Analysis of Investment Returns as Markov Chain Random Walk
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 Janua...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-01-01
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| Series: | International Journal of Mathematics and Mathematical Sciences |
| Online Access: | http://dx.doi.org/10.1155/2024/3966566 |
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| author | Felix Okoe Mettle Emmanuel Kojo Aidoo Carlos Oko Narku Dowuona Louis Agyekum |
| author_facet | Felix Okoe Mettle Emmanuel Kojo Aidoo Carlos Oko Narku Dowuona Louis Agyekum |
| author_sort | Felix Okoe Mettle |
| collection | DOAJ |
| description | 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. The 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. The Mexican market was observed to have the least 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. |
| format | Article |
| id | doaj-art-b0bcdd6c4c0147a9ab621ffc9527f224 |
| institution | Kabale University |
| issn | 1687-0425 |
| language | English |
| publishDate | 2024-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Mathematics and Mathematical Sciences |
| spelling | doaj-art-b0bcdd6c4c0147a9ab621ffc9527f2242025-02-03T01:29:31ZengWileyInternational Journal of Mathematics and Mathematical Sciences1687-04252024-01-01202410.1155/2024/3966566Analysis of Investment Returns as Markov Chain Random WalkFelix Okoe Mettle0Emmanuel Kojo Aidoo1Carlos Oko Narku Dowuona2Louis Agyekum3Department of Statistics and Actuarial ScienceDepartment of Computer Science & Information SystemsPublic Works DepartmentDepartment of Statistics and Actuarial ScienceThe 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. The 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. The Mexican market was observed to have the least 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.http://dx.doi.org/10.1155/2024/3966566 |
| spellingShingle | Felix Okoe Mettle Emmanuel Kojo Aidoo Carlos Oko Narku Dowuona Louis Agyekum Analysis of Investment Returns as Markov Chain Random Walk International Journal of Mathematics and Mathematical Sciences |
| title | Analysis of Investment Returns as Markov Chain Random Walk |
| title_full | Analysis of Investment Returns as Markov Chain Random Walk |
| title_fullStr | Analysis of Investment Returns as Markov Chain Random Walk |
| title_full_unstemmed | Analysis of Investment Returns as Markov Chain Random Walk |
| title_short | Analysis of Investment Returns as Markov Chain Random Walk |
| title_sort | analysis of investment returns as markov chain random walk |
| url | http://dx.doi.org/10.1155/2024/3966566 |
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