Analysis of Investment Returns as Markov Chain Random Walk

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dc.contributor.authorMettle, F.O.
dc.contributor.authorAgyekum, L.
dc.contributor.authorAidoo, E.K.
dc.contributor.authorDowuona, C.O.N.
dc.date.accessioned2024-04-10T12:10:58Z
dc.date.available2024-04-10T12:10:58Z
dc.date.issued2024
dc.descriptionResearch Articleen_US
dc.description.abstractThe main objective of this paper is to analyse investment returns using a stochastic model and inform investors about the best stock market to invest in. To this effect, a Markov chain random walk model was successfully developed and implemented on 450 monthly market returns data spanning from January 1976 to December 2020 for Canada, India, Mexico, South Africa, and Switzerland obtained from the Federal Reserves of the Bank of St. Louis. Limiting state probabilities and six-month moving crush probabilities were estimated for each country, and these were used to assess the performance of the markets. Te Mexican market was observed to have the lowest probabilities for all the negative states, while the Indian market recorded the largest limiting probabilities. In the case of positive states, the Mexican market recorded the highest limiting probabilities, while the Indian market recorded the lowest limiting probabilities. The results showed that the Mexican market performed better than the others over the study period, whilst India performed poorly. These findings provide crucial information for market regulators and investors in setting regulations and decision-making in investment.en_US
dc.identifier.otherhttps://doi.org/10.1155/2024/3966566
dc.identifier.urihttp://ugspace.ug.edu.gh:8080/handle/123456789/41559
dc.language.isoenen_US
dc.publisherInternational Journal of Mathematics and Mathematical Sciencesen_US
dc.subjectInvestment Returnsen_US
dc.subjectMarkov Chain Random Walken_US
dc.subjectstock marketen_US
dc.titleAnalysis of Investment Returns as Markov Chain Random Walken_US
dc.typeArticleen_US

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