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Andréas Heinen
(Andreas Heinen)

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. M. Hamadi & A. Heinen, 2015. "Firm Performance when Ownership is very Concentrated: Evidence from a Semiparametric Panel," Working Paper CRENoS 201502, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

    Cited by:

    1. Zouaoui, Haykel & Mazioud, Manel & Ellouz, Nidhal Ziedi, 2018. "A semi-parametric panel data analysis on financial development-economic volatility nexus in developing countries," Economics Letters, Elsevier, vol. 172(C), pages 50-55.
    2. Maria Aluchna & Tomasz Kuszewski, 2021. "Do Financial Investors Mitigate Agency Problems? Evidence from an Emerging Market," European Research Studies Journal, European Research Studies Journal, vol. 0(2), pages 872-888.
    3. Florackis, Chris & Kanas, Angelos & Kostakis, Alexandros & Sainani, Sushil, 2020. "Idiosyncratic risk, risk-taking incentives and the relation between managerial ownership and firm value," European Journal of Operational Research, Elsevier, vol. 283(2), pages 748-766.
    4. Farroukh, Arafet & Mazioued, Manel & Pédussel Wu, Jennifer, 2024. "Revisiting the linkage between remittances inflow and economic growth: A semi-parametric estimation with panel data," IPE Working Papers 238/2024, Berlin School of Economics and Law, Institute for International Political Economy (IPE).
    5. Gopalakrishnan, Balagopal & Mohapatra, Sanket, 2019. "Insolvency Regimes and Firms' Default Risk Under Economic Uncertainty and Shocks," MPRA Paper 96283, University Library of Munich, Germany.
    6. Maria Aluchna & Tomasz Kuszewski, 2020. "Does Corporate Governance Compliance Increase Company Value? Evidence from the Best Practice of the Board," JRFM, MDPI, vol. 13(10), pages 1-21, October.
    7. Sami Ben Jabeur & Rabi Belhaj Hassine & Salma Mefteh‐Wali, 2021. "Firm financial performance during the financial crisis: A French case study," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2800-2812, April.
    8. Inmaculada Aguiar-Diaz & María Victoria Ruiz-Mallorquí & Lourdes Trujillo, 2020. "Ownership structure and financial performance of Spanish port service companies," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 22(4), pages 674-698, December.
    9. Joura, Essam & Xiao, Qin & Ullah, Subhan, 2021. "The impact of Say-on-Pay votes on firms' strategic policies: Insights from the Anglo-Saxon economy," International Review of Financial Analysis, Elsevier, vol. 73(C).
    10. González, Maximiliano & Guzmán, Alexander & Pablo, Eduardo & Trujillo, María-Andrea, 2019. "Is board turnover driven by performance in family firms?," Research in International Business and Finance, Elsevier, vol. 48(C), pages 169-186.
    11. Taylan Mavruk & Conny Overland & Stefan Sjögren, 2020. "Keeping it real or keeping it simple? Ownership concentration measures compared," European Financial Management, European Financial Management Association, vol. 26(4), pages 958-1005, September.
    12. Qichang Xie & Yingkun Yan & Xu Wang, 2023. "Assessing the role of foreign direct investment in environmental sustainability: a spatial semiparametric panel approach," Economic Change and Restructuring, Springer, vol. 56(2), pages 1263-1295, April.
    13. Mohamad Nur Utomo & Sugeng Wahyudi & Harjum Muharam & Maximus Leonardo Taolin, 2018. "Strategy To Improve Firm Performance Through Operational Efficiency Commitment To Environmental Friendliness: Evidence From Indonesia," Organizations and Markets in Emerging Economies, Faculty of Economics, Vilnius University, vol. 9(1).
    14. Nakabayashi, Masaki, 2019. "Ownership structure and market efficiency," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 189-212.

  2. Andréas Heinen & M. Hamadi & Guillermo Baquero, 2013. "Competition, Loan Rates and Information Dispersion in Microcredit Markets," Working Paper CRENoS 201314, Centre for North South Economic Research, University of Cagliari and Sassari, Sardinia.

    Cited by:

    1. Hailu Abebe Wondirad, 2022. "Interest rates in microfinance: What is a fair interest rate when we lend to the poor?," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(6), pages 4537-4548, December.
    2. Riekhof, Marie-Catherine, 2019. "The insurance premium in the interest rates of interlinked loans in a small-scale fishery," Environment and Development Economics, Cambridge University Press, vol. 24(1), pages 87-112, February.
    3. Gregor Dorfleitner & Michaela Leidl & Christopher Priberny & Jakob von Mosch, 2013. "What determines microcredit interest rates?," Applied Financial Economics, Taylor & Francis Journals, vol. 23(20), pages 1579-1597, October.
    4. Jonathan de Quidt & Thiemo Fetzer & Maitreesh Ghatak, 2018. "Market Structure and Borrower Welfare in Microfinance," Economic Journal, Royal Economic Society, vol. 128(610), pages 1019-1046, May.
    5. Beatriz Cu鬬ar-Fernᮤez & Yolanda Fuertes-Call鮠 & Carlos Serrano-Cinca & Bego uti鲲ez-Nieto, 2016. "Determinants of margin in microfinance institutions," Applied Economics, Taylor & Francis Journals, vol. 48(4), pages 300-311, January.
    6. Cull, Robert & Demirguc-Kunt, Asli & Morduch, Jonathan, 2009. "Banks and microbanks," Policy Research Working Paper Series 5078, The World Bank.
    7. Tchakoute Tchuigoua, Hubert, 2016. "Buffer capital in microfinance institutions," Journal of Business Research, Elsevier, vol. 69(9), pages 3523-3537.
    8. Abrego, Adriana & Guizar, Isai, 2017. "Resilience of Agricultural Microfinance Institutions to Rainfall Shocks," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258031, Agricultural and Applied Economics Association.
    9. Cull, Robert & Harten, Sven & Nishida, Ippei & Rusu, Anca Bogdana & Bull, Greta, 2015. "Benchmarking the financial performance, growth, and outreach of greenfield MFIs in Africa," Emerging Markets Review, Elsevier, vol. 25(C), pages 92-124.

  3. Stéphane GOUTTE & Benteng Zou, 2011. "Foreign exchange rates under Markov Regime switching model," DEM Discussion Paper Series 11-16, Department of Economics at the University of Luxembourg.

    Cited by:

    1. T. G. Saji, 2019. "Can BRICS Form a Currency Union? An Analysis under Markov Regime-Switching Framework," Global Business Review, International Management Institute, vol. 20(1), pages 151-165, February.
    2. Anatoliy Swishchuk & Maksym Tertychnyi & Robert Elliott, 2014. "Pricing Currency Derivatives with Markov-modulated Levy Dynamics," Papers 1402.1953, arXiv.org.
    3. Mendy, David & Widodo, Tri, 2018. "Two Stage Markov Switching Model: Identifying the Indonesian Rupiah Per US Dollar Turning Points Post 1997 Financial Crisis," MPRA Paper 86728, University Library of Munich, Germany.
    4. Anatoliy Swishchuk & Maksym Tertychnyi & Winsor Hoang, 2014. "Currency Derivatives Pricing for Markov-modulated Merton Jump-diffusion Spot Forex Rate," Papers 1402.2273, arXiv.org.

  4. HEINEN, Andréas & VALDESOGO, Alfonso, 2009. "Asymmetric CAPM dependence for large dimensions: the Canonical Vine Autoregressive Model," LIDAM Discussion Papers CORE 2009069, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Rand Kwong Yew Low, 2018. "Vine copulas: modelling systemic risk and enhancing higher‐moment portfolio optimisation," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(S1), pages 423-463, November.
    2. David E. Allen & Michael McAleer & Abhay K. Singh, 2017. "Risk Measurement and Risk Modelling Using Applications of Vine Copulas," Sustainability, MDPI, vol. 9(10), pages 1-34, September.
    3. Bartels, Mariana & Ziegelmann, Flavio A., 2016. "Market risk forecasting for high dimensional portfolios via factor copulas with GAS dynamics," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 66-79.
    4. Arreola Hernandez, Jose, 2014. "Are oil and gas stocks from the Australian market riskier than coal and uranium stocks? Dependence risk analysis and portfolio optimization," Energy Economics, Elsevier, vol. 45(C), pages 528-536.
    5. Brechmann, Eike Christian & Schepsmeier, Ulf, 2013. "Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i03).
    6. Arreola Hernandez, Jose & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Al Janabi, Mazin A. M. & Reboredo, Juan Carlos, 2014. "Global financial crisis and dependence risk analysis of sector portfolios: a vine copula approach," MPRA Paper 73399, University Library of Munich, Germany, revised Aug 2016.
    7. Satish Kumar & Aviral K. Tiwari & Ibrahim D. Raheem & Qiang Ji, 2019. "Dependence risk analysis in energy, agricultural and precious metals commodities: A pair vine copula approach," Research Africa Network Working Papers 19/092, Research Africa Network (RAN).
    8. Sahamkhadam, Maziar & Stephan, Andreas & Östermark, Ralf, 2022. "Copula-based Black–Litterman portfolio optimization," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1055-1070.
    9. Weiß, Gregor N.F. & Supper, Hendrik, 2013. "Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3334-3350.
    10. David E. Allen & Mohammad A. Ashraf & Michael McAleer & Robert J. Powell & Abhay K. Singh, 2013. "Financial Dependence Analysis: Applications of Vine Copulae," Tinbergen Institute Discussion Papers 13-022/III, Tinbergen Institute.
    11. Hanif, Waqas & Arreola Hernandez, Jose & Sadorsky, Perry & Yoon, Seong-Min, 2020. "Are the interdependence characteristics of the US and Canadian energy equity sectors nonlinear and asymmetric?," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    12. Maziar Sahamkhadam & Andreas Stephan, 2023. "Portfolio optimization based on forecasting models using vine copulas: An empirical assessment for global financial crises," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(8), pages 2139-2166, December.
    13. Jammazi, Rania & Tiwari, Aviral Kr. & Ferrer, Román & Moya, Pablo, 2015. "Time-varying dependence between stock and government bond returns: International evidence with dynamic copulas," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 74-93.
    14. Catherine Bruneau & Alexis Flageollet & Zhun Peng, 2020. "Economic and financial risk factors, copula dependence and risk sensitivity of large multi-asset class portfolios," Annals of Operations Research, Springer, vol. 284(1), pages 165-197, January.
    15. David Walsh-Jones & Daniel Jones & Christoph Reisinger, 2014. "Modelling of dependence in high-dimensional financial time series by cluster-derived canonical vines," Papers 1411.4970, arXiv.org.
    16. Weiß, Gregor N.F. & Scheffer, Marcus, 2015. "Mixture pair-copula-constructions," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 175-191.
    17. Stelios Bekiros & Shawkat Hammoudeh & Rania Jammazi & Duc Khuong Nguyen, 2018. "Sovereign bond market dependencies and crisis transmission around the eurozone debt crisis: a dynamic copula approach," Applied Economics, Taylor & Francis Journals, vol. 50(47), pages 5031-5049, October.
    18. Al Janabi, Mazin A.M. & Arreola Hernandez, Jose & Berger, Theo & Nguyen, Duc Khuong, 2017. "Multivariate dependence and portfolio optimization algorithms under illiquid market scenarios," European Journal of Operational Research, Elsevier, vol. 259(3), pages 1121-1131.
    19. Salaheddine El Adlouni, 2018. "Quantile regression C-vine copula model for spatial extremes," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 94(1), pages 299-317, October.
    20. Dißmann, J. & Brechmann, E.C. & Czado, C. & Kurowicka, D., 2013. "Selecting and estimating regular vine copulae and application to financial returns," Computational Statistics & Data Analysis, Elsevier, vol. 59(C), pages 52-69.
    21. Luca Riccetti, 2013. "A copula–GARCH model for macro asset allocation of a portfolio with commodities," Empirical Economics, Springer, vol. 44(3), pages 1315-1336, June.
    22. Bekiros, Stelios & Hernandez, Jose Arreola & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2015. "Multivariate dependence risk and portfolio optimization: An application to mining stock portfolios," Resources Policy, Elsevier, vol. 46(P2), pages 1-11.
    23. Tófoli, Paula Virgínia & Ziegelmann, Flávio Augusto & Silva Filho, Osvaldo Candido & Pereira, Pedro L. Valls, 2016. "Dynamic D-Vine copula model with applications to Value-at-Risk (VaR)," Textos para discussão 424, FGV EESP - Escola de Economia de São Paulo, Fundação Getulio Vargas (Brazil).
    24. Koliai, Lyes, 2016. "Extreme risk modeling: An EVT–pair-copulas approach for financial stress tests," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 1-22.
    25. Aepli, Matthias D. & Frauendorfer, Karl & Fuess, Roland & Paraschiv, Florentina, 2015. "Multivariate Dynamic Copula Models: Parameter Estimation and Forecast Evaluation," Working Papers on Finance 1513, University of St. Gallen, School of Finance.
    26. Min, Aleksey & Czado, Claudia, 2014. "SCOMDY models based on pair-copula constructions with application to exchange rates," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 523-535.
    27. Guillaume Arnould & Catherine Bruneau & Zhun Peng, 2015. "Liquidity and Equity Short term fragility: Stress-tests for the European banking system," Post-Print halshs-01254729, HAL.
    28. Hobæk Haff, Ingrid & Aas, Kjersti & Frigessi, Arnoldo & Lacal, Virginia, 2016. "Structure learning in Bayesian Networks using regular vines," Computational Statistics & Data Analysis, Elsevier, vol. 101(C), pages 186-208.
    29. Hans Manner & Olga Reznikova, 2012. "A Survey on Time-Varying Copulas: Specification, Simulations, and Application," Econometric Reviews, Taylor & Francis Journals, vol. 31(6), pages 654-687, November.
    30. Catherine Bruneau & Alexis Flageollet & Zhun Peng, 2015. "Risk Factors, Copula Dependence and Risk Sensitivity of a Large Portfolio," Documents de recherche 15-03, Centre d'Études des Politiques Économiques (EPEE), Université d'Evry Val d'Essonne.
    31. Brechmann Eike Christain & Czado Claudia, 2013. "Risk management with high-dimensional vine copulas: An analysis of the Euro Stoxx 50," Statistics & Risk Modeling, De Gruyter, vol. 30(4), pages 307-342, December.
    32. Nikoloulopoulos, Aristidis K. & Joe, Harry & Li, Haijun, 2012. "Vine copulas with asymmetric tail dependence and applications to financial return data," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3659-3673.
    33. Zhang, Bangzheng & Wei, Yu & Yu, Jiang & Lai, Xiaodong & Peng, Zhenfeng, 2014. "Forecasting VaR and ES of stock index portfolio: A Vine copula method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 416(C), pages 112-124.
    34. Kjersti Aas, 2016. "Pair-Copula Constructions for Financial Applications: A Review," Econometrics, MDPI, vol. 4(4), pages 1-15, October.
    35. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    36. Manner, Hans & Alavi Fard, Farzad & Pourkhanali, Armin & Tafakori, Laleh, 2019. "Forecasting the joint distribution of Australian electricity prices using dynamic vine copulae," Energy Economics, Elsevier, vol. 78(C), pages 143-164.
    37. Prayer M. Rikhotso & Beatrice D. Simo-Kengne, 2022. "Dependence Structures between Sovereign Credit Default Swaps and Global Risk Factors in BRICS Countries," JRFM, MDPI, vol. 15(3), pages 1-22, February.

  5. Sophie Chemarin & Andreas Heinen & Eric Strobl, 2008. "Electricity, carbon and weather in France: where do we stand ?," Working Papers hal-00340171, HAL.

    Cited by:

    1. M. Cummins, 2013. "Multiple comparisons problem: Recent advances applied to energy and emissions," Applied Economics Letters, Taylor & Francis Journals, vol. 20(9), pages 903-909, June.
    2. Fatemeh Nazifi, 2016. "The pass-through rates of carbon costs on to electricity prices within the Australian National Electricity Market," Environmental Economics and Policy Studies, Springer;Society for Environmental Economics and Policy Studies - SEEPS, vol. 18(1), pages 41-62, January.
    3. Moutinho, Victor & Vieira, Joel & Carrizo Moreira, António, 2011. "The crucial relationship among energy commodity prices: Evidence from the Spanish electricity market," Energy Policy, Elsevier, vol. 39(10), pages 5898-5908, October.
    4. Freitas, Carlos J. Pereira & Silva, Patrícia Pereira da, 2015. "European Union emissions trading scheme impact on the Spanish electricity price during phase II and phase III implementation," Utilities Policy, Elsevier, vol. 33(C), pages 54-62.

  6. CHOLLETE, Loran & HEINEN, Andréas & VALDESOGO, Alfonso, 2008. "Modeling international financial returns with a multivariate regime switching copula," LIDAM Discussion Papers CORE 2008013, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. David E. Allen & Michael McAleer & Abhay K. Singh, 2017. "Risk Measurement and Risk Modelling Using Applications of Vine Copulas," Sustainability, MDPI, vol. 9(10), pages 1-34, September.
    2. Andréas Heinen & Mi Lim Kim & Alfonso Valdesogo, 2015. "Regime switching House price dependence: Evidence from MSAs in the US," ERES eres2015_201, European Real Estate Society (ERES).
    3. Stöber, Jakob & Czado, Claudia, 2014. "Regime switches in the dependence structure of multidimensional financial data," Computational Statistics & Data Analysis, Elsevier, vol. 76(C), pages 672-686.
    4. Canela Miguel-Angel & Pedreira Eduardo, 2012. "Modelling Dependence in Latin American Markets Using Copula Functions," Journal of Emerging Market Finance, Institute for Financial Management and Research, vol. 11(3), pages 231-270, December.
    5. Cathy Ning & Loran Chollete, 2012. "Asymmetric Dependence between Aggregate Consumption and Financial Risk," Working Papers 046, Toronto Metropolitan University, Department of Economics.
    6. Syed Abul, Basher & Salem, Nechi & Hui, Zhu, 2014. "Dependence patterns across Gulf Arab stock markets: a copula approach," MPRA Paper 56566, University Library of Munich, Germany.
    7. Małgorzata Doman & Ryszard Doman, 2013. "Dynamic linkages between stock markets: the effects of crises and globalization," Portuguese Economic Journal, Springer;Instituto Superior de Economia e Gestao, vol. 12(2), pages 87-112, August.
    8. Chollete, Lorán & de la Peña, Victor & Lu, Ching-Chih, 2012. "International diversification: An extreme value approach," Journal of Banking & Finance, Elsevier, vol. 36(3), pages 871-885.
    9. Brechmann, Eike Christian & Schepsmeier, Ulf, 2013. "Modeling Dependence with C- and D-Vine Copulas: The R Package CDVine," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 52(i03).
    10. Arreola Hernandez, Jose & Hammoudeh, Shawkat & Nguyen, Duc Khuong & Al Janabi, Mazin A. M. & Reboredo, Juan Carlos, 2014. "Global financial crisis and dependence risk analysis of sector portfolios: a vine copula approach," MPRA Paper 73399, University Library of Munich, Germany, revised Aug 2016.
    11. Yuhao Liu & Petar M. Djurić & Young Shin Kim & Svetlozar T. Rachev & James Glimm, 2021. "Systemic Risk Modeling with Lévy Copulas," JRFM, MDPI, vol. 14(6), pages 1-20, June.
    12. Su, EnDer, 2014. "Measuring Contagion Risk in High Volatility State between Major Banks in Taiwan by Threshold Copula GARCH Model," MPRA Paper 58161, University Library of Munich, Germany.
    13. Chollete, Loran, 2011. "A Model of Endogenous Extreme Events," UiS Working Papers in Economics and Finance 2012/2, University of Stavanger.
    14. Qingfu Liu & Yiuman Tse & Kaixin Zheng, 2021. "The impact of trading behavioral biases on market liquidity under different volatility levels: Evidence from the Chinese commodity futures market," The Financial Review, Eastern Finance Association, vol. 56(4), pages 671-692, November.
    15. Pablo Jose Campos de Carvalho & Aparna Gupta, 2018. "Multivariate Jump Diffusion Model with Markovian Contagion," Working Papers Series 482, Central Bank of Brazil, Research Department.
    16. Albulescu, Claudiu Tiberiu & Tiwari, Aviral Kumar & Ji, Qiang, 2020. "Copula-based local dependence among energy, agriculture and metal commodities markets," Energy, Elsevier, vol. 202(C).
    17. Weiß, Gregor N.F. & Supper, Hendrik, 2013. "Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3334-3350.
    18. Frédy Valé Manuel Pokou & Jules Sadefo Kamdem & François Benhmad, 2023. "Empirical Performance of an ESG Assets Portfolio from US Market," Post-Print hal-04312348, HAL.
    19. 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.
    20. Holger Fink & Yulia Klimova & Claudia Czado & Jakob Stober, 2016. "Regime switching vine copula models for global equity and volatility indices," Papers 1604.05598, arXiv.org.
    21. Govindan, Rajesh & Al-Ansari, Tareq, 2019. "Computational decision framework for enhancing resilience of the energy, water and food nexus in risky environments," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 653-668.
    22. Zhu, Bo & Lin, Renda & Deng, Yuanyue & Chen, Pingshe & Chevallier, Julien, 2021. "Intersectoral systemic risk spillovers between energy and agriculture under the financial and COVID-19 crises," Economic Modelling, Elsevier, vol. 105(C).
    23. David E. Allen & Mohammad A. Ashraf & Michael McAleer & Robert J. Powell & Abhay K. Singh, 2013. "Financial Dependence Analysis: Applications of Vine Copulae," Tinbergen Institute Discussion Papers 13-022/III, Tinbergen Institute.
    24. Hanif, Waqas & Arreola Hernandez, Jose & Sadorsky, Perry & Yoon, Seong-Min, 2020. "Are the interdependence characteristics of the US and Canadian energy equity sectors nonlinear and asymmetric?," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    25. Claudiu Albulescu & Aviral Tiwari & Qiang Ji, 2020. "Copula-based local dependence between energy, agriculture and metal commodity markets," Papers 2003.04007, arXiv.org.
    26. Tachibana, Minoru, 2022. "Safe haven assets for international stock markets: A regime-switching factor copula approach," Research in International Business and Finance, Elsevier, vol. 60(C).
    27. Chang, Kuang-Liang, 2023. "The low-magnitude and high-magnitude asymmetries in tail dependence structures in international equity markets and the role of bilateral exchange rate," Journal of International Money and Finance, Elsevier, vol. 133(C).
    28. Yang, Bingduo & Hafner, Christian M. & Liu, Guannan & Long, Wei, 2022. "Semiparametric estimation and variable selection for single-index copula models," LIDAM Reprints ISBA 2022011, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    29. Sleire, Anders D. & Støve, Bård & Otneim, Håkon & Berentsen, Geir Drage & Tjøstheim, Dag & Haugen, Sverre Hauso, 2022. "Portfolio allocation under asymmetric dependence in asset returns using local Gaussian correlations," Finance Research Letters, Elsevier, vol. 46(PB).
    30. Donatien Hainaut & Yang Shen & Yan Zeng, 2018. "How do capital structure and economic regime affect fair prices of bank’s equity and liabilities?," Annals of Operations Research, Springer, vol. 262(2), pages 519-545, March.
    31. Yuting Gong & Xueqin Wang & Mo Zhu & Ying‐En Ge & Wenming Shi, 2023. "Maximum utility portfolio construction in the forward freight agreement markets: Evidence from a multivariate skewed t copula," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(1), pages 69-89, January.
    32. Dominique Guegan & Pierre-André Maugis, 2010. "An Econometric Study of Vine Copulas," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00492124, HAL.
    33. Mauro Bernardi & Leopoldo Catania, 2015. "Switching-GAS Copula Models With Application to Systemic Risk," Papers 1504.03733, arXiv.org, revised Jan 2016.
    34. Peter Christoffersen & Hugues Langlois, 2011. "The Joint Dynamics of Equity Market Factors," CREATES Research Papers 2011-45, Department of Economics and Business Economics, Aarhus University.
    35. Hendriks, Johannes Jurgens & Bonga-Bonga, Lumengo, 2020. "Sectoral dependence and contagion in the BRICS grouping: an application of the R-Vine copulas," MPRA Paper 102473, University Library of Munich, Germany.
    36. Liu, Mengqiao & Zhang, Yu Yvette & Jia, Ruixin, 2024. "Is the Chinese gold product a hedge or safe haven for Chinese overseas investors?," 2024 Annual Meeting, July 28-30, New Orleans, LA 343698, Agricultural and Applied Economics Association.
    37. Atenga, Eric Martial Etoundi & Mougoué, Mbodja, 2021. "Return and volatility spillovers to African currencies markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 73(C).
    38. Jamal Bouoiyour & Refk Selmi & Shawkat Hammoudeh & Mark E Wohar, 2019. "What are the categories of geopolitical risks that could drive oil prices higher? Acts or threats?," Post-Print hal-02409062, HAL.
    39. Oleg Sokolinskiy & Dick van Dijk, 2011. "Forecasting Volatility with Copula-Based Time Series Models," Tinbergen Institute Discussion Papers 11-125/4, Tinbergen Institute.
    40. Hainaut, Donatien, 2014. "Impulse control of pension fund contributions, in a regime switching economy," European Journal of Operational Research, Elsevier, vol. 239(3), pages 810-819.
    41. Travkin, Alexandr, 2013. "Pair copula constructions in portfolio optimization ploblem," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 32(4), pages 110-133.
    42. Aepli, Matthias D. & Füss, Roland & Henriksen, Tom Erik S. & Paraschiv, Florentina, 2017. "Modeling the multivariate dynamic dependence structure of commodity futures portfolios," Journal of Commodity Markets, Elsevier, vol. 6(C), pages 66-87.
    43. Nathan Lael Joseph & Thi Thuy Anh Vo & Asma Mobarek & Sabur Mollah, 2020. "Volatility and asymmetric dependence in Central and East European stock markets," Review of Quantitative Finance and Accounting, Springer, vol. 55(4), pages 1241-1303, November.
    44. Weiß, Gregor N.F. & Scheffer, Marcus, 2015. "Mixture pair-copula-constructions," Journal of Banking & Finance, Elsevier, vol. 54(C), pages 175-191.
    45. Minoru Tachibana, 2020. "Flight-to-quality in the stock–bond return relation: a regime-switching copula approach," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 34(4), pages 429-470, December.
    46. René Garcia & Georges Tsafack, 2009. "Dependence Structure and Extreme Comovements in International Equity and Bond Markets," CIRANO Working Papers 2009s-21, CIRANO.
    47. Gong, Yuting & Li, Kevin X. & Chen, Shu-Ling & Shi, Wenming, 2020. "Contagion risk between the shipping freight and stock markets: Evidence from the recent US-China trade war," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    48. Ojea Ferreiro, Javier, 2020. "Disentangling the role of the exchange rate in oil-related scenarios for the European stock market," Energy Economics, Elsevier, vol. 89(C).
    49. Diks, Cees & Fang, Hao, 2020. "Comparing density forecasts in a risk management context," International Journal of Forecasting, Elsevier, vol. 36(2), pages 531-551.
    50. Su, Xiaoshan & Bai, Manying & Han, Yingwei, 2021. "Robust portfolio selection with regime switching and asymmetric dependence," Economic Modelling, Elsevier, vol. 99(C).
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    110. Michael A. Goldstein & Joseph McCarthy & Alexei G. Orlov, 2019. "The Core, Periphery, and Beyond: Stock Market Comovements among EU and Non‐EU Countries," The Financial Review, Eastern Finance Association, vol. 54(1), pages 5-56, February.
    111. Henryk Gurgul & Artur Machno, 2015. "Regime-Dependent Relationships among Stock Markets in Frankfurt, Vienna and Warsaw," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 13(1 (Spring), pages 3-25.
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    124. Dominique Guegan & Pierre-André Maugis, 2011. "An econometric Study for Vine Copulas," PSE-Ecole d'économie de Paris (Postprint) halshs-00645799, HAL.
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  7. Barrios, Salvador & Bertinelli, Luisito & Heinen, Andreas, 2007. "Exploring The Link Between Local And Global Knowledge Spillovers," MPRA Paper 6239, University Library of Munich, Germany.

    Cited by:

    1. Santos, Eleonora, 2017. "Externalities from FDI on domestic firms’ Productivity: A Literature Review for Developed Countries," MPRA Paper 88958, University Library of Munich, Germany.
    2. Burgi, Constantin & Gorgulu, Nisan, 2021. "The Impact of the Spatial Population Distribution on Economic Growth," Working Papers 17-2021, Copenhagen Business School, Department of Economics.
    3. Cheshire, Paul & Magrini, Stefano, 2008. "Urban growth drivers in a Europe of sticky people and implicit boundaries," LSE Research Online Documents on Economics 30774, London School of Economics and Political Science, LSE Library.
    4. Syeda Tamkeen Fatima, 2016. "Productivity spillovers from foreign direct investment: evidence from Turkish micro-level data," The Journal of International Trade & Economic Development, Taylor & Francis Journals, vol. 25(3), pages 291-324, June.
    5. Paul C. Cheshire and Stefano Magrini, 2009. "Urban Growth Drivers and Spatial Inequalities: Europe - a Case with Geographically Sticky People," Europe in Question Discussion Paper Series of the London School of Economics (LEQs) 1, London School of Economics / European Institute.
    6. Eberhardt, Markus & Helmers, Christian & Strauss, Hubert, 2010. "Do spillovers matter when estimating private returns to R&D?," Economic and Financial Reports 2010/1, European Investment Bank, Economics Department.
    7. Nuno Crespo & Isabel Proença & Maria Paula Fontoura, 2010. "The Spatial Dimension in FDI Spillovers: Evidence at the Regional Level from Portugal," Working Papers Department of Economics 2010/17, ISEG - Lisbon School of Economics and Management, Department of Economics, Universidade de Lisboa.
    8. Harald Badinger & Peter Egger, 2010. "Horizontal vs. Vertical Interdependence in Multinational Activity," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(6), pages 744-768, December.
    9. Muhammad Ali & Uwe Cantner & Ipsita Roy, 2016. "Knowledge spillovers through FDI and trade: the moderating role of quality-adjusted human capital," Journal of Evolutionary Economics, Springer, vol. 26(4), pages 837-868, October.
    10. Constantin Bürgi & Nisan Gorgulu, 2022. "The Impact of the Spatial Population Distribution on Economic Growth: Evidence from the United States," CESifo Working Paper Series 10008, CESifo.

  8. Chollete, Lorán & Heinen, Andreas, 2006. "Frequent Turbulence? A Dynamic Copula Approach," Discussion Papers 2006/10, Norwegian School of Economics, Department of Business and Management Science.

    Cited by:

    1. Penikas, Henry & Simakova, Varvara, 2009. "Interest Rate Risk Management Based on Copula-GARCH Models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 13(1), pages 3-36.
    2. Penikas, H., 2010. "Financial Applications of Copula-Models," Journal of the New Economic Association, New Economic Association, issue 7, pages 24-44.

  9. Erick Rengifo & Andresas Heinen, 2004. "Comovements in Trading activity: A Multivariate Autoregressive Model of Time Series Count Data Using Copulas," Econometric Society 2004 Far Eastern Meetings 755, Econometric Society.

    Cited by:

    1. Large, Jeremy, 2007. "Measuring the resiliency of an electronic limit order book," Journal of Financial Markets, Elsevier, vol. 10(1), pages 1-25, February.

  10. HEINEN, Andréas & RENGIFO, Erick, 2004. "Multivariate reduced rank regression in non-Gaussian contexts, using copulas," LIDAM Discussion Papers CORE 2004032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Mike Vuolo, 2017. "Copula Models for Sociology: Measures of Dependence and Probabilities for Joint Distributions," Sociological Methods & Research, , vol. 46(3), pages 604-648, August.
    2. Yee, Thomas W., 2014. "Reduced-rank vector generalized linear models with two linear predictors," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 889-902.
    3. Ben Omrane, Walid & Heinen, Andréas, 2010. "Public news announcements and quoting activity in the Euro/Dollar foreign exchange market," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2419-2431, November.

  11. Grammig, Joachin & Heinen, Andreas & Rengifo, Erick, 2004. "Trading activity and liquidity supply in a pure limit order book market: An empirical analysis using a multivariate count data model," MPRA Paper 8115, University Library of Munich, Germany.

    Cited by:

    1. Johannes Bleher & Michael Bleher & Thomas Dimpfl, 2020. "From orders to prices: A stochastic description of the limit order book to forecast intraday returns," Papers 2004.11953, arXiv.org, revised May 2021.
    2. Giampaoli, Iacopo & Ng, Wing Lon & Constantinou, Nick, 2009. "Analysis of ultra-high-frequency financial data using advanced Fourier transforms," Finance Research Letters, Elsevier, vol. 6(1), pages 47-53, March.
    3. Kempf, Alexander & Mayston, Daniel, 2006. "Liquidity commonality beyond best prices," CFR Working Papers 06-04, University of Cologne, Centre for Financial Research (CFR).

  12. GRAMMIG, Joachim & HEINEN, Andréas & RENGIFO, Erick, 2004. "Trading activity and liquidity supply in a pure limit order book market," LIDAM Discussion Papers CORE 2004058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Johannes Bleher & Michael Bleher & Thomas Dimpfl, 2020. "From orders to prices: A stochastic description of the limit order book to forecast intraday returns," Papers 2004.11953, arXiv.org, revised May 2021.
    2. Aitken, Michael & Almeida, Niall & deB. Harris, Frederick H. & McInish, Thomas H., 2007. "Liquidity supply in electronic markets," Journal of Financial Markets, Elsevier, vol. 10(2), pages 144-168, May.
    3. Pagliacci, Carolina, 2006. "The Venezuelan Overnight Fund Market: Understanding a Credit Constraint Limit Order Market," MPRA Paper 106541, University Library of Munich, Germany.
    4. Giampaoli, Iacopo & Ng, Wing Lon & Constantinou, Nick, 2009. "Analysis of ultra-high-frequency financial data using advanced Fourier transforms," Finance Research Letters, Elsevier, vol. 6(1), pages 47-53, March.
    5. Kempf, Alexander & Mayston, Daniel, 2006. "Liquidity commonality beyond best prices," CFR Working Papers 06-04, University of Cologne, Centre for Financial Research (CFR).

  13. HEINEN, Andreas & RENGIFO, Erick, 2003. "Multivariate modelling of time series count data: an autoregressive conditional Poisson model," LIDAM Discussion Papers CORE 2003025, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. James W. Taylor, 2012. "Density Forecasting of Intraday Call Center Arrivals Using Models Based on Exponential Smoothing," Management Science, INFORMS, vol. 58(3), pages 534-549, March.
    2. Weiß, Christian H. & Zhu, Fukang, 2024. "Conditional-mean multiplicative operator models for count time series," Computational Statistics & Data Analysis, Elsevier, vol. 191(C).
    3. Aknouche, Abdelhakim & Almohaimeed, Bader & Dimitrakopoulos, Stefanos, 2020. "Forecasting transaction counts with integer-valued GARCH models," MPRA Paper 101779, University Library of Munich, Germany, revised 11 Jul 2020.
    4. Aknouche, Abdelhakim & Bendjeddou, Sara, 2016. "Negative binomial quasi-likelihood inference for general integer-valued time series models," MPRA Paper 76574, University Library of Munich, Germany, revised 03 Feb 2017.
    5. Xu, Hai-Yan & Xie, Min & Goh, Thong Ngee & Fu, Xiuju, 2012. "A model for integer-valued time series with conditional overdispersion," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4229-4242.
    6. Aknouche, Abdelhakim & Francq, Christian, 2023. "Two-stage weighted least squares estimator of the conditional mean of observation-driven time series models," Journal of Econometrics, Elsevier, vol. 237(2).
    7. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "Predicting bid-ask spreads using long memory autoregressive conditional poisson models," SFB 649 Discussion Papers 2011-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    8. HEINEN, Andréas & RENGIFO, Erick, 2004. "Multivariate reduced rank regression in non-Gaussian contexts, using copulas," LIDAM Discussion Papers CORE 2004032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Vladim'ir Hol'y & Petra Tomanov'a, 2021. "Modeling Price Clustering in High-Frequency Prices," Papers 2102.12112, arXiv.org, revised Mar 2021.
    10. Sun, Yiqun & Ji, Hao & Cai, Xiurong & Li, Jiangchen, 2023. "Joint extreme risk of energy prices-evidence from European energy markets," Finance Research Letters, Elsevier, vol. 56(C).
    11. Mirko Armillotta & Paolo Gorgi, 2023. "Pseudo-variance quasi-maximum likelihood estimation of semi-parametric time series models," Tinbergen Institute Discussion Papers 23-054/III, Tinbergen Institute.
    12. Peter Congdon, 2022. "A spatio-temporal autoregressive model for monitoring and predicting COVID infection rates," Journal of Geographical Systems, Springer, vol. 24(4), pages 583-610, October.
    13. Giulia Carallo & Roberto Casarin & Christian P. Robert, 2020. "Generalized Poisson Difference Autoregressive Processes," Papers 2002.04470, arXiv.org.
    14. Daniel L. R. Orozco & Lucas O. F. Sales & Luz M. Z. Fernández & André L. S. Pinho, 2021. "A new mixed first-order integer-valued autoregressive process with Poisson innovations," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(4), pages 559-580, December.
    15. Juan Dolado, 2012. "Comments on: Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 442-446, September.
    16. Weiß, Gregor N.F. & Supper, Hendrik, 2013. "Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3334-3350.
    17. Ivanov, Vladimir & Lewis, Craig M., 2008. "The determinants of market-wide issue cycles for initial public offerings," Journal of Corporate Finance, Elsevier, vol. 14(5), pages 567-583, December.
    18. Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
    19. Quoreshi, Shahiduzzaman, 2005. "Modelling High Frequency Financial Count Data," Umeå Economic Studies 656, Umeå University, Department of Economics.
    20. Christian Weiß & Hee-Young Kim, 2013. "Parameter estimation for binomial AR(1) models with applications in finance and industry," Statistical Papers, Springer, vol. 54(3), pages 563-590, August.
    21. Fokianos, Konstantinos, 2024. "Multivariate Count Time Series Modelling," Econometrics and Statistics, Elsevier, vol. 31(C), pages 100-116.
    22. Aknouche, Abdelhakim & Scotto, Manuel, 2022. "A multiplicative thinning-based integer-valued GARCH model," MPRA Paper 112475, University Library of Munich, Germany.
    23. Weiß, Christian H., 2010. "INARCH(1) processes: Higher-order moments and jumps," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1771-1780, December.
    24. Abdelhakim Aknouche & Stefanos Dimitrakopoulos, 2023. "Autoregressive conditional proportion: A multiplicative‐error model for (0,1)‐valued time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(4), pages 393-417, July.
    25. Brännäs, Kurt & Quoreshi, Shahiduzzaman, 2004. "Integer-Valued Moving Average Modelling of the Number of Transactions in Stocks," Umeå Economic Studies 637, Umeå University, Department of Economics.
    26. Mawuli Segnon & Manuel Stapper, 2019. "Long Memory Conditional Heteroscedasticity in Count Data," CQE Working Papers 8219, Center for Quantitative Economics (CQE), University of Muenster.
    27. Aknouche, Abdelhakim & Francq, Christian, 2020. "Stationarity and ergodicity of Markov switching positive conditional mean models," MPRA Paper 102503, University Library of Munich, Germany.
    28. Christian H. Weiß & Esmeralda Gonçalves & Nazaré Mendes Lopes, 2017. "Testing the compounding structure of the CP-INARCH model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(5), pages 571-603, July.
    29. Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
    30. Dag Tjøstheim, 2012. "Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 413-438, September.
    31. Aknouche, Abdelhakim & Gouveia, Sonia & Scotto, Manuel, 2023. "Random multiplication versus random sum: auto-regressive-like models with integer-valued random inputs," MPRA Paper 119518, University Library of Munich, Germany, revised 18 Dec 2023.
    32. Christian H. Weiß & Sebastian Schweer, 2015. "Detecting overdispersion in INARCH(1) processes," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(3), pages 281-297, August.
    33. Jung, Robert & Kukuk, Martin & Liesenfeld, Roman, 2005. "Time Series of Count Data: Modelling and Estimation," Economics Working Papers 2005-08, Christian-Albrechts-University of Kiel, Department of Economics.
    34. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2021. "Autoregressive conditional proportion: A multiplicative-error model for (0,1)-valued time series," MPRA Paper 110954, University Library of Munich, Germany, revised 06 Dec 2021.
    35. Fokianos, Konstantinos & Fried, Roland & Kharin, Yuriy & Voloshko, Valeriy, 2022. "Statistical analysis of multivariate discrete-valued time series," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    36. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.
    37. Youngmi Lee & Sangyeol Lee & Dag Tjøstheim, 2018. "Asymptotic normality and parameter change test for bivariate Poisson INGARCH models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(1), pages 52-69, March.
    38. Feigin, Paul D. & Gould, Phillip & Martin, Gael M. & Snyder, Ralph D., 2008. "Feasible parameter regions for alternative discrete state space models," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2963-2970, December.
    39. A. M. M. Shahiduzzaman Quoreshi & Reaz Uddin & Naushad Mamode Khan, 2019. "Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data—Under Conditional Heteroskedasticity Framework," JRFM, MDPI, vol. 12(2), pages 1-13, April.
    40. Weiß, Christian H., 2024. "On higher-order moments of INGARCH processes," Statistics & Probability Letters, Elsevier, vol. 214(C).
    41. Mamode Khan Naushad & Rumjaun Wasseem & Sunecher Yuvraj & Jowaheer Vandna, 2017. "Computing with bivariate COM-Poisson model under different copulas," Monte Carlo Methods and Applications, De Gruyter, vol. 23(2), pages 131-146, June.
    42. GRAMMIG, Joachim & HEINEN, Andréas & RENGIFO, Erick, 2004. "Trading activity and liquidity supply in a pure limit order book market," LIDAM Discussion Papers CORE 2004058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    43. Ghahramani, M. & Thavaneswaran, A., 2009. "On some properties of Autoregressive Conditional Poisson (ACP) models," Economics Letters, Elsevier, vol. 105(3), pages 273-275, December.
    44. Ali Ahmad & Christian Francq, 2015. "Poisson QMLE of Count Time Series Models," Post-Print hal-01533548, HAL.
    45. Weiß, Christian H. & Schweer, Sebastian, 2016. "Bias corrections for moment estimators in Poisson INAR(1) and INARCH(1) processes," Statistics & Probability Letters, Elsevier, vol. 112(C), pages 124-130.
    46. Lee, Sangyeol & Kim, Dongwon & Kim, Byungsoo, 2023. "Modeling and inference for multivariate time series of counts based on the INGARCH scheme," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
    47. Cattivelli, Luca & Pirino, Davide, 2019. "A SHARP model of bid–ask spread forecasts," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1211-1225.
    48. Konstantinos Fokianos & Roland Fried, 2010. "Interventions in INGARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(3), pages 210-225, May.
    49. Ralph D. Snyder & Gael M. Martin & Phillip Gould & Paul D. Feigin, 2007. "An Assessment of Alternative State Space Models for Count Time Series," Monash Econometrics and Business Statistics Working Papers 4/07, Monash University, Department of Econometrics and Business Statistics.
    50. Pedeli, Xanthi & Karlis, Dimitris, 2013. "Some properties of multivariate INAR(1) processes," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 213-225.
    51. Christian H. Weiß, 2017. "On Eigenvalues of the Transition Matrix of Some Count-Data Markov Chains," Methodology and Computing in Applied Probability, Springer, vol. 19(3), pages 997-1007, September.
    52. Luiza S. C. Piancastelli & Wagner Barreto‐Souza & Hernando Ombao, 2023. "Flexible bivariate INGARCH process with a broad range of contemporaneous correlation," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 206-222, March.
    53. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2024. "Volatility models versus intensity models: analogy and differences," MPRA Paper 122528, University Library of Munich, Germany.
    54. Christian Weiß, 2009. "Modelling time series of counts with overdispersion," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(4), pages 507-519, November.
    55. Youngmi Lee & Sangyeol Lee, 2019. "CUSUM test for general nonlinear integer-valued GARCH models: comparison study," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(5), pages 1033-1057, October.

  14. BEN OMRANE, Walid & HEINEN, Andréas, 2003. "The response of individual FX dealers'quoting activity to macroeconomic news announcements," LIDAM Discussion Papers CORE 2003070, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. Áron Gereben & György Gyomai & Norbert Kiss M., 2005. "The microstructure approach to exchange rates: a survey from a central bank’s viewpoint," MNB Occasional Papers 2005/42, Magyar Nemzeti Bank (Central Bank of Hungary).

  15. HEINEN, Andréas, 2003. "Modelling time series count data: an autoregressive conditional Poisson model," LIDAM Discussion Papers CORE 2003062, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).

    Cited by:

    1. James W. Taylor, 2012. "Density Forecasting of Intraday Call Center Arrivals Using Models Based on Exponential Smoothing," Management Science, INFORMS, vol. 58(3), pages 534-549, March.
    2. Jung, Robert & Liesenfeld, Roman & Richard, Jean-François, 2008. "Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity," Economics Working Papers 2008-12, Christian-Albrechts-University of Kiel, Department of Economics.
    3. Weiß, Christian H. & Zhu, Fukang, 2024. "Conditional-mean multiplicative operator models for count time series," Computational Statistics & Data Analysis, Elsevier, vol. 191(C).
    4. Aknouche, Abdelhakim & Almohaimeed, Bader & Dimitrakopoulos, Stefanos, 2020. "Forecasting transaction counts with integer-valued GARCH models," MPRA Paper 101779, University Library of Munich, Germany, revised 11 Jul 2020.
    5. Aknouche, Abdelhakim & Bendjeddou, Sara, 2016. "Negative binomial quasi-likelihood inference for general integer-valued time series models," MPRA Paper 76574, University Library of Munich, Germany, revised 03 Feb 2017.
    6. Xu, Hai-Yan & Xie, Min & Goh, Thong Ngee & Fu, Xiuju, 2012. "A model for integer-valued time series with conditional overdispersion," Computational Statistics & Data Analysis, Elsevier, vol. 56(12), pages 4229-4242.
    7. Aknouche, Abdelhakim & Francq, Christian, 2023. "Two-stage weighted least squares estimator of the conditional mean of observation-driven time series models," Journal of Econometrics, Elsevier, vol. 237(2).
    8. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "Predicting bid-ask spreads using long memory autoregressive conditional poisson models," SFB 649 Discussion Papers 2011-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    9. HEINEN, Andréas & RENGIFO, Erick, 2004. "Multivariate reduced rank regression in non-Gaussian contexts, using copulas," LIDAM Discussion Papers CORE 2004032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    10. Vladim'ir Hol'y & Petra Tomanov'a, 2021. "Modeling Price Clustering in High-Frequency Prices," Papers 2102.12112, arXiv.org, revised Mar 2021.
    11. Sun, Yiqun & Ji, Hao & Cai, Xiurong & Li, Jiangchen, 2023. "Joint extreme risk of energy prices-evidence from European energy markets," Finance Research Letters, Elsevier, vol. 56(C).
    12. Mirko Armillotta & Paolo Gorgi, 2023. "Pseudo-variance quasi-maximum likelihood estimation of semi-parametric time series models," Tinbergen Institute Discussion Papers 23-054/III, Tinbergen Institute.
    13. Peter Congdon, 2022. "A spatio-temporal autoregressive model for monitoring and predicting COVID infection rates," Journal of Geographical Systems, Springer, vol. 24(4), pages 583-610, October.
    14. Heinen, Andreas & Rengifo, Erick, 2007. "Multivariate autoregressive modeling of time series count data using copulas," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 564-583, September.
    15. Giulia Carallo & Roberto Casarin & Christian P. Robert, 2020. "Generalized Poisson Difference Autoregressive Processes," Papers 2002.04470, arXiv.org.
    16. Daniel L. R. Orozco & Lucas O. F. Sales & Luz M. Z. Fernández & André L. S. Pinho, 2021. "A new mixed first-order integer-valued autoregressive process with Poisson innovations," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 105(4), pages 559-580, December.
    17. Juan Dolado, 2012. "Comments on: Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 442-446, September.
    18. Weiß, Gregor N.F. & Supper, Hendrik, 2013. "Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3334-3350.
    19. Snyder, Ralph D. & Ord, J. Keith & Beaumont, Adrian, 2012. "Forecasting the intermittent demand for slow-moving inventories: A modelling approach," International Journal of Forecasting, Elsevier, vol. 28(2), pages 485-496.
    20. Quoreshi, Shahiduzzaman, 2005. "Modelling High Frequency Financial Count Data," Umeå Economic Studies 656, Umeå University, Department of Economics.
    21. Christian Weiß & Hee-Young Kim, 2013. "Parameter estimation for binomial AR(1) models with applications in finance and industry," Statistical Papers, Springer, vol. 54(3), pages 563-590, August.
    22. Tianqing Liu & Xiaohui Yuan, 2013. "Random rounded integer-valued autoregressive conditional heteroskedastic process," Statistical Papers, Springer, vol. 54(3), pages 645-683, August.
    23. Fokianos, Konstantinos, 2024. "Multivariate Count Time Series Modelling," Econometrics and Statistics, Elsevier, vol. 31(C), pages 100-116.
    24. Aknouche, Abdelhakim & Scotto, Manuel, 2022. "A multiplicative thinning-based integer-valued GARCH model," MPRA Paper 112475, University Library of Munich, Germany.
    25. Weiß, Christian H., 2010. "INARCH(1) processes: Higher-order moments and jumps," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1771-1780, December.
    26. Abdelhakim Aknouche & Stefanos Dimitrakopoulos, 2023. "Autoregressive conditional proportion: A multiplicative‐error model for (0,1)‐valued time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(4), pages 393-417, July.
    27. Dunsmuir, William T. M. & Scott, David J., 2015. "The glarma Package for Observation-Driven Time Series Regression of Counts," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 67(i07).
    28. Brännäs, Kurt & Quoreshi, Shahiduzzaman, 2004. "Integer-Valued Moving Average Modelling of the Number of Transactions in Stocks," Umeå Economic Studies 637, Umeå University, Department of Economics.
    29. Mawuli Segnon & Manuel Stapper, 2019. "Long Memory Conditional Heteroscedasticity in Count Data," CQE Working Papers 8219, Center for Quantitative Economics (CQE), University of Muenster.
    30. Aknouche, Abdelhakim & Francq, Christian, 2020. "Stationarity and ergodicity of Markov switching positive conditional mean models," MPRA Paper 102503, University Library of Munich, Germany.
    31. Christian H. Weiß & Esmeralda Gonçalves & Nazaré Mendes Lopes, 2017. "Testing the compounding structure of the CP-INARCH model," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 80(5), pages 571-603, July.
    32. Chiranjit Dutta & Kara Karpman & Sumanta Basu & Nalini Ravishanker, 2023. "Review of Statistical Approaches for Modeling High-Frequency Trading Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 1-48, May.
    33. Dag Tjøstheim, 2012. "Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 413-438, September.
    34. Aknouche, Abdelhakim & Gouveia, Sonia & Scotto, Manuel, 2023. "Random multiplication versus random sum: auto-regressive-like models with integer-valued random inputs," MPRA Paper 119518, University Library of Munich, Germany, revised 18 Dec 2023.
    35. Ben Omrane, Walid & Heinen, Andréas, 2010. "Public news announcements and quoting activity in the Euro/Dollar foreign exchange market," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2419-2431, November.
    36. Christian H. Weiß & Sebastian Schweer, 2015. "Detecting overdispersion in INARCH(1) processes," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 69(3), pages 281-297, August.
    37. Jung, Robert & Kukuk, Martin & Liesenfeld, Roman, 2005. "Time Series of Count Data: Modelling and Estimation," Economics Working Papers 2005-08, Christian-Albrechts-University of Kiel, Department of Economics.
    38. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2021. "Autoregressive conditional proportion: A multiplicative-error model for (0,1)-valued time series," MPRA Paper 110954, University Library of Munich, Germany, revised 06 Dec 2021.
    39. Fokianos, Konstantinos & Fried, Roland & Kharin, Yuriy & Voloshko, Valeriy, 2022. "Statistical analysis of multivariate discrete-valued time series," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    40. Jung, Robert C. & Kukuk, Martin & Liesenfeld, Roman, 2006. "Time series of count data: modeling, estimation and diagnostics," Computational Statistics & Data Analysis, Elsevier, vol. 51(4), pages 2350-2364, December.
    41. Youngmi Lee & Sangyeol Lee & Dag Tjøstheim, 2018. "Asymptotic normality and parameter change test for bivariate Poisson INGARCH models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(1), pages 52-69, March.
    42. Feigin, Paul D. & Gould, Phillip & Martin, Gael M. & Snyder, Ralph D., 2008. "Feasible parameter regions for alternative discrete state space models," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2963-2970, December.
    43. J. Keith Ord, 2008. "Monitoring Processes with Changing Variances," Working Papers 2008-004, The George Washington University, Department of Economics, H. O. Stekler Research Program on Forecasting.
    44. A. M. M. Shahiduzzaman Quoreshi & Reaz Uddin & Naushad Mamode Khan, 2019. "Quasi-Maximum Likelihood Estimation for Long Memory Stock Transaction Data—Under Conditional Heteroskedasticity Framework," JRFM, MDPI, vol. 12(2), pages 1-13, April.
    45. Ben Omrane, Walid & Heinen, Andréas, 2009. "Is there any common knowledge news in the Euro/Dollar market?," International Review of Economics & Finance, Elsevier, vol. 18(4), pages 656-670, October.
    46. Weiß, Christian H., 2024. "On higher-order moments of INGARCH processes," Statistics & Probability Letters, Elsevier, vol. 214(C).
    47. Mamode Khan Naushad & Rumjaun Wasseem & Sunecher Yuvraj & Jowaheer Vandna, 2017. "Computing with bivariate COM-Poisson model under different copulas," Monte Carlo Methods and Applications, De Gruyter, vol. 23(2), pages 131-146, June.
    48. GRAMMIG, Joachim & HEINEN, Andréas & RENGIFO, Erick, 2004. "Trading activity and liquidity supply in a pure limit order book market," LIDAM Discussion Papers CORE 2004058, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    49. Ghahramani, M. & Thavaneswaran, A., 2009. "On some properties of Autoregressive Conditional Poisson (ACP) models," Economics Letters, Elsevier, vol. 105(3), pages 273-275, December.
    50. Ali Ahmad & Christian Francq, 2015. "Poisson QMLE of Count Time Series Models," Post-Print hal-01533548, HAL.
    51. Weiß, Christian H. & Schweer, Sebastian, 2016. "Bias corrections for moment estimators in Poisson INAR(1) and INARCH(1) processes," Statistics & Probability Letters, Elsevier, vol. 112(C), pages 124-130.
    52. Lee, Sangyeol & Kim, Dongwon & Kim, Byungsoo, 2023. "Modeling and inference for multivariate time series of counts based on the INGARCH scheme," Computational Statistics & Data Analysis, Elsevier, vol. 177(C).
    53. Ralph D. Snyder & Adrian Beaumont, 2007. "A Comparison of Methods for Forecasting Demand for Slow Moving Car Parts," Monash Econometrics and Business Statistics Working Papers 15/07, Monash University, Department of Econometrics and Business Statistics.
    54. Cattivelli, Luca & Pirino, Davide, 2019. "A SHARP model of bid–ask spread forecasts," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1211-1225.
    55. BEN OMRANE, Walid & HEINEN, Andréas, 2003. "The response of individual FX dealers'quoting activity to macroeconomic news announcements," LIDAM Discussion Papers CORE 2003070, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    56. Konstantinos Fokianos & Roland Fried, 2010. "Interventions in INGARCH processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(3), pages 210-225, May.
    57. Ralph D. Snyder & Gael M. Martin & Phillip Gould & Paul D. Feigin, 2007. "An Assessment of Alternative State Space Models for Count Time Series," Monash Econometrics and Business Statistics Working Papers 4/07, Monash University, Department of Econometrics and Business Statistics.
    58. Pedeli, Xanthi & Karlis, Dimitris, 2013. "Some properties of multivariate INAR(1) processes," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 213-225.
    59. Christian H. Weiß, 2017. "On Eigenvalues of the Transition Matrix of Some Count-Data Markov Chains," Methodology and Computing in Applied Probability, Springer, vol. 19(3), pages 997-1007, September.
    60. Luiza S. C. Piancastelli & Wagner Barreto‐Souza & Hernando Ombao, 2023. "Flexible bivariate INGARCH process with a broad range of contemporaneous correlation," Journal of Time Series Analysis, Wiley Blackwell, vol. 44(2), pages 206-222, March.
    61. Aknouche, Abdelhakim & Dimitrakopoulos, Stefanos, 2024. "Volatility models versus intensity models: analogy and differences," MPRA Paper 122528, University Library of Munich, Germany.
    62. Christian Weiß, 2009. "Modelling time series of counts with overdispersion," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 18(4), pages 507-519, November.
    63. Youngmi Lee & Sangyeol Lee, 2019. "CUSUM test for general nonlinear integer-valued GARCH models: comparison study," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 71(5), pages 1033-1057, October.

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  1. Andréas Heinen & James B. Kau & Donald C. Keenan & Mi Lim Kim, 2021. "Spatial Dependence in Subprime Mortgage Defaults," The Journal of Real Estate Finance and Economics, Springer, vol. 62(1), pages 1-24, January.

    Cited by:

    1. Arunav Das, 2021. "Visual Analytics approach for finding spatiotemporal patterns from COVID19," Papers 2101.06476, arXiv.org.

  2. Heinen, Andréas & Valdesogo, Alfonso, 2020. "Spearman rank correlation of the bivariate Student t and scale mixtures of normal distributions," Journal of Multivariate Analysis, Elsevier, vol. 179(C).

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    1. Saminger-Platz Susanne & Kolesárová Anna & Šeliga Adam & Mesiar Radko & Klement Erich Peter, 2024. "On comprehensive families of copulas involving the three basic copulas and transformations thereof," Dependence Modeling, De Gruyter, vol. 12(1), pages 1-36.
    2. Cameron Francis Assadian & Francis Assadian, 2023. "Data-Driven Modeling of Appliance Energy Usage," Energies, MDPI, vol. 16(22), pages 1-12, November.
    3. Andréas Heinen & Alfonso Valdesogo, 2022. "The Kendall and Spearman rank correlations of the bivariate skew normal distribution," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(4), pages 1669-1698, December.

  3. Andréas Heinen & Jeetendra Khadan & Eric Strobl, 2019. "The Price Impact of Extreme Weather in Developing Countries," The Economic Journal, Royal Economic Society, vol. 129(619), pages 1327-1342.

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    1. Maqsood Aslam & Etienne Farvaque & Franck Malan, 2021. "A disaster always rings twice: Early life experiences and central bankers' reactions to natural disasters," Kyklos, Wiley Blackwell, vol. 74(3), pages 301-320, August.
    2. William Ginn, 2022. "Climate Disasters and the Macroeconomy: Does State-Dependence Matter? Evidence for the US," Economics of Disasters and Climate Change, Springer, vol. 6(1), pages 141-161, March.
    3. Xing-Yun Zou & Xin-Yu Peng & Xin-Xin Zhao & Chun-Ping Chang, 2023. "The impact of extreme weather events on water quality: international evidence," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 115(1), pages 1-21, January.
    4. Bommer, Christian & Dreher, Axel & Perez-Alvarez, Marcello, 2022. "Home bias in humanitarian aid: The role of regional favoritism in the allocation of international disaster relief," Journal of Public Economics, Elsevier, vol. 208(C).
    5. Kanika Mahajan & Shekhar Tomar, 2021. "COVID‐19 and Supply Chain Disruption: Evidence from Food Markets in India†," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(1), pages 35-52, January.
    6. Johar, Meliyanni & Johnston, David W. & Shields, Michael A. & Siminski, Peter & Stavrunova, Olena, 2020. "The Economic Impacts of Direct Natural Disaster Exposure," IZA Discussion Papers 13616, Institute of Labor Economics (IZA).
    7. Faccia, Donata & Parker, Miles & Stracca, Livio, 2021. "Feeling the heat: extreme temperatures and price stability," Working Paper Series 2626, European Central Bank.
    8. Anastasios Evgenidis & Masashige Hamano & Wessel N. Vermeulen, 2021. "Economic consequences of follow-up disasters: lessons from the 2011 Great East Japan Earthquake," Working Papers 2111, Waseda University, Faculty of Political Science and Economics.
    9. Kanika Mahajan & Shekhar Tomar, 2020. "Here Today, Gone Tomorrow: COVID-19 and Supply Chain Disruptions," Working Papers 28, Ashoka University, Department of Economics.
    10. P. Figini & S. Cicognani & L. Zirulia, 2019. "Booking in the Rain: Testing the impact of public information on prices," Working Papers wp1137, Dipartimento Scienze Economiche, Universita' di Bologna.
    11. Alessandro Cantelmo, 2020. "Rare disasters, the natural interest rate and monetary policy," Temi di discussione (Economic working papers) 1309, Bank of Italy, Economic Research and International Relations Area.
    12. Lucidi, Francesco Simone & Pisa, Marta Maria & Tancioni, Massimiliano, 2024. "The effects of temperature shocks on energy prices and inflation in the Euro Area," European Economic Review, Elsevier, vol. 166(C).
    13. Yothin Jinjarak & Ilan Noy & Quy Ta, 2020. "How Shocks Affect International Reserves? A Quasi-Experiment of Earthquakes," CESifo Working Paper Series 8632, CESifo.
    14. Etienne Espagne, 2018. "Money, Finance and Climate: The Elusive Quest for a Truly Integrated Assessment Model," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 60(1), pages 131-143, March.
    15. Fox, Stephen & Griffy-Brown, Charla & Dabic, Marina, 2020. "From socio-technical systems to biosocial technical systems: New themes and new guidance for the field of technology in society," Technology in Society, Elsevier, vol. 62(C).
    16. K. Mukherjee & B. Ouattara, 2021. "Climate and monetary policy: do temperature shocks lead to inflationary pressures?," Climatic Change, Springer, vol. 167(3), pages 1-21, August.
    17. Kunze, Sven, 2020. "Unraveling the effects of tropical cyclones on economic sectors worldwide," Working Papers 0685, University of Heidelberg, Department of Economics.
    18. Ciccarelli, Matteo & Marotta, Fulvia, 2021. "Demand or supply? An empirical exploration of the effects of climate change on the macroeconomy," Working Paper Series 2608, European Central Bank.
    19. Yang, Bixuan & Asche, Frank & Li, Tao, 2021. "Food Price Inflation and Demand Shocks: Evidence from Chinese Cities during the Covid-19 Epidemic," 2021 Annual Meeting, August 1-3, Austin, Texas 314067, Agricultural and Applied Economics Association.
    20. Alessandro Cantelmo & Nikos Fatouros & Giovanni Melina & Chris Papageorgiou, 2024. "Monetary Policy Under Natural Disaster Shocks," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 65(3), pages 1441-1497, August.
    21. John Beirne & Yannis Dafermos & Alexander Kriwoluzky & Nuobu Renzhi & Ulrich Volz & Jana Wittich, 2021. "The Effects of Natural Disasters on Price Stability in the Euro Area," Discussion Papers of DIW Berlin 1981, DIW Berlin, German Institute for Economic Research.
    22. Beuermann, Diether W. & Pecha, Camilo J., 2020. "The effects of weather shocks on early childhood development: Evidence from 25 years of tropical storms in Jamaica," Economics & Human Biology, Elsevier, vol. 37(C).
    23. Cunpu Li & Xuetong Zhang & Jing He, 2023. "Impact of Climate Change on Inflation in 26 Selected Countries," Sustainability, MDPI, vol. 15(17), pages 1-22, August.
    24. Cevik Serhan & Jalles Joao, 2024. "Eye of the Storm: The Impact of Climate Shocks on Inflation and Growth," Review of Economics, De Gruyter, vol. 75(2), pages 109-138.
    25. Jeroen Klomp & John Sseruyange, 2021. "Earthquakes and Economic Outcomes: Does Central Bank Independence Matter?," Open Economies Review, Springer, vol. 32(2), pages 335-359, April.
    26. Thibault Lemaire & Paul Vertier, 2023. "International Commodity Prices Transmission to Consumer Prices in Africa," Working Papers hal-03944888, HAL.
    27. Serhan Cevik, João Tovar Jalles, 2023. "Eye of the Storm: The Impact of Climate Shocks on Inflation and Growth," Working Papers REM 2023/0276, ISEG - Lisbon School of Economics and Management, REM, Universidade de Lisboa.
    28. Alain N. Kabundi & Mr. Montfort Mlachila & Jiaxiong Yao, 2022. "How Persistent are Climate-Related Price Shocks? Implications for Monetary Policy," IMF Working Papers 2022/207, International Monetary Fund.
    29. Chaitat Jirophat & Pym Manopimoke & Suparit Suwanik, 2022. "The Macroeconomic Effects of Climate Shocks in Thailand," PIER Discussion Papers 188, Puey Ungphakorn Institute for Economic Research.
    30. Utkur Djanibekov & Maksym Polyakov & Heather Craig & Ryan Paulik, 2024. "Flood Impacts on Agriculture under Climate Change: The case of the Awanui Catchment, New Zealand," Economics of Disasters and Climate Change, Springer, vol. 8(2), pages 283-316, July.
    31. Pablo Garcia Sanchez, 2022. "Introduction to weather extremes and monetary policy," BCL working papers 163, Central Bank of Luxembourg.
    32. Sven Kunze, 2021. "Unraveling the Effects of Tropical Cyclones on Economic Sectors Worldwide: Direct and Indirect Impacts," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 78(4), pages 545-569, April.
    33. Meltem Chadwick & Hulya Saygili, 2024. "Temperature, precipitation and food price inflation: Evidence from a panel of countries," Working Papers wp55, South East Asian Central Banks (SEACEN) Research and Training Centre.
    34. Li, Xing & Zhou, Yanli & Zhu, Dixing & Ge, Xiangyu, 2024. "Research on effect of extreme climates penalties local government debt pricing: Evidence from urban investment bonds in China," The North American Journal of Economics and Finance, Elsevier, vol. 73(C).

  4. Guillermo Baquero & Malika Hamadi & Andréas Heinen, 2018. "Competition, Loan Rates, and Information Dispersion in Nonprofit and For‐Profit Microcredit Markets," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(5), pages 893-937, August.

    Cited by:

    1. Wang, Bo & Yu, Yunjun & Yang, Ziying & Zhang, Xiaomei, 2021. "Microfinance institutions and Peer-to-Peer lending: What does microfinance competition bring?," Pacific-Basin Finance Journal, Elsevier, vol. 67(C).
    2. Quidt, Jonathan de & Fetzer, Thiemo & Ghatak, Maitreesh, 2016. "Commercialization and the Decline of Joint Liability Microcredit," CAGE Online Working Paper Series 272, Competitive Advantage in the Global Economy (CAGE).
    3. Giovanna Aguilar Andía & Jhonatan Portilla Goicochea, 2020. "Competencia, alcance social y sostenibilidad financiera en las microfinanzas reguladas peruanas," Documentos de Trabajo / Working Papers 2020-493, Departamento de Economía - Pontificia Universidad Católica del Perú.
    4. Ahmad, Syedah & Lensink, Robert & Mueller, Annika, 2020. "The double bottom line of microfinance: A global comparison between conventional and Islamic microfinance," World Development, Elsevier, vol. 136(C).
    5. Djibril Faye & Zaka Ratsimalahelo, 2022. "Dynamic analysis of the interest rate determinant in microfinance institutions," Working Papers 2022-09, CRESE.
    6. Magloire Nya Tchatchoua & Isabelle Pignatel & Hubert Tchakoute Tchuigoua, 2019. "What type of microfinance institutions comply with International Financial Reporting Standards?," Working Papers CEB 19-012, ULB -- Universite Libre de Bruxelles.
    7. Fall, François Seck & Tchuigoua, Hubert Tchakoute & Vanhems, Anne & Simar, Léopold, 2020. "Gender effect on microfinance social efficiency: A robust nonparametric approach," LIDAM Discussion Papers ISBA 2020033, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    8. Pignatel, Isabelle & Tchakoute Tchuigoua, Hubert, 2020. "Microfinance institutions and International Financial Reporting Standards: An exploratory analysis," Research in International Business and Finance, Elsevier, vol. 54(C).
    9. Tchakoute-Tchuigoua, Hubert & Soumaré, Issouf, 2019. "The effect of loan approval decentralization on microfinance institutions' outreach and loan portfolio quality," Journal of Business Research, Elsevier, vol. 94(C), pages 1-17.
    10. Christoph Sommer, 2022. "Unintended consequences of microfinance: Effects on credit access for small‐ and medium‐sized enterprises," Journal of International Development, John Wiley & Sons, Ltd., vol. 34(3), pages 564-586, April.

  5. Hamadi, Malika & Heinen, Andréas & Linder, Stefan & Porumb, Vlad-Andrei, 2016. "Does Basel II affect the market valuation of discretionary loan loss provisions?," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 177-192.

    Cited by:

    1. Hamdi Ben-Nasr & Sabri Boubaker & Syrine Sassi, 2021. "Board reforms and debt choice," Post-Print hal-04455596, HAL.
    2. Hou, Xiaohui & Wang, Bo & Lian, Jiale & Li, Wanli, 2021. "Bank executive pay limits and discretionary loan loss provisions: Evidence from China," Research in International Business and Finance, Elsevier, vol. 58(C).
    3. Walter Amedzro St-Hilaire & Patrick Boisselier, 2018. "Evaluating profitability strategies and the determinants of the risk performance of sectoral and banking institutions," Post-Print hal-03220229, HAL.
    4. Mohamed A. Elbannan, 2016. "Accounting Discretion and the Market Disciplining of Bank Risk-taking Behavior: An Assessment of the Effectiveness of Egyptian Banking Reforms from an Accounting Perspective," Accounting and Finance Research, Sciedu Press, vol. 5(4), pages 1-1, November.
    5. Bakkar, Yassine & De Jonghe, Olivier & Tarazi, Amine, 2023. "Does banks’ systemic importance affect their capital structure and balance sheet adjustment processes?," Journal of Banking & Finance, Elsevier, vol. 151(C).
    6. Jutasompakorn, Pearpilai & Lim, Chu Yeong & Ranasinghe, Tharindra & Ow Yong, Kevin, 2021. "Impact of Basel III on the discretion and timeliness of Banks’ loan loss provisions," Journal of Contemporary Accounting and Economics, Elsevier, vol. 17(2).
    7. Lartey, Theophilus & James, Gregory A. & Danso, Albert & Boateng, Agyenim, 2022. "Bank business models, failure risk and earnings opacity: A short- versus long-term perspective," International Review of Financial Analysis, Elsevier, vol. 80(C).
    8. Raffaela Casciello & Marco Maffei & David A. Ziebart, 2024. "Regulatory and contextual factors influencing earnings and capital management decisions: evidence from the European banking sector," Review of Quantitative Finance and Accounting, Springer, vol. 63(1), pages 87-146, July.
    9. Sanzid A. Haq & Dung Viet Tran & M. Kabir Hassan, 2019. "Discretionary Loan Loss Provision Behaviour and Banks' Liquidity Creation," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 15(2), pages 119-154.
    10. Pandey, Ashish & Guhathakurta, Kousik, 2022. "Value relevance of loan loss provision components and the choice of model specification," Advances in accounting, Elsevier, vol. 58(C).
    11. Degryse, Hans & Huylebroek, Cédric, 2023. "Fiscal support and banks’ loan loss provisions during the COVID-19 crisis," Journal of Financial Stability, Elsevier, vol. 67(C).
    12. Yassine Bakkar & Olivier De Jonghe & Amine Tarazi, 2017. "Does banks' systemic importance affect their capital structure adjustment process?," Working Papers hal-01546995, HAL.
    13. Konstantinos Vasilakopoulos & Christos Tzovas & Apostolos Ballas, 2021. "Banks’ Risk and The Impact of Audit Quality on Income Smoothing," Journal of Accounting and Management Information Systems, Faculty of Accounting and Management Information Systems, The Bucharest University of Economic Studies, vol. 20(3), pages 425-453, September.
    14. Hegde, Shantaram P. & Kozlowski, Steven E., 2021. "Discretionary loan loss provisioning and bank stock returns: The Role of economic booms and busts," Journal of Banking & Finance, Elsevier, vol. 130(C).

  6. Hamadi, Malika & Heinen, Andréas, 2015. "Firm performance when ownership is very concentrated: Evidence from a semiparametric panel," Journal of Empirical Finance, Elsevier, vol. 34(C), pages 172-194.
    See citations under working paper version above.
  7. Salvador Barrios & Luisito Bertinelli & Andreas Heinen & Eric Strobl, 2012. "Exploring the Existence of Local and Global Knowledge Spillovers: Evidence from Plant-Level Data," Scandinavian Journal of Economics, Wiley Blackwell, vol. 114(3), pages 856-880, September.

    Cited by:

    1. Görg, Holger & Mulyukova, Alina, 2022. "Place-Based Policies and Agglomeration Economies: Firm-Level Evidence from Special Economic Zones in India," IZA Discussion Papers 15123, Institute of Labor Economics (IZA).
    2. Stephan Kyburz, Huong Quynh Nguyen, 2017. "Does Proximity to Foreign Invested Firms Stimulate Productivity Growth of Domestic Firms? Firmlevel Evidence from Vietnam," Diskussionsschriften credresearchpaper16, Universitaet Bern, Departement Volkswirtschaft - CRED.
    3. Nguyen, Huong, 2016. "Does Proximity to Foreign Invested Firms Stimulate Productivity Growth of Domestic Firms? Firm-level Evidence from Vietnam," Papers 1001, World Trade Institute.

  8. Ben Omrane, Walid & Heinen, Andréas, 2010. "Public news announcements and quoting activity in the Euro/Dollar foreign exchange market," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2419-2431, November.

    Cited by:

    1. Dimitrios I. Vortelinos, 2015. "Out‐of‐sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini‐futures markets," Review of Financial Economics, John Wiley & Sons, vol. 27(1), pages 58-67, November.
    2. Aymen Belgacem & Anna Creti & Khaled Guesmi & Amine Lahiani, 2015. "Volatility spillovers and macroeconomic announcements: evidence from crude oil markets," Applied Economics, Taylor & Francis Journals, vol. 47(28), pages 2974-2984, June.
    3. Walid Ben Omrane & Christian Hafner, 2015. "Macroeconomic news surprises and volatility spillover in foreign exchange markets," Empirical Economics, Springer, vol. 48(2), pages 577-607, March.
    4. Walid Ben Omrane & Robert Welch & Xinyao Zhou, 2020. "The dynamic effect of macroeconomic news on the euro/US dollar exchange rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 84-103, January.
    5. Aymen Belgacem & Amine Lahiani, 2012. "More on the impact of US macroeconomic announcements: Evidence from French and German stock markets' volatility," Economics Bulletin, AccessEcon, vol. 32(2), pages 1509-1526.
    6. Vortelinos, Dimitrios I., 2015. "Out-of-sample evaluation of macro announcements, linearity, long memory, heterogeneity and jumps in mini-futures markets," Review of Financial Economics, Elsevier, vol. 27(C), pages 58-67.

  9. Ben Omrane, Walid & Heinen, Andréas, 2009. "Is there any common knowledge news in the Euro/Dollar market?," International Review of Economics & Finance, Elsevier, vol. 18(4), pages 656-670, October.

    Cited by:

    1. Müller, Christian, 2015. "Radical uncertainty: Sources, manifestations and implications," Economics Discussion Papers 2015-41, Kiel Institute for the World Economy (IfW Kiel).
    2. Mensi, Walid & Hammoudeh, Shawkat & Yoon, Seong-Min, 2014. "Structural breaks and long memory in modeling and forecasting volatility of foreign exchange markets of oil exporters: The importance of scheduled and unscheduled news announcements," International Review of Economics & Finance, Elsevier, vol. 30(C), pages 101-119.

  10. Lorán Chollete & Andréas Heinen & Alfonso Valdesogo, 2009. "Modeling International Financial Returns with a Multivariate Regime-switching Copula," Journal of Financial Econometrics, Oxford University Press, vol. 7(4), pages 437-480, Fall.
    See citations under working paper version above.
  11. Heinen, Andréas & Rengifo, Erick, 2008. "Multivariate reduced rank regression in non-Gaussian contexts, using copulas," Computational Statistics & Data Analysis, Elsevier, vol. 52(6), pages 2931-2944, February.
    See citations under working paper version above.
  12. Heinen, Andreas & Rengifo, Erick, 2007. "Multivariate autoregressive modeling of time series count data using copulas," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 564-583, September.

    Cited by:

    1. Jung, Robert & Liesenfeld, Roman & Richard, Jean-François, 2008. "Dynamic Factor Models for Multivariate Count Data: An Application to Stock-Market Trading Activity," Economics Working Papers 2008-12, Christian-Albrechts-University of Kiel, Department of Economics.
    2. Groß-Klußmann, Axel & Hautsch, Nikolaus, 2011. "Predicting bid-ask spreads using long memory autoregressive conditional poisson models," SFB 649 Discussion Papers 2011-044, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    3. Mike Vuolo, 2017. "Copula Models for Sociology: Measures of Dependence and Probabilities for Joint Distributions," Sociological Methods & Research, , vol. 46(3), pages 604-648, August.
    4. HEINEN, Andréas & RENGIFO, Erick, 2004. "Multivariate reduced rank regression in non-Gaussian contexts, using copulas," LIDAM Discussion Papers CORE 2004032, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    5. Eugenio Miravete, 2014. "Testing for complementarities among countable strategies," Empirical Economics, Springer, vol. 46(4), pages 1521-1544, June.
    6. Matteo Iacopini & Carlo Romano Marcello Alessandro Santagiustina, 2021. "Filtering the Intensity of Public Concern from Social Media Count Data with Jumps," SciencePo Working papers Main hal-04494229, HAL.
    7. Yang Lu, 2021. "The predictive distributions of thinning‐based count processes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 48(1), pages 42-67, March.
    8. BAUWENS, Luc & HAUTSCH, Nikolaus, 2009. "Modelling financial high frequency data using point processes," LIDAM Reprints CORE 2123, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    9. Escribano, Ana & Maggi, Mario, 2019. "Intersectoral default contagion: A multivariate Poisson autoregression analysis," Economic Modelling, Elsevier, vol. 82(C), pages 376-400.
    10. Weiß, Gregor N.F. & Supper, Hendrik, 2013. "Forecasting liquidity-adjusted intraday Value-at-Risk with vine copulas," Journal of Banking & Finance, Elsevier, vol. 37(9), pages 3334-3350.
    11. Ruben Loaiza-Maya & Michael Stanley Smith, 2017. "Variational Bayes Estimation of Discrete-Margined Copula Models with Application to Time Series," Papers 1712.09150, arXiv.org, revised Jul 2018.
    12. Šárka Hudecová & Marie Hušková & Simos G. Meintanis, 2021. "Goodness–of–Fit Tests for Bivariate Time Series of Counts," Econometrics, MDPI, vol. 9(1), pages 1-20, March.
    13. Christian Gouriéroux & Yang Lu, 2018. "Negative Binomial Autoregressive Process," Working Papers 2018-03, Center for Research in Economics and Statistics.
    14. BAUWENS, Luc & HAUTSCH, Nikolaus, 2003. "Dynamic latent factor models for intensity processes," LIDAM Discussion Papers CORE 2003103, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Fokianos, Konstantinos, 2024. "Multivariate Count Time Series Modelling," Econometrics and Statistics, Elsevier, vol. 31(C), pages 100-116.
    16. Rainer Baule & Bart Frijns & Sebastian Schlie, 2024. "Feedback Trading: The Intraday Case of Retail Derivatives," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(9), pages 1487-1507, September.
    17. BAUWENS, Luc & HAUTSCH, Nikolaus, 2006. "Stochastic conditional intensity processes," LIDAM Reprints CORE 1937, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    18. Serge Darolles & Gaëlle Le Fol & Yang Lu & Ran Sun, 2018. "Bivariate integer-autoregressive process with an application to mutual fund flows," Post-Print hal-04590149, HAL.
    19. Dag Tjøstheim, 2012. "Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 413-438, September.
    20. Yan Cui & Qi Li & Fukang Zhu, 2020. "Flexible bivariate Poisson integer-valued GARCH model," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 72(6), pages 1449-1477, December.
    21. Ben Omrane, Walid & Heinen, Andréas, 2010. "Public news announcements and quoting activity in the Euro/Dollar foreign exchange market," Computational Statistics & Data Analysis, Elsevier, vol. 54(11), pages 2419-2431, November.
    22. Fokianos, Konstantinos & Fried, Roland & Kharin, Yuriy & Voloshko, Valeriy, 2022. "Statistical analysis of multivariate discrete-valued time series," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    23. Eugenio J. Miravete, 2009. "Competing with Menus of Tariff Options," Journal of the European Economic Association, MIT Press, vol. 7(1), pages 188-205, March.
    24. Arianna Agosto & Paolo Giudici, 2023. "Cyber Risk Contagion," Risks, MDPI, vol. 11(9), pages 1-10, September.
    25. Youngmi Lee & Sangyeol Lee & Dag Tjøstheim, 2018. "Asymptotic normality and parameter change test for bivariate Poisson INGARCH models," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(1), pages 52-69, March.
    26. Paul Doukhan, 2012. "Comments on: Some recent theory for autoregressive count time series," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(3), pages 447-450, September.
    27. Siem Jan Koopman & Rutger Lit & André Lucas & Anne Opschoor, 2018. "Dynamic discrete copula models for high‐frequency stock price changes," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(7), pages 966-985, November.
    28. Yang Lu & Christian Gourieroux, 2018. "Negative Binomial Autoregressive Process," Working Papers hal-01730050, HAL.
    29. Fantazzini, Dean, 2020. "Discussing copulas with Sergey Aivazian: a memoir," MPRA Paper 102317, University Library of Munich, Germany.
    30. González-Rivera, Gloria & Sun, Yingying, 2015. "Generalized autocontours: Evaluation of multivariate density models," International Journal of Forecasting, Elsevier, vol. 31(3), pages 799-814.
    31. Cattivelli, Luca & Pirino, Davide, 2019. "A SHARP model of bid–ask spread forecasts," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1211-1225.
    32. Hautsch, Nikolaus & Jeleskovic, Vahidin, 2008. "Modelling high-frequency volatility and liquidity using multiplicative error models," SFB 649 Discussion Papers 2008-047, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    33. Popovic, Gordana C. & Hui, Francis K.C. & Warton, David I., 2018. "A general algorithm for covariance modeling of discrete data," Journal of Multivariate Analysis, Elsevier, vol. 165(C), pages 86-100.
    34. Pedeli, Xanthi & Karlis, Dimitris, 2013. "Some properties of multivariate INAR(1) processes," Computational Statistics & Data Analysis, Elsevier, vol. 67(C), pages 213-225.
    35. Darolles, Serge & Fol, Gaëlle Le & Lu, Yang & Sun, Ran, 2019. "Bivariate integer-autoregressive process with an application to mutual fund flows," Journal of Multivariate Analysis, Elsevier, vol. 173(C), pages 181-203.
    36. Scotto, Manuel G. & Weiß, Christian H. & Silva, Maria Eduarda & Pereira, Isabel, 2014. "Bivariate binomial autoregressive models," Journal of Multivariate Analysis, Elsevier, vol. 125(C), pages 233-251.
    37. Yicheng Song & Nachiketa Sahoo & Shuba Srinivasan & Chrysanthos Dellarocas, 2022. "Uncovering Characteristic Response Paths of a Population," INFORMS Journal on Computing, INFORMS, vol. 34(3), pages 1661-1680, May.
    38. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
    39. Yan Cui & Fukang Zhu, 2018. "A new bivariate integer-valued GARCH model allowing for negative cross-correlation," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(2), pages 428-452, June.
    40. Patton, Andrew, 2013. "Copula Methods for Forecasting Multivariate Time Series," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 899-960, Elsevier.
    41. Bracher, Johannes & Held, Leonhard, 2022. "Endemic-epidemic models with discrete-time serial interval distributions for infectious disease prediction," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1221-1233.

Chapters

  1. Andréas Heinen & Alfonso Valdesogo, 2010. "Dynamic D-Vine Model," World Scientific Book Chapters, in: Dorota Kurowicka & Harry Joe (ed.), Dependence Modeling Vine Copula Handbook, chapter 16, pages 329-353, World Scientific Publishing Co. Pte. Ltd..

    Cited by:

    1. GRIGORIADIS, Vasilis & EMMANOUILIDES, Christos & FOUSEKIS, Panos, 2016. "The Integration Of Pigmeat Markets In The Eu. Evidence From A Regular Mixed Vine Copula," Review of Agricultural and Applied Economics (RAAE), Faculty of Economics and Management, Slovak Agricultural University in Nitra, vol. 19(1), pages 1-10, March.

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