VOLATILITY SPILLOVER AND CONTAGION EFFECTS BETWEEN EURODOLLAR FUTURE AND ZERO COUPONS MARKETS: EVIDENCE FROM ITALY
Keywords:
DCC-GARCH model, EURODOLLAR future market, zero coupons, financial contagion, dynamic conditional correlations
Abstract
This paper examines the time-varying conditional correlations between Eurodollar futures market and zero coupons of Banca Fideuram. We apply a bivariate dynamic conditional correlation (DCC) GARCH model in order to capture potential contagion effects between the markets for the period 2005-2017. Empirical results reveal contagion during the under investigation period regarding the twenty one bivariate models, showing that Eurodollar futures market has a major impact on the zero coupons of Banca Fideuram. Findings have crucial implications for policymakers who provide regulations for the above derivative markets.
References
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Antonakakis, N., Floros, C., & Kizys, R. (2016). Dynamic spillover effects in futures markets: UK and US evidence. International Review of Financial Analysis 48, 406–418. DOI: 10.1016/j.irfa.2015.03.008.
Bhargava V., & Malhotra D.K. (2007). The relationship between futures trading activity and exchange rate volatility, revisited, Journal of Multinational Financial Management 17, 95-111. DOI: 10.1016/j.mulfin.2006.05.001.
Bollerslev, T. (1986). Generalized autoregressive conditional heteroskedasticity. Journal of Econometrics 31(3), 307-327. DOI: 10.1016/0304-4076(86)90063-1.
Dickey, D. A., & Fuller, W. A. (1979). Distribution of the Estimators for Autoregressive Time Series with a Unit Root. Journal of the American Statistical Association 74, 427-431. DOI: 10.2307/2286348.
Dimitriou, D. and Kenourgios, D. (2015). Contagion of the global financial crisis and the real economy: A regional analysis. Economic Modelling 44, 283-293. DOI: 10.1016/j.econmod.2014.10.048.
Dimitriou, D, Kenourgios, D., & Simos, T. (2013). Global financial crisis and emerging stock market contagion: A multivariate FIAPARCH-DCC approach. International Review of Financial Analysis 30, 46-56. DOI: 10.1016/j.irfa.2013.05.008.
Grammatikos, T., & Saunders, A. (1986). Futures price variability: A test of maturity and volume effects. Journal of Business 59(2), 319-330. DOI: 10.1086/296330.
Glen, J., & Jorion, P. (1993). Currency Hedging for International Portfolios. Journal of Finance 48, 1865-1886. DOI: 10.2307/2329070.
Engle, R. F. (2002). Dynamic conditional correlation-a simple class of multivariate GARCH models. Journal of Business & Economic Statistics 20, 339-350. DOI: 10.1198/073500102288618487.
Forbes, K., & Rigobon, R. (2002). No contagion, Only Interdependence: Measuring Stock Market CoMovements. Journal of Finance, 57, 2223-2261. DOI: 10.1111/0022-1082.00494.
Hosking, J. R. M. (1980). The Multivariate Portmanteau Statistic. Journal of the American Statistical Association 75(371), 602-608. DOI: 10.2307/2287656.
Huang, B.N., Yang, C.W., & Hwang, M.J. (2009). The dynamics of a nonlinear relationship between crude oil spot and futures prices: a multivariate threshold regression approach. Energy Economics, 31, 91–98. DOI: 10.1016/j.eneco.2008.08.002.
Baur, D.G., & McDermott, T.K. (2010). Is gold a safe haven? International evidence. J. Bank. Finance, 34, 1886–1898. DOI: 10.1016/j.jbankfin.2009.12.008.
Corsetti, G., Pericoli, M., & Sbacia, M. (2005). Some contagion, some interdependence’: More pitfalls in tests of financial contagion. Journal of International Money and Finance 25(8), 1177-1199. DOI: 10.1016/j.jimonfin.2005.08.012.
Li, Y., & Giles, D. E. (2015). Modelling volatility spillover effects between developed stock markets and Asian emerging stock markets. International Journal of Finance and Economics 20, 155-177. DOI: 10.1002/ijfe.1506.
McLeod, A. I., & Li, W. K. (1983). Diagnostic checking ARMA time series models using squared-residuals autocorrelations. Journal of Time Series Analysis 4(4), 269-273. DOI: 10.1111/j.1467-9892.1983.tb00373.x.
Mensi, W., Beljid, M., Boubaker, A., & Managi, S. (2013). Correlations and volatility spillovers across commodity and stock markets: Linking energies, food, and gold. Economic Modelling 32, 15-22. DOI: 10.1016/j.econmod.2013.01.023.
Sehgal, S., Ahmad W., & Deisting, F. (2015). An investigation of price discovery and volatility spillovers in India’s foreign exchange market. Journal of Economic Studies 42(2), 261-284. ISSN: 0144-3585.
Sensoy, A., Hacihasanoglu, E., & Nguyen, D.K., 2015. Dynamic convergence of commodity futures: Not all types of commodities are alike. Resources Policy 44(3). DOI: 10.1016/j.resourpol.2015.03.001.
Singhal S., & Ghosh, S. (2016). Returns and volatility linkages between international crude oil price, metal and other stock indices in India: Evidence from VAR-DCC-GARCH models. Resources Policy. Vol. 50(3), 276-288 (2016) DOI: 10.1016/j.resourpol.2016.10.001.
Tolgahan, Y. (2010). Improving Portfolio Optimization by DCC And DECO GARCH: Evidence from Istanbul Stock Exchange. Munich University Library Paper. URI: https://mpra.ub.uni-muenchen.de/id/eprint/27314.
Tsiaras, K., & Simos, T. (2020). FOREX and equity markets spillover effects among USA, Brazil, Italy, Germany and Canada in the aftermath of the Global Financial Crisis. Journal of Finance and Accounting Research 2(1). DOI: 10.32350/JFAR/0201/03.
Tsiaras, K. (2020). Dynamic relationship between future FOREX markets in the post Global Financial Crisis. Journal of Quantitative Methods 4(1), 30-52. DOI: 10.29145/2020/jqm/040102.
Tsiaras, K. (2020). Contagion in crude oil future market and 3Y, 4Y and 5Y CDS markets for the post-Global Financial Crisis: A multivariate GARCH-cDCC approach. Ekonomická revue. Accepted Paper for publication in the upcoming issue.
Published
2020/10/14
Section
Original Scientific Paper
