Empirical modelling of high-frequency foreign exchange rates

 

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dc.contributor.advisor Guo, Renkuan en_ZA
dc.contributor.author Packirisamy, Someshini en_ZA
dc.date.accessioned 2014-08-02T14:48:03Z
dc.date.available 2014-08-02T14:48:03Z
dc.date.issued 2004 en_ZA
dc.identifier.citation Packirisamy, S. 2004. Empirical modelling of high-frequency foreign exchange rates. University of Cape Town. en_ZA
dc.identifier.uri http://hdl.handle.net/11427/5963
dc.description Includes bibliographical references (leaves 213-219).
dc.description.abstract There is a wealth of information available on modelling foreign exchange time series data, however, research studies on modelling and predicting high frequency foreign exchange data is less prominent. Furthermore, there does not appear to be much evidence supporting work on the modelling and prediction of high frequency South African Rand/United States Dollar (ZAR/USD) exchange rates. A fair amount of noise is embedded in high frequency time series data, especially the ZAR/USD exchange rates, and the modelling of these time series requires the use of specialized models. In addition, lengthy high frequency foreign exchange data is largely unavailable for the South African market. This dissertation undertakes empirical explorations to model high frequency foreign exchange time series (primarily the ZAR/USD time series), through the use of multi-agent neural networks, linear Kalman filters and fuzzy Markov chain theory. en_ZA
dc.language.iso eng en_ZA
dc.subject.other Mathematics of Finance en_ZA
dc.title Empirical modelling of high-frequency foreign exchange rates en_ZA
dc.type Master Thesis
uct.type.publication Research en_ZA
uct.type.resource Thesis en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Science en_ZA
dc.publisher.department Department of Mathematics and Applied Mathematics en_ZA
dc.type.qualificationlevel Masters
dc.type.qualificationname MSc en_ZA
uct.type.filetype Text
uct.type.filetype Image
dc.identifier.apacitation Packirisamy, S. (2004). <i>Empirical modelling of high-frequency foreign exchange rates</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Mathematics and Applied Mathematics. Retrieved from http://hdl.handle.net/11427/5963 en_ZA
dc.identifier.chicagocitation Packirisamy, Someshini. <i>"Empirical modelling of high-frequency foreign exchange rates."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Mathematics and Applied Mathematics, 2004. http://hdl.handle.net/11427/5963 en_ZA
dc.identifier.vancouvercitation Packirisamy S. Empirical modelling of high-frequency foreign exchange rates. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Mathematics and Applied Mathematics, 2004 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/5963 en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Packirisamy, Someshini AB - There is a wealth of information available on modelling foreign exchange time series data, however, research studies on modelling and predicting high frequency foreign exchange data is less prominent. Furthermore, there does not appear to be much evidence supporting work on the modelling and prediction of high frequency South African Rand/United States Dollar (ZAR/USD) exchange rates. A fair amount of noise is embedded in high frequency time series data, especially the ZAR/USD exchange rates, and the modelling of these time series requires the use of specialized models. In addition, lengthy high frequency foreign exchange data is largely unavailable for the South African market. This dissertation undertakes empirical explorations to model high frequency foreign exchange time series (primarily the ZAR/USD time series), through the use of multi-agent neural networks, linear Kalman filters and fuzzy Markov chain theory. DA - 2004 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2004 T1 - Empirical modelling of high-frequency foreign exchange rates TI - Empirical modelling of high-frequency foreign exchange rates UR - http://hdl.handle.net/11427/5963 ER - en_ZA


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