Dependency structure between the markets of Iran, Turkey, China and the United Arab Emirates, according the approach of Copula – Markov Switching
Subject Areas : Financial Knowledge of Securities AnalysisS. Mozaffar Mirbargkar 1 , Maryam Sohrabi 2
1 - Assistant Professor in Economy, Department of Management, Rasht Branch, Islamic Azad University Rasht, Iran
2 - P.HD. Student, Financial engineering, Department of Management, Rasht Branch, Islamic Azad University Rasht, Iran
Keywords: share market, dependence structure, GARCH models, Markov switching-Copula functi,
Abstract :
Studying, and analyzing the dependency structure between the markets at the economic boom and bust have been suggested by the researchers and theorists of different areas. Furthermore, there have been various models to explain the correlation between the financial markets. Among them, the Copula model has a high ability to recognize the asymmetric dependence structure. The present research is going to study the dependency structure in the financial markets of four countries; Iran, the United Arab Emirates, Turkey and China at the boom and bust cycling in the period of 2014-2017, applying conditional heterogeneity variance model (GARCH), the Markov switching approach, and the Copula functions. The results illustrate that there is an asymmetric structure in every regime, as at the recession time, the correlation between these markets and Iranian market would be higher than the boom time.
* ابونوری، اسمعیل ؛ محمدرضا عبداللهی، (1390)، "ارتباط بازارهای سهام ایران، آمریکا، ترکیه و مالزی در یک مدل گارچ چند متغیره"، فصلنامه بورس اوراق بهادار، دوره 4، تابستان 1390، شماره چهاردهم، صص: 79-61
* جعفر عبدی، اکبر و غلامرضا کشاورز حداد، (1389)، "بررسی ارتباط میان بازارهای سهام تهران و دبی"، پایاننامه کارشناسی ارشد، دانشکده مدیریت و اقتصاد دانشگاه صنعتی شریف، تیرماه 1389 .
* حسینی افتخار سادات کفاش، علی رستمی (1392)، " بررسی تأثیر نوسانات شاخص قیمت و بازده نقدی بورس بر بازدهی سرمایهگذاری در طلا"، فصلنامـه علمی، پژوهشی دانش سرمایهگـذاری، دوره دوم، شماره هشتم، زمستان 1392، صص: 254-235
* کشاورز حداد، غلامرضا، مهرداد حیرانی (1393). "برآورد ارزش در معرض ریسک با وجود ساختار وابستگی بین بازدهیهای مالی: رهیافت مبتنی بر توابع کاپولا" – مجله تحقیقات اقتصادی دانشگاه تهران- دوره 49، شماره 4،زمستان 1393، صص: 902-869
* Ang A., and G., Bekaert, 2002a, International Asset Allocation with Regime Shifts. Review of Financial Studies, 15, 1137-1187.
* Ang, A. and Chen, J. (2002), "Asymmetric correlations of equity portfolios", Journal of Financial Economics 63(3), 443-94.
* Bae, K., Karolyi, G., and Stulz, R. (2003). A new approach to measuring financial contagion. Review of Financial Studies, 16(3):717.
* Baig and Goldfajn, (1999). T. Baig, I. GoldfajnFinancial market contagion in the Asian crisis. International Monetary Fund Staff Papers, 46 (2), pp. 167-195
* Bartram, S. M. and Dufey, G. (2001). ìInternational portfolio investment: theory, evidence, and institutional framework,îFinancial Markets, Institutions and Instruments 10 (3), 85-155
* Bollerslev, T. (1987), "A conditional heteroskedastic time series model for speculative prices and rates of return", Review of Economics and Statistics 69, 542-547.
* Bussière, Matthieu – Mulder, Christian,(1999). “Political Instability and Economic Vulnerability”, IMF Working Paper, WB/99/46
* Canela, M.A., Collazo, P. (2006): Modelling dependence in Latin American markets using copula functions. Working Paper, IESE Business School (Barcelona)
* Chesney, F., and Jondeau, E.(2000), “Does Correlation Between Stock Returns Really Increase During Turbulent Period?”, Banque de France, 2000, Working Paper.
* Chiang, T. C., & Chen, X. (2016). Stock returns and economic fundamentals in an emerging market: An empirical investigation of domestic and global market forces. International Review of Economics & Finance, 43, 107–120.
* Ciner, C., Gurdgiev, C., & Lucey, B. (2013). Hedges and safe havens: An examination of stocks, bonds, gold, oil and exchange rates. International Review of Financial Analysis, 29, 202–211.
* Clayton, David G. (1978). "A model for association in bivariate life tables and its application in epidemiological studies of familial tendency in chronic disease incidence". Biometrika. 65 (1): 141–151
* Costinot, A., Roncalli, T., & Teiletche, J. (2000). Revisiting the dependence between financial markets with copulas. Working Paper.
* Da Silva Filho, O.C., Ziegelmann, F.A. and Dueker, M.J. (2012) Modeling Dependence Dynamics through Copulas with Regime Switching. Insurance: Mathematics and Economics, 50, 346-356
* Dibbmann, J., Brechmann, E., Czado C. & Kurowicka, D, (2013). Selecting and estimating regular vine copulae and application to nancial returns. In: Computational Statistics & Data Analysis, vol 59, pp. 52-69.
* Engle, R. F. – Kroner, K. F. 1995: Multivariate simultaneous generalized ARCH. Econometric Theroy, 11, 122-150. p.
* Hartmann, P., Straetmans, S. and de Vries, C. G. (2004). Asset market linkages in crisis periods. Review of Economics and Statistics 86(1), 313-326. DOI: 10.1162/003465304323023831
* J. Dibmann, E.C. Brechmann, C. Czado, D. Kurowicka, Selecting and estimating regular vine copula and application to financial returns, Comput. Statist. Data Anal. 59 (2013) 52–69.
* Longin, Francois mname and Solnik, Bruno mname (2001), Extreme Correlation of International Equity Markets (April 1, 2000). Journal of Finance, Vol. LVI, No. 2,
* Mensi, W., Hammoudeh, S., Reboredo, J.C., Nguyen, D.K., (2014). Do global factors impact BRICS stock markets? A quantile regression approach. Emerg. Mark. Rev. 19, 1–17.
* Nelson, Roger B. (1998), An Introduction to Copula, Springer-Verlag, New York
* Ning, C.(2010), The dependence structure between the Canadian stock market and the US/Canada exchange rate: A copula approach (with L. Michelis), Canadian Journal of Economics, 43(3), 1016-1039, 2010.
* Patton, A.J., (2006a), "Modelling asymmetric exchange rate dependence", International Economics Review 47 (2), 527-556
* Patton, Andrew J. (2004), "On the Out-of-Sample Importance of Skewness and Asymmetric Dependence for Asset Allocation." Journal of Financial Econometrics, Vol. 2, No. 1, pp. 130-168.
* Ramchand, L and R Susmel (1998): “Volatility and cross correlation across major stock markets”. Journal of Empirical Finance, 5, pp. 397-416
* Shahzad, S.J.H., Ameer, S., Shahbaz, M., (2016). Disaggregating the correlation under bearish and bullish markets: a quantile-quantile approach''. Econ. Bull. 36 (4),2465–2473.
* Sklar, A. (1959). Fonctions de répartition á n dimensions et leurs marges. Fonctions de repartition á n dimensions et leurs marges. Publications de l'Institut de Statistique de l'Université de Paris, 8229–8231.
* Smith K., Czado, C., Frigessi, A., & Bakken, H. (2012). Pair-copula constructions of multiple dependence. Insurance: Mathematics and Economics, 44(2), 182–198.
* Tansuchat Roengchai, Woraphon Yamaka Kritsana Khemawanit Songsak Sriboonchitta (2017), Analyzing the Contribution of ASEAN Stock Markets to Systemic Risk. Robustness in Econometrics
* Vithessonthi, C., & Kumarasinghe, S. (2016). Financial development, international trade integration, and stock market integration: Evidence from Asia. Journal of Multinational Financial Management, 35, 79–92.
* Wang, G. J., Xie, C., Lin, M., & Stanley, H. E. (2017). Stock market contagion during the global financial crisis: A multiscale approach. Finance Research Letters, 22, 163–168.
* Yang, L., Tian, S., Yang, W., Xu, M., & Hamori, S. (2018). Dependence structures between Chinese stock markets and the international financial market: Evidence from a wavelet-based quantile regression approach. North American Journal of Economics and Finance, 45, 116-137.
* Zhang Bangzheng, Yu Wei, Jiang Yu, Xiaodong Lai, Zhenfeng Peng (2014) Forecasting VaR and ES of stock index portfolio: A Vine copula method Original Research Article Pages 112-124
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