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

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  1. Lee, Tae-Hwy & Yang, Weiping, 2014. "Granger-causality in quantiles between financial markets: Using copula approach," International Review of Financial Analysis, Elsevier, vol. 33(C), pages 70-78.
  2. Wang, Bo & Xiao, Yang, 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, Elsevier, vol. 86(C).
  3. Beare, Brendan K., 2012. "Archimedean Copulas And Temporal Dependence," Econometric Theory, Cambridge University Press, vol. 28(6), pages 1165-1185, December.
  4. Okhrin, Ostap & Ristig, Alexander & Sheen, Jeffrey R. & Trück, Stefan, 2015. "Conditional systemic risk with penalized copula," SFB 649 Discussion Papers 2015-038, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
  5. Sun, Xiaolei & Liu, Chang & Wang, Jun & Li, Jianping, 2020. "Assessing the extreme risk spillovers of international commodities on maritime markets: A GARCH-Copula-CoVaR approach," International Review of Financial Analysis, Elsevier, vol. 68(C).
  6. CORONEO, Laura & VEREDAS, David, 2006. "Intradaily seasonality of returns distribution. A quantile regression approach and intradaily VaR estimation," LIDAM Discussion Papers CORE 2006077, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  7. Khalid Almeshal & Nader Naifar, 2016. "A quantile regression approach and nonlinear analysis with Archimedean copulas to explain the movements of residential real estate prices," Afro-Asian Journal of Finance and Accounting, Inderscience Enterprises Ltd, vol. 6(4), pages 374-395.
  8. Xiaohong Chen & Wei Biao Wu Wu & Yanping Yi, 2009. "Efficient estimation of copula-based semiparametric Markov models," CeMMAP working papers CWP06/09, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
  9. Harvey,Andrew C., 2013. "Dynamic Models for Volatility and Heavy Tails," Cambridge Books, Cambridge University Press, number 9781107034723, November.
  10. Kraus, Daniel & Czado, Claudia, 2017. "D-vine copula based quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 110(C), pages 1-18.
  11. Chen, Xiaohong & Fan, Yanqin, 2006. "Estimation of copula-based semiparametric time series models," Journal of Econometrics, Elsevier, vol. 130(2), pages 307-335, February.
  12. Beare, Brendan K. & Seo, Juwon, 2014. "Time Irreversible Copula-Based Markov Models," Econometric Theory, Cambridge University Press, vol. 30(5), pages 923-960, October.
  13. Sim, Nicholas, 2016. "Modeling the dependence structures of financial assets through the Copula Quantile-on-Quantile approach," International Review of Financial Analysis, Elsevier, vol. 48(C), pages 31-45.
  14. Refk Selmi & Christos Kollias & Stephanos Papadamou & Rangan Gupta, 2017. "A Copula-Based Quantile-on-Quantile Regression Approach to Modeling Dependence Structure between Stock and Bond Returns: Evidence from Historical Data of India, South Africa, UK and US," Working Papers 201747, University of Pretoria, Department of Economics.
  15. Tian, Maoxi & Ji, Hao, 2022. "GARCH copula quantile regression model for risk spillover analysis," Finance Research Letters, Elsevier, vol. 44(C).
  16. Chang, Bo & Joe, Harry, 2019. "Prediction based on conditional distributions of vine copulas," Computational Statistics & Data Analysis, Elsevier, vol. 139(C), pages 45-63.
  17. Xianling Ren & Xinping Yu, 2024. "Hedging performance analysis of energy markets: Evidence from copula quantile regression," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 44(3), pages 432-450, March.
  18. Huo, Lijuan & Kim, Tae-Hwan & Kim, Yunmi, 2012. "Robust estimation of covariance and its application to portfolio optimization," Finance Research Letters, Elsevier, vol. 9(3), pages 121-134.
  19. M. Mesfioui & T. Bouezmarni & M. Belalia, 2023. "Copula-based link functions in binary regression models," Statistical Papers, Springer, vol. 64(2), pages 557-585, April.
  20. Jorge V. Pérez-Rodríguez, 2020. "Another look at the implied and realised volatility relation: a copula-based approach," Risk Management, Palgrave Macmillan, vol. 22(1), pages 38-64, March.
  21. David E. Allen & Abhay K. Singh & Robert J. Powell & Michael McAleer & James Taylor & Lyn Thomas, 2013. "Return-Volatility Relationship: Insights from Linear and Non-Linear Quantile Regression," Tinbergen Institute Discussion Papers 13-020/III, Tinbergen Institute.
  22. Arunanondchai, Panit & Sukcharoen, Kunlapath & Leatham, David J., 2020. "Dealing with tail risk in energy commodity markets: Futures contracts versus exchange-traded funds," Journal of Commodity Markets, Elsevier, vol. 20(C).
  23. Agbeyegbe, Terence D., 2015. "An inverted U-shaped crude oil price return-implied volatility relationship," Review of Financial Economics, Elsevier, vol. 27(C), pages 28-45.
  24. Reboredo, Juan C. & Ugolini, Andrea, 2016. "Quantile dependence of oil price movements and stock returns," Energy Economics, Elsevier, vol. 54(C), pages 33-49.
  25. Elie, Bouri & Naji, Jalkh & Dutta, Anupam & Uddin, Gazi Salah, 2019. "Gold and crude oil as safe-haven assets for clean energy stock indices: Blended copulas approach," Energy, Elsevier, vol. 178(C), pages 544-553.
  26. Fabrizio Cipollini & Giampiero Gallo & Andrea Ugolini, 2016. "Median Response to Shocks: A Model for VaR Spillovers in East Asia," Econometrics Working Papers Archive 2016_01, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
  27. Tian, Maoxi & Alshater, Muneer M. & Yoon, Seong-Min, 2022. "Dynamic risk spillovers from oil to stock markets: Fresh evidence from GARCH copula quantile regression-based CoVaR model," Energy Economics, Elsevier, vol. 115(C).
  28. Rémillard, Bruno & Nasri, Bouchra & Bouezmarni, Taoufik, 2017. "On copula-based conditional quantile estimators," Statistics & Probability Letters, Elsevier, vol. 128(C), pages 14-20.
  29. Zhou, Xinmiao & Qian, Huanhuan & Pérez-Rodríguez, Jorge. V. & González López-Valcárcel, Beatriz, 2020. "Risk dependence and cointegration between pharmaceutical stock markets: The case of China and the USA," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).
  30. David E Allen & Abhay K Singh & Robert J Powell & Michael McAleer & James Taylor & Lyn Thomas, 2012. "The Volatility-Return Relationship:Insights from Linear and Non-Linear Quantile Regressions," KIER Working Papers 831, Kyoto University, Institute of Economic Research.
  31. Li, Danyang & Zhang, Zhekai & Cerrato, Mario, 2023. "Factor investing and currency portfolio management," International Review of Financial Analysis, Elsevier, vol. 87(C).
  32. Benlagha, Noureddine, 2020. "Stock market dependence in crisis periods: Evidence from oil price shocks and the Qatar blockade," Research in International Business and Finance, Elsevier, vol. 54(C).
  33. Tian, Maoxi & Guo, Fei & Niu, Rong, 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, Elsevier, vol. 63(C).
  34. Fernando F. Moreira, 2015. "Estimating Portfolio Credit Losses in Downturns," Financial Markets, Institutions & Instruments, John Wiley & Sons, vol. 24(5), pages 391-414, December.
  35. 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, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.
  36. Avdulaj Krenar & Barunik Jozef, 2017. "A semiparametric nonlinear quantile regression model for financial returns," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 21(1), pages 81-97, February.
  37. Sim, Nicholas & Zhou, Hongtao, 2015. "Oil prices, US stock return, and the dependence between their quantiles," Journal of Banking & Finance, Elsevier, vol. 55(C), pages 1-8.
  38. Al-Yahyaee, Khamis Hamed & Mensi, Walid & Maitra, Debasish & Al-Jarrah, Idries Mohammad Wanas, 2019. "Portfolio management and dependencies among precious metal markets: Evidence from a Copula quantile-on-quantile approach," Resources Policy, Elsevier, vol. 64(C).
  39. Harry Joe, 2018. "Dependence Properties of Conditional Distributions of some Copula Models," Methodology and Computing in Applied Probability, Springer, vol. 20(3), pages 975-1001, September.
  40. Komunjer, Ivana, 2013. "Quantile Prediction," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 961-994, Elsevier.
  41. 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, John Wiley & Sons, Ltd., vol. 17(2), pages 91-109, April.
  42. Bernard, Carole & Czado, Claudia, 2015. "Conditional quantiles and tail dependence," Journal of Multivariate Analysis, Elsevier, vol. 138(C), pages 104-126.
  43. Limin Wu, 2020. "Tuning the Bivariate Meta-Gaussian Distribution Conditionally in Quantifying Precipitation Prediction Uncertainty," Forecasting, MDPI, vol. 2(1), pages 1-19, January.
  44. Patton, Andrew J., 2012. "A review of copula models for economic time series," Journal of Multivariate Analysis, Elsevier, vol. 110(C), pages 4-18.
  45. Shanglei Chai, 2015. "Dependence Structure and Hedging of U.S. Spot and Futures Markets in Financial Crisis," Accounting and Finance Research, Sciedu Press, vol. 4(3), pages 1-77, August.
  46. Wattanawongwan, Suttisak & Mues, Christophe & Okhrati, Ramin & Choudhry, Taufiq & So, Mee Chi, 2023. "Modelling credit card exposure at default using vine copula quantile regression," European Journal of Operational Research, Elsevier, vol. 311(1), pages 387-399.
  47. Sukcharoen, Kunlapath & Leatham, David J., 2017. "Hedging downside risk of oil refineries: A vine copula approach," Energy Economics, Elsevier, vol. 66(C), pages 493-507.
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