Submitted dissertation is focused on methods of robust normality testing and applications of robust tests in verifying hypothesis of the weak form of efficiency in stock markets. In the dissertation, theory of efficient markets and approaches to verifying the weak form of market efficiency and normality assumption are being discussed. Novel robust testing procedures of testing normality are proposed in this work to overcome shortcomings of classical normality tests in the field of financial data, which are typical with occurrence of remote data points and additional types of deviations from normality. Results of power simulation study of classical and robust tests of normality against several types of alternative distributions, i.e. symmetric heavy-tailed, symmetric light-tailed, asymmetric heavy-tailed, asymmetric light-tailed, selected mixtures of normal distributions and outlier models, are presented. Based on outcome of the power simulation study, selected normality tests were consequently used to verify the weak form of efficiency in stock markets in the Czech Republic, Hungary, Austria, Germany, Slovakia, United States and Japan during years 2000-2009. In addition to selected classical and robust normality tests, Ljung-Box portmanteau test was also used. In conclusion, there is a discussion and comparison of results carried out and future trends of these markets are outlined.
| Identifer | oai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:249241 |
| Date | January 2010 |
| Creators | Střelec, Luboš |
| Source Sets | Czech ETDs |
| Language | Czech |
| Detected Language | English |
| Type | info:eu-repo/semantics/doctoralThesis |
| Rights | info:eu-repo/semantics/restrictedAccess |
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