Bayesian estimation of stochastic volatility models with fat tails and correlated errors applied to the South African financial market

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dc.contributor.advisorBecker, Ronalden_ZA
dc.contributor.authorSavanhu, Richarden_ZA
dc.date.accessioned2015-01-03T05:28:58Z
dc.date.available2015-01-03T05:28:58Z
dc.date.issued2011en_ZA
dc.descriptionIncludes bibliographical references (leaves 39-40).en_ZA
dc.description.abstractIn this study we apply Markov Chain Monte Carlo methods in the Bayesian framework to estimate Stochastic Volatility models using South African financial market data. A single move Gibbs sampler is used to sample parameters from the posterior distribution. Volatility is used as measure of an asset's risk. It is particularly important in risk management, derivatives pricing, and portfolio selection. When pricing derivatives it is important to quote the correct volatility trading in the market, hence there is need for good estimates of volatility. To capture the stylised facts about asset returns we used the model extended for fat tails and correlated errors. To support this model against the basic model of Taylor (1986), we computed Bayes Factors of Jacquier, Polson and Ross (2004). The extended model was found to be far superior to the basic model.en_ZA
dc.identifier.apacitationSavanhu, R. (2011). <i>Bayesian estimation of stochastic volatility models with fat tails and correlated errors applied to the South African financial market</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Mathematics and Applied Mathematics. Retrieved from http://hdl.handle.net/11427/11085en_ZA
dc.identifier.chicagocitationSavanhu, Richard. <i>"Bayesian estimation of stochastic volatility models with fat tails and correlated errors applied to the South African financial market."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Mathematics and Applied Mathematics, 2011. http://hdl.handle.net/11427/11085en_ZA
dc.identifier.citationSavanhu, R. 2011. Bayesian estimation of stochastic volatility models with fat tails and correlated errors applied to the South African financial market. University of Cape Town.en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Savanhu, Richard AB - In this study we apply Markov Chain Monte Carlo methods in the Bayesian framework to estimate Stochastic Volatility models using South African financial market data. A single move Gibbs sampler is used to sample parameters from the posterior distribution. Volatility is used as measure of an asset's risk. It is particularly important in risk management, derivatives pricing, and portfolio selection. When pricing derivatives it is important to quote the correct volatility trading in the market, hence there is need for good estimates of volatility. To capture the stylised facts about asset returns we used the model extended for fat tails and correlated errors. To support this model against the basic model of Taylor (1986), we computed Bayes Factors of Jacquier, Polson and Ross (2004). The extended model was found to be far superior to the basic model. DA - 2011 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2011 T1 - Bayesian estimation of stochastic volatility models with fat tails and correlated errors applied to the South African financial market TI - Bayesian estimation of stochastic volatility models with fat tails and correlated errors applied to the South African financial market UR - http://hdl.handle.net/11427/11085 ER - en_ZA
dc.identifier.urihttp://hdl.handle.net/11427/11085
dc.identifier.vancouvercitationSavanhu R. Bayesian estimation of stochastic volatility models with fat tails and correlated errors applied to the South African financial market. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Mathematics and Applied Mathematics, 2011 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/11085en_ZA
dc.language.isoengen_ZA
dc.publisher.departmentDepartment of Mathematics and Applied Mathematicsen_ZA
dc.publisher.facultyFaculty of Scienceen_ZA
dc.publisher.institutionUniversity of Cape Town
dc.subject.otherMathematics of Financeen_ZA
dc.titleBayesian estimation of stochastic volatility models with fat tails and correlated errors applied to the South African financial marketen_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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