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The European Journal of Finance Volume 15, 2009 - Issue 7-8: COPULAE AND MULTIVARIATE PROBABILITY DISTRIBUTIONS IN FINANCE
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Original Articles

Dynamic copula quantile regressions and tail area dynamic dependence in Forex markets

Eric Bouyé Financial Econometrics Research Centre, Warwick Business School, UK
&
Mark Salmon Financial Econometrics Research Centre, Warwick Business School, UKCorrespondence[email protected]
Pages 721-750 | Published online: 09 Jun 2009

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Ozan Evkaya, Bilgi Yilmaz & Ebru Yüksel Haliloğlu. (2023) Sectoral electricity consumption modeling with D-vine quantile regression: The US electricity market case. Energy Sources, Part B: Economics, Planning, and Policy 18:1.
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Maoxi Tian, Rim El Khoury, Nohade Nasrallah & Muneer M. Alshater. (2023) Assessing systemic risk spillovers from FinTech to China’s financial system. The European Journal of Finance 0:0, pages 1-24.
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Noureddine Benlagha & Wael Hemrit. (2023) Does investment in insurance stocks reap diversification benefits? Static and time varying copula modeling. Communications in Statistics - Simulation and Computation 52:4, pages 1384-1402.
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Maoxi Tian, Yong Jiang, Binyao Wang, Yizhe Dong, Yingying Chen & Baofeng Shi. (2023) Downside and upside risk spillovers from commercial banks into China’s financial system: a new copula quantile regression-based CoVaR model. Economic Research-Ekonomska Istraživanja 36:1.
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Thomas Nagler & Thibault Vatter. (2023) Solving Estimating Equations With Copulas. Journal of the American Statistical Association 0:0, pages 1-13.
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Shuo Li, Liuhua Peng & Yundong Tu. (2022) Testing independence between exogenous variables and unobserved errors. Econometric Reviews 41:7, pages 697-728.
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Emmanouil N. Karimalis & Nikos K. Nomikos. (2018) Measuring systemic risk in the European banking sector: a copula CoVaR approach. The European Journal of Finance 24:11, pages 944-975.
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Amir T. Payandeh Najafabadi & Marjan Qazvini. (2015) A GLM Approach to Estimating Copula Models. Communications in Statistics - Simulation and Computation 44:6, pages 1641-1656.
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Hohsuk Noh, Anouar El Ghouch & Ingrid Van Keilegom. (2015) Semiparametric Conditional Quantile Estimation Through Copula-Based Multivariate Models. Journal of Business & Economic Statistics 33:2, pages 167-178.
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Qing Xu & Terry Childs. (2013) Evaluating forecast performances of the quantile autoregression models in the present global crisis in international equity markets. Applied Financial Economics 23:2, pages 105-117.
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Laura Coroneo & David Veredas. (2012) A simple two-component model for the distribution of intraday returns. The European Journal of Finance 18:9, pages 775-797.
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Suttisak Wattanawongwan, Christophe Mues, Ramin Okhrati, Taufiq Choudhry & Mee Chi So. (2023) Modelling credit card exposure at default using vine copula quantile regression. European Journal of Operational Research 311:1, pages 387-399.
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Danyang Li, Zhekai Zhang & Mario Cerrato. (2023) Factor investing and currency portfolio management. International Review of Financial Analysis 87, pages 102626.
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M. Mesfioui, T. Bouezmarni & M. Belalia. (2022) Copula-based link functions in binary regression models. Statistical Papers 64:2, pages 557-585.
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Bo Wang & Yang Xiao. (2023) Risk spillovers from China's and the US stock markets during high-volatility periods: Evidence from East Asianstock markets. International Review of Financial Analysis 86, pages 102538.
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Walid Mensi, Debasish Maitra, Refk Selmi & Xuan Vinh Vo. (2023) Extreme dependencies and spillovers between gold and stock markets: evidence from MENA countries. Financial Innovation 9:1.
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Maoxi Tian, Muneer M. Alshater & Seong-Min Yoon. (2022) Dynamic risk spillovers from oil to stock markets: Fresh evidence from GARCH copula quantile regression-based CoVaR model. Energy Economics 115, pages 106341.
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Maoxi Tian, Fei Guo & Rong Niu. (2022) Risk spillover analysis of China’s financial sectors based on a new GARCH copula quantile regression model. The North American Journal of Economics and Finance, pages 101817.
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Eric-Pascal Zahiri, Modeste Kacou, Marielle Gosset & Sahouarizié Adama Ouattara. (2022) Modeling the Interdependence Structure between Rain and Radar Variables Using Copulas: Applications to Heavy Rainfall Estimation by Weather Radar. Atmosphere 13:8, pages 1298.
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Alecos Papadopoulos. (2022) Accounting for Endogeneity in Regression Models Using Copulas: A Step-by-Step Guide for Empirical Studies. Journal of Econometric Methods 11:1, pages 127-154.
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Maoxi Tian & Hao Ji. (2022) GARCH copula quantile regression model for risk spillover analysis. Finance Research Letters 44, pages 102104.
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Ángel León & Trino-Manuel Ñíguez. (2021) Copula methods for evaluating relative tail forecasting performance. The Journal of Risk Finance 22:5, pages 332-344.
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Annalisa Di Clemente & Claudio Romano. (2021) Calibrating and Simulating Copula Functions in Financial Applications. Frontiers in Applied Mathematics and Statistics 7.
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Jianeng Ni & Shaojun Li. (2021) An adaptive soft sensor method of D-vine copula quantile regression for complex chemical processes. Chemical Engineering Science 230, pages 116210.
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Noureddine Benlagha. (2020) Stock market dependence in crisis periods: Evidence from oil price shocks and the Qatar blockade. Research in International Business and Finance 54, pages 101285.
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Jorge V. Pérez-Rodríguez. (2019) Another look at the implied and realised volatility relation: a copula-based approach. Risk Management 22:1, pages 38-64.
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Xiaolei Sun, Chang Liu, Jun Wang & Jianping Li. (2020) Assessing the extreme risk spillovers of international commodities on maritime markets: A GARCH-Copula-CoVaR approach. International Review of Financial Analysis 68, pages 101453.
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Limin Wu. (2020) Tuning the Bivariate Meta-Gaussian Distribution Conditionally in Quantifying Precipitation Prediction Uncertainty. Forecasting 2:1, pages 1-19.
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Khamis Hamed Al-Yahyaee, Walid Mensi, Debasish Maitra & Idries Mohammad Wanas Al-Jarrah. (2019) Portfolio management and dependencies among precious metal markets: Evidence from a Copula quantile-on-quantile approach. Resources Policy 64, pages 101529.
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Bo Chang & Harry Joe. (2019) Prediction based on conditional distributions of vine copulas. Computational Statistics & Data Analysis 139, pages 45-63.
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Elif F. Acar, Parisa Azimaee & Md. Erfanul Hoque. (2018) Predictive assessment of copula models. Canadian Journal of Statistics 47:1, pages 8-26.
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Harry Joe. (2017) Dependence Properties of Conditional Distributions of some Copula Models. Methodology and Computing in Applied Probability 20:3, pages 975-1001.
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Annalisa Di Clemente. (2018) Estimating the Marginal Contribution to Systemic Risk by A CoVaR-model Based on Copula Functions and Extreme Value Theory. Economic Notes 47:1, pages 69-112.
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Bruno Rémillard, Bouchra Nasri & Taoufik Bouezmarni. (2017) On copula-based conditional quantile estimators. Statistics & Probability Letters 128, pages 14-20.
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Kunlapath Sukcharoen & David J. Leatham. (2017) Hedging downside risk of oil refineries: A vine copula approach. Energy Economics 66, pages 493-507.
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Daniel Kraus & Claudia Czado. (2017) D-vine copula based quantile regression. Computational Statistics & Data Analysis 110, pages 1-18.
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Krenar Avdulaj & Jozef Barunik. (2017) A semiparametric nonlinear quantile regression model for financial returns. Studies in Nonlinear Dynamics & Econometrics 21:1.
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Nicholas Sim. (2016) Modeling the dependence structures of financial assets through the Copula Quantile-on-Quantile approach. International Review of Financial Analysis 48, pages 31-45.
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Juan C. Reboredo & Andrea Ugolini. (2016) Quantile dependence of oil price movements and stock returns. Energy Economics 54, pages 33-49.
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Terence D. Agbeyegbe. 2016. The Economics of the Global Environment. The Economics of the Global Environment 597 621 .
Fernando F. Moreira. (2015) Estimating Portfolio Credit Losses in Downturns. Financial Markets, Institutions & Instruments 24:5, pages 391-414.
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Terence D. Agbeyegbe. (2015) An inverted U‐shaped crude oil price return‐implied volatility relationship. Review of Financial Economics 27:1, pages 28-45.
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Oscar M. Camacho, Alison Eldridge, Christopher J. Proctor & Kevin McAdam. (2015) Empirical characterisation of ranges of mainstream smoke toxicant yields from contemporary cigarette products using quantile regression methodology. Regulatory Toxicology and Pharmacology 72:3, pages 458-472.
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Seong-Yoon Kim, Yong-Tae Kim & Sang-Jun Lee. (2015) Influence Comparison of Customer Satisfaction Factor using Quantile Regression Model. Journal of Digital Convergence 13:6, pages 125-132.
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Carole Bernard & Claudia Czado. (2015) Conditional quantiles and tail dependence. Journal of Multivariate Analysis 138, pages 104-126.
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Brendan K. Beare. (2012) ARCHIMEDEAN COPULAS AND TEMPORAL DEPENDENCE. Econometric Theory 28:6, pages 1165-1185.
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Biljana Mileva-Boshkoska & Marko Bohanec. 2012. Operations Research Proceedings 2011. Operations Research Proceedings 2011 103 108 .
Umberto Cherubini, Fabio Gobbi, Sabrina Mulinacci & Silvia Romagnoli. 2011. Dynamic Copula Methods in Finance. Dynamic Copula Methods in Finance 245 249 .
Francesco Serinaldi & Giovanni Cuomo. (2011) Characterizing impulsive wave-in-deck loads on coastal bridges by probabilistic models of impact maxima and rise times. Coastal Engineering 58:9, pages 908-926.
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D. E. ALLEN, R. J. POWELL & A. K. SINGH. (2014) QUANTILE REGRESSION AS A TOOL FOR PORTFOLIO INVESTMENT DECISIONS DURING TIMES OF FINANCIAL DISTRESS. Annals of Financial Economics 06:01, pages 1150003.
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Giovanni De Luca, Giorgia Rivieccio & Paola Zuccolotto. (2010) Combining random forest and copula functions: A heuristic approach for selecting assets from a financial crisis perspective. Intelligent Systems in Accounting, Finance and Management 17:2, pages 91-109.
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Laura Coroneo & David Veredas. (2011) A Simple Two-Component Model for the Distribution of Intra-Day Returns. SSRN Electronic Journal.
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David E. Allen, Abhay Kumar Singh, Robert J. Powell, Michael McAleer, James W. Taylor & Lyn C. Thomas. (2013) Return-Volatility Relationship: Insights from Linear and Non-Linear Quantile Regression. SSRN Electronic Journal.
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