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Computer-Intensive Time-Varying Model Approach to the Systematic Risk of Australian Industrial Stock Returns

Author

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  • Juan Yao

    (Finance Discipline, School of Business, The University of Sydney, NSW 2006.)

  • Jiti Gao

    (Department of Statistics, School of Mathematics and Statistics, The University of Western Australia, Crawley, WA 6009.)

Abstract

This paper aims to investigate the form of systematic risk of Australian industrial stock returns. We suggest using four stochastic state-space models for the analysis. The stochastic properties of systematic risk are studied by examining four classes of state-space models: random walk model, random coefficient model, ARMA(1, 1) model and mean reverting model (or moving mean model). We have found that the industrial portfolio betas are unstable. The variation of industrial portfolio beta is either random or mean-reverting. Among the nineteen industrial groups, ten of them have the mean-reverting process betas but six of them seem to have a moving long-term mean. Five of the industrial groups have the random process betas, more specifically; the betas of three of them are the random walk processes while the betas of the other two are just the random coefficients. We have also identified that the betas of five industrial groups seem to follow an ARMR(1,1) process.

Suggested Citation

  • Juan Yao & Jiti Gao, 2004. "Computer-Intensive Time-Varying Model Approach to the Systematic Risk of Australian Industrial Stock Returns," Australian Journal of Management, Australian School of Business, vol. 29(1), pages 121-145, June.
    • Handle: RePEc:sae:ausman:v:29:y:2004:i:1:p:121-145
    DOI: 10.1177/031289620402900113
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    References listed on IDEAS

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    1. Ding, Zhuanxin & Granger, Clive W. J. & Engle, Robert F., 1993. "A long memory property of stock market returns and a new model," Journal of Empirical Finance, Elsevier, vol. 1(1), pages 83-106, June.
    2. Robert D. Brooks & Robert W. Faff & Michael D. McKenzie, 1998. "Time†Varying Beta Risk of Australian Industry Portfolios: A Comparison of Modelling Techniques," Australian Journal of Management, Australian School of Business, vol. 23(1), pages 1-22, June.
    3. Ray Ball & Philip Brown, 1980. "Risk and Return from Equity Investments in the Australian Mining Industry: January 1958 — February 1979," Australian Journal of Management, Australian School of Business, vol. 5(1-2), pages 45-66, April.
    4. R.W. Faff & R.D. Brooks, 1998. "Time‐varying Beta Risk for Australian Industry Portfolios: An Exploratory Analysis," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 25(5‐6), pages 721-745, June.
    5. Ohlson, James & Rosenberg, Barr, 1982. "Systematic Risk of the CRSP Equal-weighted Common Stock Index: A History Estimated by Stochastic-Parameter Regression," The Journal of Business, University of Chicago Press, vol. 55(1), pages 121-145, January.
    6. Thomas Josev & Robert Brooks & Robert Faff, 2001. "Testing a two factor APT model on Australian industry equity portfolios: the effect of intervaling," Applied Financial Economics, Taylor & Francis Journals, vol. 11(2), pages 157-163.
    7. Vasicek, Oldrich A, 1973. "A Note on Using Cross-Sectional Information in Bayesian Estimation of Security Betas," Journal of Finance, American Finance Association, vol. 28(5), pages 1233-1239, December.
    8. Brooks, Robert D. & Faff, Robert W. & McKenzie, Michael D. & Mitchell, Heather, 2000. "A multi-country study of power ARCH models and national stock market returns," Journal of International Money and Finance, Elsevier, vol. 19(3), pages 377-397, June.
    9. Bos, T & Newbold, P, 1984. "An Empirical Investigation of the Possibility of Stochastic Systematic Risk in the Market Model," The Journal of Business, University of Chicago Press, vol. 57(1), pages 35-41, January.
    10. Chang-Jin Kim & Charles R. Nelson, 1999. "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262112388, December.
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