Application of Discrete-time semi-Markov Model to the Stochastic forecasting of Capital assests as stock.

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dc.contributor.authorNafiu, Lukman Abiodun
dc.contributor.authorPatrick, Weke
dc.contributor.authorAlieu Jallow, Mamadou
dc.contributor.authorCarolyne, Ogutu
dc.date.accessioned2022-02-17T07:06:34Z
dc.date.available2022-02-17T07:06:34Z
dc.date.issued2021
dc.description.abstractIn this paper, we developed and applied a stochastic model based on Discrete-time Semi Markov chain approach and its generalizations to study the high frequency price dynamics of traded stocks. Semi Markov is a stochastic process that generalizes both the Markov chain and the Markov renewal processes. it is well known that the performances of the stock market or factors that move stock prices are technical factors, fundamental factors and market sentiments.en_US
dc.description.sponsorshipKabale Universityen_US
dc.identifier.issn0972-0863
dc.identifier.urihttp://hdl.handle.net/20.500.12493/564
dc.publisherFar East Journal of theoretical Statisticsen_US
dc.subjectDiscrete-time Semi Markov Model, Stock prices, bull market, bear market, stagnant marketen_US
dc.titleApplication of Discrete-time semi-Markov Model to the Stochastic forecasting of Capital assests as stock.en_US
dc.typeArticleen_US

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