A new time-varying optimal copula model identifying the dependence across markets

References

• Aloui, R., Hammoudeh, S. and Nguyen, D.K., A time-varying copula approach to oil and stock market dependence: The case of transition economies. Energy Econ., 2013, 39, 208–221.10.1016/j.eneco.2013.04.012
   Web of Science ®Google Scholar
• Caillault, C. and Guégan, D., Empirical estimation of tail dependence using copulas: Application to Asian markets. Quant. Finance, 2005, 5, 489–501.10.1080/14697680500147853
   Web of Science ®Google Scholar
• Chan, K.F., Treepongkaruna, S., Brooks, R. and Gray, S., Asset market linkages: Evidence from financial, commodity and real estate assets. J. Bank. Finance, 2011, 35, 1415–1426.
   Web of Science ®Google Scholar
• Cherubini, U., Luciano, E. and Vecchiato, W., Copula Methods in Finance, 2004 (Wiley: Chichester).10.1002/9781118673331
   Google Scholar
• Creal, D., Koopman, S.J. and Lucas, A., A general framework for observation driven time-varying parameter models. Tinbergen Institute Discussion Paper, 08–108/4, 2008.
   Google Scholar
• Delatte, A.L. and Lopez, C., Commodity and equity markets: Some stylized facts from a copula approach. J. Bank. Finance, 2013, 37, 5346–5356.
   Web of Science ®Google Scholar
• Dias, A. and Embrechts, P., Dynamic copula models for multivariate high-frequency data in finance. Manuscript, ETH Zurich, 2004.
   Google Scholar
• Fan, J. and Gu, J., Semiparametric estimation of value at risk. Econometrics J., 2003, 6, 261–290.10.1111/(ISSN)1368-423X
   Google Scholar
• Fermanian, J.D. and Scaillet, O., Some statistical pitfalls in copula modeling for financial applications. FAME Working Paper, No. 108, 2004.
   Google Scholar
• Garcia, R. and Tsafack, G., Dependence structure and extreme comovements in international equity and bond markets. J. Bank. Finance, 2011, 35, 1954–1970.
   Web of Science ®Google Scholar
• Giacomini, E., Härdle, W. and Spokoiny, V., Inhomogeneous dependence modeling with time-varying copulae. J. Bus. Econ. Stat., 2009, 27, 224–234.
   Web of Science ®Google Scholar
• Graham, M., Kiviaho, J. and Nikkinen, J., Short-term and long-term dependencies of the S&P 500 index and commodity prices. Quant. Finance, 2013, 13, 583–592.10.1080/14697688.2013.768773
   Web of Science ®Google Scholar
• Guégan, D. and Zhang, J., Change analysis of a dynamic copula for measuring dependence in multivariate financial data. Quant. Finance, 2010, 10, 421–430.10.1080/14697680902933041
   Web of Science ®Google Scholar
• Hafner, C.M. and Reznikova, O., Efficient estimation of a semiparametric dynamic copula model. Comput. Stat. Data Anal., 2010, 54, 2609–2627.
   Web of Science ®Google Scholar
• Harris, R.D.F. and Shen, J., Robust estimation of the optimal hedge ratio. J. Futures Markets, 2003, 23, 799–816.10.1002/(ISSN)1096-9934
   Web of Science ®Google Scholar
• Hill, J.B., Efficient tests of long-run causation in trivariate VAR processes with a rolling window study of the money–income relationship. J. Appl. Econ., 2007, 22, 747–765.10.1002/(ISSN)1099-1255
   Web of Science ®Google Scholar
• Hollander, M. and Wolfe, D.A., Nonparametric Statistical Methods, 1973 (Wiley: New York, NY).
   Google Scholar
• Hu, L., Dependence patterns across financial markets: A mixed copula approach. Appl. Financial Econ., 2006, 16, 717–729.10.1080/09603100500426515
   Google Scholar
• Ji, Q., System analysis approach for the identification of factors driving crude oil prices. Comput. Ind. Eng., 2012, 63, 615–625.
   Web of Science ®Google Scholar
• Ji, Q. and Fan, Y., How does oil price volatility affect non-energy commodity markets? Appl. Energy, 2012, 89, 273–280.10.1016/j.apenergy.2011.07.038
   Web of Science ®Google Scholar
• Joe, H., Multivariate Models and Dependence Concepts, 1997 (Chapman & Hall: London).10.1201/CHMONSTAAPP
   Google Scholar
• Junker, M., Szimayer, A. and Wagner, N., Nonlinear term structure dependence: Copula functions, empirics, and risk implications. J. Bank. Finance, 2006, 30, 1171–1199.
   Web of Science ®Google Scholar
• Kole, E., Koedijk, K. and Verbeek, M., Selecting copulas for risk management. J. Bank. Finance, 2007, 31, 2405–2423.
   Web of Science ®Google Scholar
• Manner, H. and Reznikova, O., A survey on time-varying copulas: Specification, simulations, and application. Econometric Rev, 2012, 31, 654–687.10.1080/07474938.2011.608042
   Web of Science ®Google Scholar
• Miller, D.J. and Liu, W.H., Improved estimation of portfolio value-at-risk under copula models with mixed marginals. J. Futures Markets, 2006, 26, 997–1018.10.1002/(ISSN)1096-9934
   Web of Science ®Google Scholar
• Narayan, P.K., Narayan, S. and Prasad, A., Understanding the oil price-exchange rate nexus for the Fiji islands. Energy Econ., 2008, 30, 2686–2696.10.1016/j.eneco.2008.03.003
   Web of Science ®Google Scholar
• Nelsen, R.B., An Introduction to Copulas, 1999 (Springer: New York, NY).10.1007/978-1-4757-3076-0
   Google Scholar
• Ning, C., Dependence structure between the equity market and the foreign exchange market–A copula approach. J. Int. Money and Finance, 2010, 29, 743–759.10.1016/j.jimonfin.2009.12.002
   Web of Science ®Google Scholar
• Okimoto, T., New evidence of asymmetric dependence structures in international equity markets. J. Financial and Quant. Anal., 2008, 43, 787–815.10.1017/S0022109000004294
   Web of Science ®Google Scholar
• Patton, A.J., Modelling asymmetric exchange rate dependence. Int. Econ. Rev., 2006, 47, 527–556.10.1111/iere.2006.47.issue-2
   Web of Science ®Google Scholar
• Patton, A.J., A review of copula models for economic time series. J. Multivariate Anal., 2012, 110, 4–18.10.1016/j.jmva.2012.02.021
   Web of Science ®Google Scholar
• Penzer, J., Schmid, F. and Schmidt, R., Measuring large comovements in financial markets. Quant. Finance, 2012, 12, 1037–1049.10.1080/14697688.2010.495950
   Web of Science ®Google Scholar
• Sklar, A., Fonctions de répartition à n dimensions et leurs marges. Publications de l’Institut Statistique de l’Université Paris, 1959, 8, 229–231.
   Google Scholar
• Swanson, N.R., Money and output viewed through a rolling window. J. Monetary Econ., 1998, 41, 455–474.10.1016/S0304-3932(98)00005-1
   Web of Science ®Google Scholar
• Wu, C.C. and Lin, Z.Y., An economic evaluation of stock-bond return comovements with copula-based GARCH models. Quant. Finance, 2014, 14, 1283–1296.10.1080/14697688.2012.727213
   Web of Science ®Google Scholar