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A Comparison of Spillover Effects before, during and after the 2008 Financial Crisis

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DOI: 10.4236/am.2014.54057    3,003 Downloads   3,775 Views   Citations


This paper applies graphical modelling to the S & P 500, Nikkei 225 and FTSE 100 stock market indices to trace the spillover of returns and volatility between these three major world stock market indices before, during and after the 2008 financial crisis. We find that the depth of market integration changed significantly between the pre-crisis period and the crisis and post-crisis period. Graphical models of both return and volatility spillovers are presented for each period. We conclude that graphical models are a useful tool in the analysis of multivariate time series where tracing the flow of causality is important.

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Rea, A. , Rea, W. , Reale, M. and Scarrott, C. (2014) A Comparison of Spillover Effects before, during and after the 2008 Financial Crisis. Applied Mathematics, 5, 601-614. doi: 10.4236/am.2014.54057.


[1] King, M.A. and Wadhwani, S. (1990) Transmission of Volatility between Stock Markets. The Review of Financial Studies, 3, 5-33.
[2] Bray, M. (1985) Rational Expectations, Information and Asset Markets: An Introduction. Oxford Economic Papers, 37, 161-195.
[3] Park, J. and Fatemi, A.M. (1993) The Linkages between the Equity Markets of Pacific-Basic Countries and Those of the US, UK, and Japan: A Vector Autoregression Analysis. Global Finance Journal, 4, 49-64.
[4] Kang, S.H., Cheong, C. and Yoon, S.-M. (2011) Structural Changes and Volatility Transmission in Crude Oil Markets. Physica A, 390, 4317-4324.
[5] Lamoureux, C.G. and Lastrapes, W.D. (1990) Persistance in Variance, Structural Change, and the GARCH Model. Journal of Business and Economic Statistics, 8, 225-234.
[6] Bollerslev, T. (1986) Generalized Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 31, 307327.
[7] Mulyadi, M.S. (2009) Volatility Spillover in Indonesia, USA, and Japan Capital Markets. MPRA Paper 16914, University Library of Munich, Munich.
[8] Martins, M. and Poon, S.-H. (2001) Returns Synchronization and Daily Correlation Dynamics between International Stock Markets. Journal of Banking and Finance, 25, 1805-1827.
[9] Engle, R.F. (1982) Autoregressive Conditional Heteroskedasticity with Estimates of the Variance of UK Inflation. Econometrica, 50, 987-1008.
[10] Nelson, D.B. (1991) Stationarity and Persistence in the GARCH(1,1) Model. Econometrica, 59, 318-334.
[11] Baillie, R.T., Bollerslev, T. and Mikkelson, H.O. (1996) Fractionally Integrated Generalised Autoregressive Conditional Heteroskedasticity. Journal of Econometrics, 74, 3-30.
[12] Tsay, R.S. (2002) Analysis of Financial Time Series. John Wiley & Sons, Inc., Hoboken.
[13] Hamao, Y., Masulis, R.W. and Ng, V. (1990) Correlations in Prices Changes and Volatility across International Stock Markets. The Review of Financial Studies, 3, 281-307.
[14] Ng, A. (2000) Volatility Spillover Effects from Japan and the US to the Pacific-Basin. Journal of International Money and Finance, 19, 207-233.
[15] Savva, C., Osborn, D.R. and Gill, L. (2005) Volatility, Spillover Effects and Correlations in US and Major European Markets. Money Macro and Finance (MMF) Research Group Conference 2005, Money Macro and Finance Research Group.
[16] Singh, P., Kumar, B. and Pandey, A. (2010) Price and Volatility Spillovers across North American, European and Asian Stock Markets. International Review of Financial Analysis, 19, 55-64.
[17] Al-Deehani, T. and Moosa, I.A. (2006) Volatility Spillover in Regional Emerging Stock Markets: A Structural TimeSeries Approach. Emerging Markets Finance & Trade, 42, 78-89.
[18] Wright, S. (1921) Correlation and Causation. Journal of Agricultural Research, 20, 557-585.
[19] Lauritzen, S.L. (1996) Graphical Models. Oxford University Press, Oxford.
[20] Edwards, D. (2000) Introduction to Graphical Modelling. 2nd Edition, Springer, Berlin.
[21] Whittaker, J. (2009) Graphical Models in Applied Multivariate Statistics. Wiley, Hoboken.
[22] Dahlhaus, R. (2000) Graphical Interaction Models for Multivariate Time Series. Metrika, 51, 157-172.
[23] Reale, M. (1998) A Graphical Modelling Approach to Time Series. PhD Thesis, Lancaster University, Lancaster.
[24] Reale, M. and Tunnicliffe-Wilson, G. (2001) Identification of Vector AR Models with Recursive Structural Errors Using Conditional Independence Graphs. Statistical Methods and Applications, 10, 49-65.
[25] Reale, M. and Tunnicliffe-Wilson, G. (2002) The Sampling Properties of Conditional Independence Graphs for Structural Vector Autoregressions. Biometrika, 89, 457-461.
[26] Lauritzen, S.L. and Spiegelhalter, D.J. (1988) Local Computations with Probabilities on Graphical Structures and Their Application to Expert Systems. Journal of the Royal Statistical Society. Series B, 50, 157-224.
[27] Akaike, H. (1973) Information Theory and an Extension of the Maximum Likelihood Principle. In: Petrov, B. and Csaki, F., Eds., 2nd International Symposium on Information Theory, Akademia Kadio, Budapest, 267-281.
[28] Cappelli, C., Penny, R.N., Rea, W.S. and Reale, M. (2008) Detecting Multiple Mean Breaks at Unknown Points with Atheoretical Regression Trees. Mathematics and Computers in Simulation, 78, 351-356.
[29] Breiman, L., Friedman, J., Olshen, R. and Stone, C. (1993) Classification and Regression Trees. Chapman & Hall/ CRC.
[30] Ripley, B. (2011) Tree: Classification and Regression Trees. R Package Version 1.0-28.
[31] R Development Core Team (2009) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna.
[32] Hurvich, C.M., Simonoff, J.S. and Tsai, C. (1998) Smoothing Parameter Selection in Non-Parametric Regression Using an Improved Akaike Information Criterion. Journal of the Royal Statistical Society Series B, 60, 271-293.
[33] Hannan, E.J. and Quinn, B.G. (1979) The Determination of the Order of an AutoRegression. Journal of the Royal Statistical Society Series B, 41, 190-195.
[34] Schwarz, G. (1978) Estimating the Dimension of a Model. The Annals of Statistics, 6, 461-464.

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