Springer;Happiness Economics and Interpersonal Relations (HEIRS), vol. 60(2), pages 245-245, June.
    11. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2023. "Identification with External Instruments in Structural VARs," Journal of Monetary Economics, Elsevier, vol. 135(C), pages 1-19.
    12. Fabio Canova, 2007. "How much structure in empirical models?," Economics Working Papers 1054, Department of Economics and Business, Universitat Pompeu Fabra.
    13. Thomas Gries & Manfred Kraft & Daniel Meierrieks, 2008. "Financial Deepening, Trade Openness and Economic Growth in Latin America and the Caribbean," Working Papers CIE 17, Paderborn University, CIE Center for International Economics.
    14. Altissimo, F. & Violante, G.L., 1998. "Nonlinear VAR: Some Theory and an Application to the US GNP and Unemployment," Papers 338, Banca Italia - Servizio di Studi.
    15. M. Huchet & Jean-Sébastien Pentecôte, 2008. "Growing too fast? Shock asymmetries and the Euro area enlargement," Brussels Economic Review, ULB -- Universite Libre de Bruxelles, vol. 51(1), pages 33-56.
    16. Kemal Bagzibagli, 2012. "Monetary Transmission Mechanism and Time Variation in the Euro Area," Discussion Papers 12-12, Department of Economics, University of Birmingham.
    17. YOUNG Ademola Obafemi, 2022. "Non-Oil Sectors, Economic Diversification And Growth In Nigeria: Further Empirical Evidence," Studies in Business and Economics, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 17(1), pages 290-311, April.
    18. Yasir Riaz & Choudhry T. Shehzad & Zaghum Umar, 2021. "The sovereign yield curve and credit ratings in GIIPS," International Review of Finance, International Review of Finance Ltd., vol. 21(3), pages 895-916, September.
    19. Helmut Lütkepohl, 2012. "Fundamental Problems with Nonfundamental Shocks," Discussion Papers of DIW Berlin 1230, DIW Berlin, German Institute for Economic Research.
    20. Thomas Gries & Manfred Kraft & Daniel Meierrieks, 2008. "Linkages between Financial Deepening,Trade Openness and Economic Development: Causality Evidence from Sub-Saharan Africa," Working Papers CIE 15, Paderborn University, CIE Center for International Economics.
    21. Horaţiu LOVIN, 2015. "Liquidity Shocks Transmission to Lending Activity in the Romanian Banking System. A VAR Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 48-60, June.
    22. Kilian, Lutz & Kim, Yun Jung, 2009. "Do Local Projections Solve the Bias Problem in Impulse Response Inference?," CEPR Discussion Papers 7266, C.E.P.R. Discussion Papers.
    23. Ellahie, Atif & Ricco, Giovanni, 2017. "Government Purchases Reloaded : Informational Insufficiency and Heterogeneity in Fiscal VARs," Economic Research Papers 269308, University of Warwick - Department of Economics.
    24. Maganya, Mnaku H. & Ndanshau, Michael O. A., 2020. "Money and Output in Tanzania: A Test for Causality," African Journal of Economic Review, African Journal of Economic Review, vol. 8(2), July.
    25. Ronayne, David, 2011. "Which Impulse Response Function?," Economic Research Papers 270753, University of Warwick - Department of Economics.
    26. Albis, Manuel Leonard F. & Mapa, Dennis S., 2014. "Bayesian Averaging of Classical Estimates in Asymmetric Vector Autoregressive (AVAR) Models," MPRA Paper 55902, University Library of Munich, Germany.
    27. OSENI Isiaq Olasunkanmi, 2015. "Fiscal Policy Shocks and Private Consumption in Nigeria: Blanchard-Perotti (2002) Approach," Journal of Economics and Behavioral Studies, AMH International, vol. 7(6), pages 42-60.
    28. Lovcha, Yuliya & Pérez Laborda, Àlex, 2016. "Structural shocks and dinamic elasticities in a long memory model of the US gasoline retail market," Working Papers 2072/261538, Universitat Rovira i Virgili, Department of Economics.
    29. Qianqian Wang & Choi, 2015. "Co-movement of the Chinese and U.S. aggregate stock returns," Applied Economics, Taylor & Francis Journals, vol. 47(50), pages 5337-5353, October.
    30. Serguei Zernov & Victoria Zindle-Walsh & John Galbraith, 2006. "Asymptotics For Estimation Of Truncated Infinite-Dimensional Quantile Regressions," Departmental Working Papers 2006-16, McGill University, Department of Economics.
    31. Silvia Miranda Agrippino & Giovanni Ricco, 2018. "Identification with external instruments in structural VARs under partial invertibility," Sciences Po publications 24, Sciences Po.
    32. Keuk-Soo Kim & W. Douglas McMillin, 2003. "Estimating the effects of monetary policy shocks: does lag structure matter?," Applied Economics, Taylor & Francis Journals, vol. 35(13), pages 1515-1526.
    33. Miranda-Agrippino, Silvia & Ricco, Giovanni, 2019. "Identification with External Instruments in Structural VARs under Partial Invertibility," The Warwick Economics Research Paper Series (TWERPS) 1213, University of Warwick, Department of Economics.
    34. René Lalonde, 1998. "Le PIB potentiel des États-Unis et ses déterminants : la productivité de la main-d'oeuvre et le taux d'activité," Staff Working Papers 98-13, Bank of Canada.
    35. Ren, Yunwen & Xiao, Zhiguo & Zhang, Xinsheng, 2013. "Two-step adaptive model selection for vector autoregressive processes," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 349-364.
    36. Omer Ali Ibrahim & Sonal Devesh & Hisham Mohamed Hassan, 2019. "Sensitivity of Fiscal Balances to Oil Price Shocks: Short and Long Term Effects in the Context of Oman," International Journal of Energy Economics and Policy, Econjournals, vol. 9(2), pages 146-155.
    37. Abidemi Abiola & Rasak A. Adefabi, 2022. "Rural Structural Transformation and Agricultural Productivity in Nigeria," Athens Journal of Business & Economics, Athens Institute for Education and Research (ATINER), vol. 8(2), pages 119-138, April.
    38. W. Douglas McMillin & Keuk-Soo Kim, 2001. "Symmetric versus Asymmetric Lag Structures in Vector Autoregressive Models: A Monte Carlo Analysis with an Application to Estimating the Effects of Monetary Policy Shocks," Departmental Working Papers 2001-01, Department of Economics, Louisiana State University.
    39. Pierre St-Amant & David Tessier, 1998. "Tendance des dépenses publiques et de l'inflation et évolution comparative du taux de chômage au Canada et aux États-Unis," Staff Working Papers 98-3, Bank of Canada.
    40. Zernov, Serguei & Zinde-Walsh, Victoria & Galbraith, John W., 2009. "Asymptotics for estimation of quantile regressions with truncated infinite-dimensional processes," Journal of Multivariate Analysis, Elsevier, vol. 100(3), pages 497-508, March.
    41. Binet, Marie-Estelle & Pentecôte, Jean-Sébastien, 2015. "Macroeconomic idiosyncrasies and European monetary unification: A sceptical long run view," Economic Modelling, Elsevier, vol. 51(C), pages 412-423.
    42. Laing, Andrew R. & Nolan, James F., 2009. "Price Dynamics and Market Structure in Transportation: For-Hire Grain Trucking Along the Alberta- Saskatchewan Border," 50th Annual Transportation Research Forum, Portland, Oregon, March 16-18, 2009 207599, Transportation Research Forum.
    43. Marrouch, Walid & Mourad, Jana, 2019. "Effect of gasoline prices on car fuel efficiency: Evidence from Lebanon," Energy Policy, Elsevier, vol. 135(C).
    44. Betül Mutlugün, 2022. "Endogenous income distribution and aggregate demand: Empirical evidence from heterogeneous panel structural vector autoregression," Metroeconomica, Wiley Blackwell, vol. 73(2), pages 583-637, May.
    45. Carrasco Gutierrez, Carlos Enrique & Castro Souza, Reinaldo & Teixeira de Carvalho Guillén, Osmani, 2009. "Selection of optimal lag length in cointegrated VAR models with weak form of common cyclical features," MPRA Paper 22550, University Library of Munich, Germany.
    46. Gan‐Ochir Doojav & Davaasukh Damdinjav, 2023. "The macroeconomic effects of unconventional monetary policies in a commodity‐exporting economy: Evidence from Mongolia," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4627-4654, October.
    47. Pierre St-Amant & David Tessier, 1998. "A Discussion of the Reliability of Results Obtained with Long-Run Identifying Restrictions," Staff Working Papers 98-4, Bank of Canada.
    48. René Lalonde & Jennifer Page & Pierre St-Amant, 1998. "Une nouvelle méthode d'estimation de l'écart de production et son application aux États-Unis, au Canada et à l'Allemagne," Staff Working Papers 98-21, Bank of Canada.
    49. Kilian, Lutz & Chang, Pao-Li, 2000. "How accurate are confidence intervals for impulse responses in large VAR models?," Economics Letters, Elsevier, vol. 69(3), pages 299-307, December.
    50. Deven Bathia & Don Bredin & Dirk Nitzsche, 2016. "International Sentiment Spillovers in Equity Returns," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 21(4), pages 332-359, October.
    51. Main Ud-din, 2018. "Continuity and Change in Patriarchal Structure: Recent Trends in Rural Bangladesh," European Journal of Interdisciplinary Studies Articles, Revistia Research and Publishing, vol. 4, January -.
    52. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, June.
    53. Wei Yao & Weikun Zhang & Wenxiu Li & Penglong Li, 2022. "Measurement and Evaluation of Convergence of Japan’s Marine Fisheries and Marine Tourism," Sustainability, MDPI, vol. 14(15), pages 1-16, July.
    54. Nezir Kose & Nuri Ucar, 2006. "Effect of cross correlations in error terms on the model selection criteria for the stationary VAR process," Applied Economics Letters, Taylor & Francis Journals, vol. 13(4), pages 223-228.

  33. Mittnik, Stefan, 1991. "Derivation of the unconditional state-covariance matrix for exact maximum-likelihood estimation of ARMA models," Journal of Economic Dynamics and Control, Elsevier, vol. 15(4), pages 731-740, October.

    Cited by:

    1. Melard, Guy & Roy, Roch & Saidi, Abdessamad, 2006. "Exact maximum likelihood estimation of structured or unit root multivariate time series models," Computational Statistics & Data Analysis, Elsevier, vol. 50(11), pages 2958-2986, July.

  34. Mittnik, Stefan, 1990. "Macroeconomic forecasting experience with balanced state space models," International Journal of Forecasting, Elsevier, vol. 6(3), pages 337-348, October.

    Cited by:

    1. Mittnik, Stefan, 2013. "VaR-implied tail-correlation matrices," CFS Working Paper Series 2013/05, Center for Financial Studies (CFS).
    2. Najand, Mohammad & Noronha, Gregory, 1998. "Causal relations among stock returns, inflation, real activity, and interest rates: Evidence from Japan," Global Finance Journal, Elsevier, vol. 9(1), pages 71-80.
    3. 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.
    4. Michael Mosebach & Mohammad Najand, 1999. "Are The Structural Changes In Mutual Funds Investing Driving The U.S. Stock Market To Its Current Levels?," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 22(3), pages 317-329, September.
    5. Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
    6. Stefan Mittnik & Peter A. Zadrozny, 2004. "Forecasting Quarterly German GDP at Monthly Intervals Using Monthly IFO Business Conditions Data," CESifo Working Paper Series 1203, CESifo.
    7. Saxen, Henrik & Ostermark, Ralf, 1996. "State realization with exogenous variables - A test on blast furnace data," European Journal of Operational Research, Elsevier, vol. 89(1), pages 34-52, February.
    8. Donald S. Allen & Meenakshi Pasupathy, 1997. "A state space forecasting model with fiscal and monetary control," Working Papers 1997-017, Federal Reserve Bank of St. Louis.
    9. Najand, Mohammad & Bond, Charlotte, 2000. "Structural models of exchange rate determination," Journal of Multinational Financial Management, Elsevier, vol. 10(1), pages 15-27, January.

  35. Mittnik, Stefan, 1990. "Macroeconomic Forecasting Using Pooled International Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 205-208, April.

    Cited by:

    1. Peña, Daniel & Poncela, Pilar, 2000. "Forecasting with nostationary dynamic factor models," DES - Working Papers. Statistics and Econometrics. WS 9959, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Ash, J. C. K. & Smyth, D. J. & Heravi, S. M., 1997. "The accuracy of OECD forecasts of the international economy: balance of payments," Journal of International Money and Finance, Elsevier, vol. 16(6), pages 969-987, December.
    3. Ash, J. C. K. & Smyth, D. J. & Heravi, S. M., 1998. "Are OECD forecasts rational and useful?: a directional analysis," International Journal of Forecasting, Elsevier, vol. 14(3), pages 381-391, September.
    4. Antonio García Ferrer & Juan del Hoyo Bernat & Peter C. Young & Alfonso Novales Cinca, 1993. "Recursive identification, estimation and forecasting of nonstationary economic time series with applications to GNP international data," Documentos de Trabajo del ICAE 9310, Universidad Complutense de Madrid, Facultad de Ciencias Económicas y Empresariales, Instituto Complutense de Análisis Económico.

  36. Mittnik, Stefan, 1987. "Non-recursive methods for computing the coefficients of the autoregressive and the moving-average representation of mixed ARMA processes," Economics Letters, Elsevier, vol. 23(3), pages 279-284.

    Cited by:

    1. D.S. Poskitt & Wenying Yao, 2012. "VAR Modeling and Business Cycle Analysis: A Taxonomy of Errors," Monash Econometrics and Business Statistics Working Papers 11/12, Monash University, Department of Econometrics and Business Statistics.
    2. Menelaos Karanasos, "undated". "The Covariance Structure of Mixed ARMA Models," Discussion Papers 00/11, Department of Economics, University of York.
    3. Stefan Mittnik & Nikolay Robinzonov & Klaus Wohlrabe, 2013. "What Moves the DAX?," ifo Schnelldienst, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, vol. 66(23), pages 32-36, December.
    4. Pollock, D. S. G., 2003. "Recursive estimation in econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 37-75, October.

  37. Mittnik, Stefan, 1987. "The determination of the state covariance matrix of moving-average processes without computation," Economics Letters, Elsevier, vol. 23(2), pages 177-179.

    Cited by:

    1. Pollock, D. S. G., 2003. "Recursive estimation in econometrics," Computational Statistics & Data Analysis, Elsevier, vol. 44(1-2), pages 37-75, October.

Chapters

  1. Stefan Mittnik & Willi Semmler, 2014. "Estimating a Banking-Macro Model Using a Multi-regime VAR," Dynamic Modeling and Econometrics in Economics and Finance, in: Frauke Schleer-van Gellecom (ed.), Advances in Non-linear Economic Modeling, edition 127, pages 3-40, Springer.

    Cited by:

    1. Halvorsen, Jørn I. & Jacobsen, Dag Henning, 2016. "The bank-lending channel empirically revisited," Journal of Financial Stability, Elsevier, vol. 27(C), pages 95-105.
    2. Gaies, Brahim & Nakhli, Mohamed Sahbi & Ayadi, Rim & Sahut, Jean-Michel, 2022. "Exploring the causal links between investor sentiment and financial instability: A dynamic macro-financial analysis," Journal of Economic Behavior & Organization, Elsevier, vol. 204(C), pages 290-303.
    3. Ernst, Ekkehard & Semmler, Willi & Haider, Alexander, 2016. "Debt deflation, financial market stress and regime change: Evidence from Europe using MRVAR," ZEW Discussion Papers 16-030, ZEW - Leibniz Centre for European Economic Research.
    4. Barrales-Ruiz, Jose & Mohammed, Mikidadu, 2021. "Financial regimes and oil prices," Resources Policy, Elsevier, vol. 74(C).

  2. Markus Haas & Stefan Mittnik, 2009. "Portfolio Selection with Common Correlation Mixture Models," Contributions to Economics, in: Georg Bol & Svetlozar T. Rachev & Reinhold Würth (ed.), Risk Assessment, pages 47-76, Springer.

    Cited by:

    1. Mittnik, Stefan, 2013. "VaR-implied tail-correlation matrices," CFS Working Paper Series 2013/05, Center for Financial Studies (CFS).

  3. Stefan Mittnik & Peter Zadrozny, 2005. "Forecasting Quarterly German GDP at Monthly Intervals Using Monthly Ifo Business Conditions Data," Contributions to Economics, in: Jan-Egbert Sturm & Timo Wollmershäuser (ed.), Ifo Survey Data in Business Cycle and Monetary Policy Analysis, pages 19-48, Springer.
    See citations under working paper version above.
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