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An analysis of skewness and kurtosis in Polish stock returns and the estimation of beta using the generalised skew student distribution

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Języki publikacji
EN
Abstrakty
EN
This paper uses the generalised skew Student (GST) distribution to model returns on Polish stocks that are constituents of the WIG20 index. A basic analysis of returns provides strong evidence of skewness and kurtosis, both of which can be accommodated by the generalised skew Student model. Three specific forms of the GST distribution are used. These are Student's t itself, the symmetric generalised Student distribution and a specific version of the generalised skew Student distribution. The models are first used to estimate the location parameter and other parameters of the return distribution separately for each stock. Secondly, stock betas are estimated for each security by assuming that the stock specific residuals in the market model follow one of the specified forms of GST distribution. The paper also reports the results of a short portfolio selection study in which the minimum variance portfolio is constructed using the different sets of parameter estimates.
Czasopismo
Rocznik
Strony
213--225
Opis fizyczny
Bibliogr. 13 poz., tab., wykr.
Twórcy
autor
  • The University of Sheffield, Department of Economics, UK
autor
  • The University of Sheffield, Department of Economics, UK
Bibliografia
  • 1. Adcock C.J., Shutes K. (2000), Fat Tails and the Capital Asset Pricing Model, in: C. Dunis (ed.), Advances in Quantitative Asset Management, Kluwer Academic Press, Boston, Mass.
  • 2. Adcock C.J., Meade N. (2002), An Extension of The Generalised Skew Student Distribution with Applications to Modelling Returns on Financial Assets, Invited paper at the 4th International Conference on Statistical Data Analysis based on the L Norm and Related Methods, Neuchâtel, Switzerland.
  • 3. Aparicio F., Estrada J. (2001), Empirical Distributions for Stock Returns: European Securities Markets 1990-95, “The European Journal of Finance”, 7, p. 1-21.
  • 4. Bekaert G., Harvey C.R., Erb C.B., Viskantam T.E. (1998), Distributional Characteristics of Emerging Market Returns & Asset Allocation, “Journal of Portfolio Management”, 24, p. 102-116.
  • 5. Berndt E.K., Hall H.B., Hall R.E., Hausman J.A. (1974), Estimation and Inference in Non-linear Structured Models, “Annals of Economic and Social Measurement”, 4, p. 653-666.
  • 6. Blattberg R., Gonedes N. (1974), A Comparison of the Stable and Student Distributions as Statistical Models for Stock Prices, “Journal of Business”, 47, p. 244-280.
  • 7. Campbell J.Y., Lo A.W., MacKinlay A.C. (1997), The Econometrics of Financial Markets, Princeton University Press, Princeton, New Jersey.
  • 8. McDonald J.B., Newey W.K. (1988), Partially Adaptive Estimation of Regression Models Via The Generalized T Distribution, “Economic Theory”, 4, p. 428-457.
  • 9. McDonald J.B., Nelson R.D. (1989), Alternative Beta Estimation for the Market Model Using Partially Adaptive Techniques, “Communications in Statistical Theory and Methods”, 18, p. 4039-4058.
  • 10. McDonald J.B., Xu Y.J. (1995), A Generalization of the Beta Distribution with Applications, “Journal of Econometrics”, 66, p. 133-152.
  • 11. Praetz P. (1972), The Distribution of Share Price Changes, “Journal of Business”, 45, p. 49-55.
  • 12. Sharpe W.F. (1964), Capital Asset Prices: A Theory of market equilibrium Under Conditions of Risk, “Journal of Finance”, 19, p. 425-442.
  • 13. Theodossiou P. (1998), Financial Data and the Skewed Generalized T Distribution, “Management Science”, 44, p. 1650-1661.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPZ2-0024-0028
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