Volatility forecasting using Double-Markov switching GARCH models under skewed Student-t distribution

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dc.contributor.advisorClark, Allanen_ZA
dc.contributor.authorMazviona, Batsirai Winmoreen_ZA
dc.date.accessioned2015-02-03T18:30:35Z
dc.date.available2015-02-03T18:30:35Z
dc.date.issued2012en_ZA
dc.descriptionIncludes bibliographical references.en_ZA
dc.description.abstractThis thesis focuses on forecasting the volatility of daily returns using a double Markov switching GARCH model with a skewed Student-t error distribution. The model was applied to individual shares obtained from the Johannesburg Stock Exchange (JSE). The Bayesian approach which uses Markov Chain Monte Carlo was used to estimate the unknown parameters in the model. The double Markov switching GARCH model was compared to a GARCH(1,1) model. Value at risk thresholds and violations ratios were computed leading to the ranking of the GARCH and double Markov switching GARCH models. The results showed that double Markov switching GARCH model performs similarly to the GARCH model based on the ranking technique employed in this thesis.en_ZA
dc.identifier.apacitationMazviona, B. W. (2012). <i>Volatility forecasting using Double-Markov switching GARCH models under skewed Student-t distribution</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Statistical Sciences. Retrieved from http://hdl.handle.net/11427/12344en_ZA
dc.identifier.chicagocitationMazviona, Batsirai Winmore. <i>"Volatility forecasting using Double-Markov switching GARCH models under skewed Student-t distribution."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Statistical Sciences, 2012. http://hdl.handle.net/11427/12344en_ZA
dc.identifier.citationMazviona, B. 2012. Volatility forecasting using Double-Markov switching GARCH models under skewed Student-t distribution. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Mazviona, Batsirai Winmore AB - This thesis focuses on forecasting the volatility of daily returns using a double Markov switching GARCH model with a skewed Student-t error distribution. The model was applied to individual shares obtained from the Johannesburg Stock Exchange (JSE). The Bayesian approach which uses Markov Chain Monte Carlo was used to estimate the unknown parameters in the model. The double Markov switching GARCH model was compared to a GARCH(1,1) model. Value at risk thresholds and violations ratios were computed leading to the ranking of the GARCH and double Markov switching GARCH models. The results showed that double Markov switching GARCH model performs similarly to the GARCH model based on the ranking technique employed in this thesis. DA - 2012 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2012 T1 - Volatility forecasting using Double-Markov switching GARCH models under skewed Student-t distribution TI - Volatility forecasting using Double-Markov switching GARCH models under skewed Student-t distribution UR - http://hdl.handle.net/11427/12344 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/12344
dc.identifier.vancouvercitationMazviona BW. Volatility forecasting using Double-Markov switching GARCH models under skewed Student-t distribution. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Statistical Sciences, 2012 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/12344en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Statistical Sciencesen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherMathematical Financeen_ZA
dc.titleVolatility forecasting using Double-Markov switching GARCH models under skewed Student-t distributionen_ZA
dc.typeMaster Thesis
dc.type.qualificationlevelMasters
dc.type.qualificationnameMPhilen_ZA
uct.type.filetypeText
uct.type.filetypeImage
uct.type.publicationResearchen_ZA
uct.type.resourceThesisen_ZA
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