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Estimation of the Shape Parameter of Ged Distribution for a Small Sample Size

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Purczyński J., Bednarz-Okrzyńska K.

Folia Oeconomica Stetinensia

2014

vol. 14

issue 1

35-46

In this paper a new method of estimating the shape parameter of generalized error distribution (GED), called ‘approximated moment method’, was proposed. The following estimators were considered: the one obtained through the maximum likelihood method (MLM), approximated fast estimator (AFE), and approximated moment method (AMM). The quality of estimator was evaluated on the basis of the value of the relative mean square error. Computer simulations were conducted using random number generators for the following shape parameters: s = 0.5, s = 1.0 (Laplace distribution) s = 2.0 (Gaussian distribution) and s = 3.0.

Application of Generalized Student’s T-Distribution In Modeling The Distribution of Empirical Return Rates on Selected Stock Exchange Indexes

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Purczyńskiz J., Bednarz-Okrzyńska K.

Folia Oeconomica Stetinensia

2014

vol. 13

issue 2

37-48

This paper examines the application of the so called generalized Student’s t-distribution in modeling the distribution of empirical return rates on selected Warsaw stock exchange indexes. It deals with distribution parameters by means of the method of logarithmic moments, the maximum likelihood method and the method of moments. Generalized Student’s t-distribution ensures better fitting to empirical data than the classical Student’s t-distribution.

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2 Folia Oeconomica Stetinensia

2 Bednarz-Okrzyńska K.

1 Purczyński J.

1 Purczyńskiz J.

2 2014

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Estimation of the Shape Parameter of Ged Distribution for a Small Sample Size

Application of Generalized Student’s T-Distribution In Modeling The Distribution of Empirical Return Rates on Selected Stock Exchange Indexes