Analysis of Investment Returns as Markov Chain Random Walk
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Date
2024
Journal Title
Journal ISSN
Volume Title
Publisher
International Journal of Mathematics and Mathematical Sciences
Abstract
The 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.
Description
Research Article
Keywords
Investment Returns, Markov Chain Random Walk, stock market