Relación de dependencia entre el mercado de renta variable español y algunos mercados de bolsa internacionales. Un estudio basado en el análisis copula variante en el tiempo.

Autores/as

  • Antonio Pérez Cambriles Phd student, Facultad de Ciencias Económicas y empresariales (UNED)
  • Sonia Benito Muela Departamento de Análisis Económico de la Facultad de Ciencias Económicas y Empresariales (UNED).

DOI:

https://doi.org/10.32826/reyf.v1i1.342

Palabras clave:

Dependencia, Efecto contagio, Cópulas, Diversificación, Cobertura

Resumen

En este estudio utilizamos cópulas dinámicas para investigar la dependencia entre el mercado de valores español, representado por el índice IBEX35, y algunos mercados internacionales de acciones y materias primas. Los resultados indican que: en primer lugar, las bolsas europeas ofrecen posibilidades de diversificación limitadas. En segundo lugar, los mercados estadounidenses ofrecen mayores posibilidades de diversificación que los mercados europeos, pero es posible que la diversificación no funcione en condiciones de extremas de mercado; en esos casos encontramos una fuerte evidencia del efecto de contagio. En tercer lugar, los mercados asiáticos superan a los mercados estadounidenses y ofrecen mayores posibilidades de diversificación incluso en condiciones de mercado extremas. En cuarto lugar, los activos negociados en el mercado de Shanghai pueden considerarse activos de cobertura en lugar de activos diversificadores. Esta característica es compartida por el Bitcoin y el oro, aunque el papel de este último activo es altamente volátil. Estos resultados brindan información útil para aquellos que buscan diversificar activamente sus carteras internacionalmente y administrar sus activos en todo el mundo. Finalmente, observamos que el grado de dependencia derivado del análisis de correlaciones es notablemente superior al sugerido por el análisis de copula; esto puede deberse a que el coeficiente de correlación no considera la heterocedasticidad condicional, por lo que las correlaciones estarán sesgadas al alza.

Citas

Baig, T. and Goldfajn, I., 1999. Financial Market Contagion in the Asian Crisis, IMF Staff Papers. Volume 46, 167–195.

Baur, D.G., and Lucey, B.M., 2010. Is Gold a Hedge or a Safe Haven? An analysis of Stocks Bonds and Gold, The Financial Review. Volume 45, 217-229.

Baur, D., 2012. Asymmetric volatility in the gold market, Journal of Alternative Investments. Volume 14, 26–38.

Bouri, E., Molnár, P., Azzi, G., Roubaud, D., and Hagfors, L. I., 2017b. On the hedge and safe haven properties of Bitcoin: is it really more than a diversifier? Finance Re-search Letters. Volume 20,192-198.

Bouri, E., Jalkh N., Molnár, P., Roubaud, D., 2017a. Bitcoin for energy commodities before and after the December 2013 crash: diversifier, hedge or safe haven? Applied Economics. Volume 49(50), 5063-5073.

Calvo, G.A., L., Leiderman, L. and Reinhart, C.M., 1996. Inflows of Capital to Developing Countries in the 1990s, Journal of Economic Perspectives. Volume 10(2), 123-139.

Case, B., Yang, Y., and Yildirin, Y., 2012. Dynamic Corre-lations Among Asset Classes: REIT and Stock Returns, The Journal of Real Estate Finance and Economics. Volume 44, 298–318.

Changquing, L., Chi, X., Cong, Y., and Yan, X., 2015. Measuring financial market risk contagion using dynamic MRS-Copula models: The case of Chinese and other in-ternational stock markets, Economic Modelling. Volume 51, 657-671

Cherubini, U., and Luciano, E., 2001. Value at risk Trade off and Capital Copulas, Economic Notes. Volume 30, 235-256

Das, S., 2016. Cointegration of Bombay Stock Exchange with Major Asian Markets—A Copula Approach, Global Business Review. Volume 13(3), 566-581

Ding, Z., Granger, C.W.J., and Engle, R.F., 1993. A long memory property of stock market returns and a new model, Journal of Empirical Finance. Volume 1, 83-106.

Dyhrberg, A. H., 2016. Bitcoin, gold and the dollar – A GARCH volatility analysis, Finance Research Letters. Vol-ume 16, 85-92

Engle, R., 1982. Autoregressive Conditional Heteroscedas-ticity with Estimates of the Variance of United Kingdom Inflation. Econometrica. Volume, 50(4) 987-1007.

Eisl, A., Gasser, S., Weinmayer, K., 2015. Caveat Emptor: Does Bitcoin Improve Portfolio Diversification? Available at SSRN: 2408997. http://dx.doi.org/10.2139/ssrn.2408997

Fang, Y., Madsen, L., and Liu L., 2007. Comparison of Two Methods to Check Copula Fitting, IAENG Interna-tional Journal of Applied Mathematics. Volume, 44(1), 1-9.

Feng, W., Wang, Y., Zhang, Z., 2018. Can Cryptocurren-cies Be a Safe Haven: A Tail Risk Perspective Analysis, Applied Economics. Volume 50(44), 4745-4762.

Fermanian, J.D., 2005. Goodness-of-fit tests for copulas, Journal of Multivariate Analysis. Volume 95, 119–152.

Forbes, K., and Rigobon, R., 2002. No Contagion, Only Interdependence: Measuring Stock Market Comove-ments, The Journal of Finance. Volume, 57(5), 2223-2261.

Frey, R., and McNeil, A., 2003. Dependent Defaults in Models of Portfolio Credit Risk, Journal of Risk. Volume 6(1): 59-92.

Gkillas, K., Longin, F., 2018. Is Bitcoin the New Digital Gold? Evidence From Extreme Price Movements in Fi-nancial Markets. Evidence From Extreme Price Move-ments in Financial Markets (October 20, 2018). Available at SSRN: https://ssrn.com/abstract=3245571

Gregoire, V., Genest, C., and Gendron, M., 2008. Using copulas to model price dependence in Energy Markets, Energy Risk.Volume, 6(3), 62-68.

He, X.D., Jin, H. and Zhou, X.Y., 2015. Dynamic portfolio choice when risk is measured by weighted VaR, Math-ematics of operations research. Volume 40(3).

Hon, M. T., Strauss, J. K. and Yon S-K, 2007. Deconstruct-ing the Nasdaq bubble: A look at contagion across in-ternational stock markets, Journal of International Fi-nancial Markets, Institutions and Money. Volume 17(3), 213-230.

Horta, P., Mendes, C. and Vieira, I. 2010. Contagion ef-fects of the subprime crisis in the European NYSE Eu-ronext markets, Portuguese Economic Journal. Volume 9, 115–140.

Hussain, S. I. and Li, S., 2018. The dependence structure between Chinese and other major stock markets using extreme values and copulas, International Review of Economics & Finance. Volume 56, 421-437.

Joe, H., 1997. Multivariate Models and Dependence Con-cepts, Chapman and Hall, London.

Jondeau, E., and Rockinger, M., 2006. The Copula-GARCH model of conditional dependencies: An international stock market application, Journal of International Mon-ey and Finance. Volume 25(5), 827-853.

Junker, M., Szimayer, A., and Wagner, N., 2006. Nonline-ar Term Structure: Dependence: Copula Functions, Empirics and Risk Implications, Journal of Banking and Finance. Volume 30, 1171-1199.

Kang, S.H., Mclver, R.P., Arreola, J., 2019. Co-movements between Bitcoin and Gold: A wavelet co-herence analysis, Physica A: Volume 536, 1-9.

Kenourgios, D., Samitas, A. and Paltalidis, N., 2010. Fi-nancial crises and stock market contagion in a multivar-iate time-varying asymmetric framework, Journal of In-ternational Financial Markets, Institutions & Money. Vol-ume 21(1), 92-106.

King, M. A. and Wadhwani, S., 1990. Transmission of Vola-tility between Stock Market, The Review of Financial Studies. Volume 3(1), 5–33

Klein, T., Hien, P.T. and Walther, T., 2018. Bitcoin is not the New Gold – A comparison of volatility, correlation, and portfolio performance, International Review of Fi-nancial Analysis. Volume 59, 105-116,

Luciano, E., and Marena, M., 2002. Copula as a new tool in financial modelling, Operational Research: An Inter-national Journal. Volume 2: 139-155.

Mandelbrot, B., 1963 New Methods in Statistical Econom-ics, The Journal of Political Economy. Volume 71(5), 421-440.

Meucci, A., 2010. Managing Diversification, Bloomberg Education & Quantitative Research and Education Pa-per, 74-79.

Nguyen, C., Ishac, B.M., and Henri, D., 2017. Are Vietnam and Chinese stock markets out of the US contagion ef-fect in extreme events? Physica A: Statistical Mechanics and its Applications. Volume 480(15) 10-21

Patton, A., 2006. Modelling asymmetric exchange rate dependence, International Economic Review. Volume 47(2), 527-556.

Rajwani, S. and Kumar, D., 2019. Measuring Dependence Between the USA and the Asian Economies: A Time-varying Copula Approach. Global Business Review, Vol-ume 27.

Reboredo, J.C., 2011. How do crude oil prices co-move? A copula approach. Energy Economics. Volume 33(5), 948-955

Rong, N., and Trück, S., 2014. Modelling the Dependence Structure Between Australian Equity and Real Estate Market – a Copula Approach, Australian Accounting, Business and Finance Journal. Volume 8(5): 93-113.

Samitas, A. and Tsakalos, I., 2013. How can a small coun-try affect the European economy? The Greek contagion phenomenon, Journal of International Financial Mar-kets, Institutions and Money. Volume 25, 18-32

Syriopoulos, T. and Roumpis, R., 2009. Dynamic correla-tions and volatility effects in the Balkan equity markets, Journal of International Financial Markets, Institutions and Money. Volume 19(4), 565-587.

Yang, J., Zhou, Y. and Leung, W.K., 2012. Asymmetric Correlation and Volatility Dynamics among Stock, Bond, and Securitized Real Estate Markets. The Journal of Real Estate Finance and Economics. Volume 45, 491–521.

Wang, Y-Q, Shi-wen, L. 2011. Financial market openness and risk contagion: A time-varying Copula approach. College of Finance, Zhejiang Gongshang University, 31(4): 778-784.

Weng, X., Wei, Y. and Huang, D., 2012. Measuring conta-gion between energy market and stock market during financial crisis: A copula approach. Energy Economics Volume 34(5) 1435-1446

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Publicado

2023-03-09