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Volatility spillovers from the US to Australia and China across the GFC

Author

Listed:
  • David E Allen

    (School of Accounting, Finance and Economics, Edith Cowan University)

  • Michael McAleer

    (Econometric Institute Erasmus School of Economics Erasmus University Rotterdam and Tinbergen Institute The Netherlands and Institute of Economic Research Kyoto University Japan and Department of Quantitative Economics Complutense University of Madrid Spain)

  • Robert J Powell

    (School of Accounting, Finance and Economics, Edith Cowan University)

  • Abhay Kumar Singh

    (School of Accounting, Finance and Economics, Edith Cowan University)

Abstract

This paper features an analysis of volatility spillover effects from the US market, represented by the S&P500 index to the Australian capital market as represented by the Australian S&P200 for a period running from 12th September 2002 to 9th September 2012. This captures the impact of the Global Financial Crisis (GFC). The GARCH analysis features an exploration of whether there are any spillover effects in the mean equations as well as in the variance equations. We adopt a bi-mean equation to model the conditional mean in the Australian markets plus an ARMA model to capture volatility spillovers from the US. We also apply a Markov Switching GARCH model to explore the existence of regime changes during this period and we also explore the non-constancy of correlations between the markets and apply a moving window of 120 days of daily observations to explore time-varying conditional and fitted correlations. There appears to be strong evidence of regime switching behaviour in the Australian market and changes in correlations between the two markets particularly in the period of the GFC. We also apply a tri-variate Cholesky-GARCH model to include potential effects from the Chinese market, as represented by the Hang Seng Index

Suggested Citation

  • David E Allen & Michael McAleer & Robert J Powell & Abhay Kumar Singh, 2012. "Volatility spillovers from the US to Australia and China across the GFC," KIER Working Papers 838, Kyoto University, Institute of Economic Research.
    • Handle: RePEc:kyo:wpaper:838
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    References listed on IDEAS

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    1. Ataurima Arellano, Miguel & Rodríguez, Gabriel, 2020. "Empirical modeling of high-income and emerging stock and Forex market return volatility using Markov-switching GARCH models," The North American Journal of Economics and Finance, Elsevier, vol. 52(C).

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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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