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An Empirical Study of Asian Stock Volatility Using Stochastic Volatility Factor Model: Factor Analysis and Forecasting

  • Silvia S.W. Lui


    (Queen Mary, University of London)

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    This paper is an empirical study of Asian stock volatility using stochastic volatility factor (SVF) model of Cipollini and Kapetanios (2005). We adopt their approach to carry out factor analysis and to forecast volatility. Our results show some Asian factors exhibit long memory that is in line with existing empirical findings in financial volatility. However, their local-factor SVF model is not powerful enough in forecasting Asian volatility. This has led us to propose an extension to a multi-factor SVF model. We also discuss how to produce forecast using this multi-factor model.

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    Paper provided by Queen Mary University of London, School of Economics and Finance in its series Working Papers with number 581.

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    Date of creation: Dec 2006
    Date of revision:
    Handle: RePEc:qmw:qmwecw:wp581
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    1. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    2. Cipollini, A. & Kapetanios, G., 2008. "A stochastic variance factor model for large datasets and an application to S&P data," Economics Letters, Elsevier, vol. 100(1), pages 130-134, July.
    3. Khalid, Ahmed M. & Kawai, Masahiro, 2003. "Was financial market contagion the source of economic crisis in Asia?: Evidence using a multivariate VAR model," Journal of Asian Economics, Elsevier, vol. 14(1), pages 131-156, February.
    4. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
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