<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>In this paper a classic rate of return was examined. Due to a limited quantitative range, the study included only the modeling of the rate of return distribution of the WIG20 index and its companies by means of the Laplace distribution and the Gaussian distribution. Additionally, the goodness of fit tests and methods of estimating the aforementioned distributions parameters were thoroughly covered. When applying the Laplace distribution to modeling the rate of return distribution the parameters were determined by means of two methods: the method of moments and the maximum likelihood method. The maximum period was determined, for which usefulness of the distribution in modeling the rates of return distribution was observed, as well as the results of the chi-square test for class intervals with varying length ensuring equal probability, and for intervals with identical length considering two methods of determining the theoretical size: in accordance with the cumulative distribution function as well as on the basis of the probability density function.</p></abstract>

In this paper a classic rate of return was examined. Due to a limited quantitative range, the study included only the modeling of the rate of return distribution of the WIG20 index and its companies by means of the Laplace distribution and the Gaussian distribution. Additionally, the goodness of fit tests and methods of estimating the aforementioned distributions parameters were thoroughly covered. When applying the Laplace distribution to modeling the rate of return distribution the parameters were determined by means of two methods: the method of moments and the maximum likelihood method. The maximum period was determined, for which usefulness of the distribution in modeling the rates of return distribution was observed, as well as the results of the chi-square test for class intervals with varying length ensuring equal probability, and for intervals with identical length considering two methods of determining the theoretical size: in accordance with the cumulative distribution function as well as on the basis of the probability density function.

Goodness of Fit Tests in Modeling the Distribution of the Daily Rate of Return of the WIG20 Companies

Department of Quantitative Methods, Faculty of Management and Economics of Services, University of Szczecin, Cukrowa 8, 71-004 Szczecin

Folia Oeconomica Stetinensia

In this paper a classic rate of return was examined. Due to a limited quantitative range, the study included only the modeling of the rate of return...

Goodness of Fit Tests in Modeling the Distribution of the Daily Rate of Return of the WIG20 Companies

Pubblicato online: 28 giu 2012

Pagine: 103 - 113

DOI: https://doi.org/10.2478/v10031-011-0036-8

Parole chiave
goodness of fit tests, Kolmogorov test, chi-square test, class intervals

This content is open access.

Goodness of Fit Tests in Modeling the Distribution of the Daily Rate of Return of the WIG20 Companies

Pubblicato online: 28 giu 2012

Pagine: 103 - 113

DOI: https://doi.org/10.2478/v10031-011-0036-8

Parole chiavegoodness of fit tests, Kolmogorov test, chi-square test, class intervals

This content is open access.

Parole chiave
goodness of fit tests, Kolmogorov test, chi-square test, class intervals