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Estimating and predicting multivariate volatility thresholds in global stock markets

  • Fabio Trojani

    (Swiss Institute of Banking and Finance, University of St. Gallen, Switzerland)

  • Francesco Audrino

    (University of Lugano, CH-6900 Lugano, Switzerland)

We propose a general double tree structured AR-GARCH model for the analysis of global equity index returns. The model extends previous approaches by incorporating (i) several multivariate thresholds in conditional means and volatilities of index returns and (ii) a richer specification for the impact of lagged foreign (US) index returns in each threshold. We evaluate the out-of-sample forecasting power of our model for eight major equity indices in comparison to some existing volatility models in the literature. We find strong evidence for more than one multivariate threshold (more than two regimes) in conditional means and variances of global equity index returns. Such multivariate thresholds are affected by foreign (US) lagged index returns and yield a higher out-of-sample predictive power for our tree structured model setting. Copyright © 2006 John Wiley & Sons, Ltd.

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Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

Volume (Year): 21 (2006)
Issue (Month): 3 ()
Pages: 345-369

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Handle: RePEc:jae:japmet:v:21:y:2006:i:3:p:345-369
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  11. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
  12. Masih, Rumi & Masih, Abul M. M., 2001. "Long and short term dynamic causal transmission amongst international stock markets," Journal of International Money and Finance, Elsevier, vol. 20(4), pages 563-587, August.
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