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Empirical Analyses of Industry Stock Index Return Distributions for the Taiwan Stock Exchange

Author

Listed:
  • Svetlozar T. Rachev

    (School of Economics and Business Engineering, University of Karlsruhe)

  • Chufang Wu

    (Department of Applied Mathematics, National Donghua University of Taiwan)

  • Frank J. Fabozzi

    (Finance and Becton Fellow, School of Management, Yale University)

Abstract

We study the daily return distributions for 22 industry stock indexes on the Tai-wan Stock Exchange under the unconditional homoskedastic independent, identically distributed and the conditional heteroskedastic GARCH models. Two distribution hypotheses are tested: the Gaussian and the stable Paretian distributions. The performance of the stable Paretian distribution is better than that of the Gaussian distribution. A back-testing example is provided to give evidence on the superiority of the stable ARMA-GARCH to the normal ARMA-GARCH.

Suggested Citation

  • Svetlozar T. Rachev & Chufang Wu & Frank J. Fabozzi, 2007. "Empirical Analyses of Industry Stock Index Return Distributions for the Taiwan Stock Exchange," Annals of Economics and Finance, Society for AEF, vol. 8(1), pages 21-31, May.
    • Handle: RePEc:cuf:journl:y:2007:v:8:i:1:p:21-31
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    References listed on IDEAS

    as
    1. Rachev, S.T (ed.), 2003. "Handbook of Heavy Tailed Distributions in Finance," Elsevier Monographs, Elsevier, edition 1, number 9780444508966.
    2. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    3. Yu Chuan Huang & Bor-Jing Lin, 2004. "Value-at-Risk Analysis for Taiwan Stock Index Futures: Fat Tails and Conditional Asymmetries in Return Innovations," Review of Quantitative Finance and Accounting, Springer, vol. 22(2), pages 79-95, March.
    4. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-547, August.
    5. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters, in: Anastasios G Malliaris & William T Ziemba (ed.), THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78, World Scientific Publishing Co. Pte. Ltd..
    6. Chiang, Thomas C. & Doong, Shuh-Chyi, 1999. "Empirical analysis of real and financial volatilities on stock excess returns: evidence from Taiwan industrial data," Global Finance Journal, Elsevier, vol. 10(2), pages 187-200.
    7. 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.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Yuri Heymann, 2016. "A test of financial time-series data to discriminate among lognormal, Gaussian and square-root random walks," Computational Statistics, Springer, vol. 31(4), pages 1373-1383, December.
    2. Wei Sun & Svetlozar Rachev & Frank J. Fabozzi, 2009. "A New Approach for Using Lévy Processes for Determining High‐Frequency Value‐at‐Risk Predictions," European Financial Management, European Financial Management Association, vol. 15(2), pages 340-361, March.

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    More about this item

    Keywords

    Stable distributions; ARMA-GARCH; Heavy tails; Volatility clustering; Value at risk;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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