Application of Markov Chain Techniques for Selecting Efficient Financial Stocks for Investment Portfolio Construction

G. Kallah-Dagadu, Victor Apatu, F. Mettle, D. Arku, Godwin Debrah
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引用次数: 3

Abstract

In this paper, we apply Markov chain techniques to select the best financial stocks listed on the Ghana Stock Exchange based on the mean recurrent times and steady-state distribution for investment and portfolio construction. Weekly stock prices from Ghana Stock Exchange spanning January 2017 to December 2020 was used for the study. A three-state Markov chain was used to estimate the transition matrix, long-run probabilities, and mean recurrent times for stock price movements from one state to another. Generally, the results revealed that the long-run distribution of the stock prices showed that the constant state recorded the highest probabilities as compared to the point loss and point gain states. However, the results showed that the mean recurrent time to the point gain state ranges from three weeks to thirty-five weeks approximately. Finally, Standard Chartered Bank, GCB, Ecobank, and Cal Bank emerged as the top best performing stocks with respect to the mean recurrent times and steady-state distribution, and therefore, these equities should be considered when constructing asset portfolios for higher returns.
马尔可夫链技术在构建投资组合中选择有效金融股的应用
本文运用马尔可夫链技术,基于平均循环时间和稳态分布选择加纳证券交易所上市的最佳金融股,进行投资组合构建。该研究使用了2017年1月至2020年12月期间加纳证券交易所的每周股票价格。一个三状态马尔可夫链被用来估计从一个状态到另一个状态的股票价格运动的转移矩阵、长期概率和平均循环时间。总的来说,结果表明,股票价格的长期分布表明,与点数损失和点数获得状态相比,恒定状态记录了最高的概率。然而,结果表明,平均循环时间到点增益状态约为3周至35周。最后,渣打银行、GCB、Ecobank和Cal Bank在平均循环时间和稳态分布方面表现最佳,因此,在构建更高回报的资产组合时应考虑这些股票。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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