Portfolio selection for Polish stocks using the multivariate skew normal distribution

• Autorzy: Adcock C.
• Języki publikacji: EN

Abstrakty

EN

The paper applies the multivariate skew normal probability distribution to returns on Polish stocks. The estimated parameters are used as the input to a portfolio selection study in which the aim is to construct mean-varianceskewness efficient portfolios. As the paper shows, skewness is present in some of the stocks included in the study. On the basis of the data available, there is evidence that skewness does not persist in Polish stocks. That is, skewness is time varying. It is shown that it is possible to use the time varying estimates of skewness in portfolio selection. The results reported suggest that portfolios constructed by an investor who has a preference for skewness but no preference for expected return will outperform an index portfolio even after the deduction of transactions costs.

Słowa kluczowe

EN

portfolio selection; stock

PL

portfel; kapitał

• Wydawca: University of Zielona Góra, Faculty of Economics and Management
• Czasopismo: Management
• Rocznik: 2004
• Tom: Vol. 8, no 1
• Strony: 145--154
• Opis fizyczny: Bibliogr. 32 poz., rys., tab.

Twórcy

autor

Adcock C.

• The University of Sheffield, School of Management, United Kingdom

Bibliografia

• 1. Adcock C.J. (2004), An Extension Of Stein ’s Lemma For The Skew Normal Distribution, Working Paper.
• 2. Adcock C.J. and Shutes K. (2001), Portfolio Selection Based on the Multivariate-Skew Normal Distribution, (in:) A Skulimowski (ed.) Financial Modelling, Progress and Business Publishers, Kraków.
• 3. Adcock C.J. and Shutes K. (2003), An Analysis Of Polish Stock Retums Using The Generalised Skew Student Distribution, „Management".
• 4. Arditti F.D., Levy H. (1975), Portfolio Efficiency in Three Moments, „Journal of Finance”, 30, p. 797-809.
• 5. Azzalini A. (1985), A Class of Distributions Which lncludes The Normal Ones, (in:) J. Scand, „Statist”, 12, p. 171-178.
• 6. Azzalini A. (1986), Further Results on a Class of Distributions Which lncludes The Normal Ones, „Statistica”, 46, p. 199-208.
• 7. Azzalini A., Capitanio A. (2003), Distributions Generated by Perturbation of Symmetry with Emphasis on a Multivariate Skew t-Distribution, „Journal of the Royal Statistical Society”, Series B, 65, p. 367-390.
• 8. Azzalini A., Dalia Valle A. (1996), The Multivariate Skew-normal Distribution, „Biometrika”, 83, p. 715-726.
• 9. Barone Adesi G. (1988), Arbitrage Eąuilibrium with Skewed Asset Returns, „Journal of Financial and Quantitative Analysis”, 20, p. 299-313.
• 10. Bekaert G.C.R., Harvey C.B.Erb, Viskantam T.E. (1998), Distributional Characteristics of Emerging Market Returns and Asset Allocation, „Journal of Portfolio Management”, 24, p. 102-116.
• 11. Best M.J. Grauer R.R. (1991), On The Sensitivity of Mean-Yariance- Efficient Portfolios to Changes in Asset Means: Some Analytical and Computational Results, „Review of Financial Studies”, 4, p. 315-342.
• 12. Chopra V., Ziemba W.T. (1993), The Effect of Errors in Means, Yariances and Covariances on Optimal portfolio Choice, „Journal of Portfolio Management”, Winter, p. 6-11.
• 13. Chunhachinda P.K., Dandapani S.H., Prakash A.J. (1997), Portfolio Selection and Skewness: Evidence From International Stock Markets, „Journal of Banking and Finance”, 21, p. 143-167.
• 14. Harris R.D.F., Kukukozmen C.C. (2001), The Empirical Distribution ofUK and US Stock Returns, „Journal of Business Finance and Accounting”, 28, p. 715-740.
• 15. Harris R.D.F., Kukukozmen C.C., Yilmaz F. (2004), Skewness in the Conditional Distribution of Equity Returns, „Applied Financial Economics”, 14, p. 195-202.
• 16. Harvey C.R., Siddique A. (2000), Conditional Skewness in Asset Pricing Tests, „Journal of Finance”, 55, p. 1263-1295.
• 17. Harvey C.R., Leichty J.C., Leichty M.W., Muller P. (2002), Portfolio Selection With Higher Moments, Working Paper.
• 18. Kraus A., Litzenberger R.H. (1976), Skewness Preference and The Valuation of Risk Assets, „Journal of Finance”, 31, p. 1085-1100.
• 19. McDonald J.B., Newey W.K. (1988), Partially Adaptive Estimation of Regression Models Via The Generalized T Distribution, „Economic Theory”, 4, p. 428-457.
• 20. 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.
• 21. McDonald J.B., Xu Y.J. (1995), A Generalization of the Beta Distribution with Applications, „Journal of Econometrics”, 66, p. 133-152.
• 22. Michaud R.O. (1998), Efficient Asset Management, Harvard Business School Press, Boston.
• 23. O’Hagan A., Leonard T. (1976), Bayes Estimation Subject to Uncertainty About Parameter Constraints, „Biometrika”, 63, p. 201-203.
• 24. Roberts C. (1966), A Correlation Model Useful in The Study of Twins, „Journal of the American Statistical Association”, 61, p. 1184-1190.
• 25. Rubinstein M. (1973), The Fundamental Theorem of Parameter Preference Security Valuation, „Journal of Financial and Quantitative Analysis”, 8, p. 61-69.
• 26. Samuelson P. (1970), The Fundamental Approximation Theorem of Portfolio Analysis I terms of Means Variances and Higher Moments, „Review of Economic Studies”, 37, p. 537-542.
• 27. Sahu S.K., Dey D.K., Branco M.D. (2003), A New Class of Multivariate Skew Distributions With Applications to Bayesian Regression Models, „The Canadian Journal of Statistics”, 31, p. 129-150.
• 28. Singleton J.C., Wingender J. (1986), Skewness Persistence in Common Stock Returns, „Journal of Financial and Quantitative Analysis”, 13, p. 335-341.
• 29. Simaan Y. (1993), Portfolio Selection and Asset Pricing - Three Parameter Framework, „Management Science”, 39(5), 568-587.
• 30. Stein C.M. (1981), Estimation of the Mean of a Multivariate Normal Distribution, „Annals of Statistics”, 9.
• 31. Sun Q., Yan Y. (2003), Skewness Persistence with Optimal Portfolio Selection, „Journal of Banking and Finance”, 27, p. 111-1121.
• 32. Theodossiou P. (1998), Financial Data and the Skewed Generalized Ditritin, „Management Science”, 44, p. 1650-1661.