The Impact of Markov Chain and Properties of Fundamental Matrix Solution in the Analysis of Stock Market Price Variation in Finite Domain

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Published: 2022-11-29

Page: 774-794


Amadi, Innocent Uchenna *

Department of Mathematics and Statistics, Ignatius Ajuru University of Education, Rumuolumeni, Port Harcourt, Nigeria.

Kanu, Nkechinyere Faith

Department of Mathematics and Statistics, Captain Elechi Amadi Polytechnic, Rumuola, Port Harcourt, Nigeria.

Anyamele, Bethel Azunna

Department of Mathematics and Statistics, Ignatius Ajuru University of Education, Rumuolumeni, Port Harcourt, Nigeria.

*Author to whom correspondence should be addressed.


Abstract

The success of any investment depends on regular assessment of daily activities in order to move an investment forward. So, stochastic analysis of Markov chain is well-known prevailing mathematical tools used for the prediction of future stock price changes. This paper studied the stochastic analysis of Markov chain in finite state for Dangote cement Nigeria PLC, Oando cement Nigeria PLC and Bua cement Nigeria PLC using closing stock price data of (2017-2021) extracted from Nigeria Stock Exchange. The transition probability matrix solutions were obtained independently. The growth rates, expected mean rate of return were considered. Also Dangote has the best probability of no change in price in the near future which informs an investor on the proper decision in respect to stock market price movements for both short and long term investment plans respectively. In the same vain, criteria were imposed to select four elements each from the transition matrix solutions independently. These four elements were logically extended to form a matrix that would help in predicting different commodity price processes, and the result obtained by exploring the properties of the fundamental matrix solution to assess the future price changes of each   company investment. Finally, an increase in volatility with respect to time increases the future price changes through the trading days.  

Keywords: Markov chain, stock market prices, transition matrix, return rates and growth rates


How to Cite

Uchenna, A. I., Faith, K. N., & Azunna, A. B. (2022). The Impact of Markov Chain and Properties of Fundamental Matrix Solution in the Analysis of Stock Market Price Variation in Finite Domain. Asian Journal of Pure and Applied Mathematics, 4(1), 774–794. Retrieved from https://globalpresshub.com/index.php/AJPAM/article/view/1704

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References

Nkemnole EB, Okafor SN. Markov chain applied to Returns on Stock Prices. Benin Journal of Statistics. 2020;3:142-159.

ISSN 2682-5767.

Chun-Wei C, Jonathan ZZ. The effects of channel experiences and direct marketing on customer retention in multichannel setting. Journal of Interactive Marketing. 2016;36:77-90.

Lakshmi G, Jyothi M. Application of markov process for prediction of stock market performance. International Journal of Recent Technology and Engineering (IJRTE). 2020;8(6):2277-3878.

Haiying C, Haiyan C, Wei Zhang CY, Hongxiu C. Research on marketing prediction model based on markov prediction. Wireless Communications and Mobile Computing. 2021;12:1-9.

DOI: 10.1155/2021/4535181

Adesokan IA, Philip N, Abdulhakeen K. Analyzing expected returns of a stock using the markov chain model and the capital asset price model; 2017.

Amit P. Marketing channel attribution with Markov models; 2018.

Available:www.linkedin.com>pulse>attributionwithmarkovmodel. .

Iyai D, Amadi IU, Nsu RI. Stability analysis of stochastic model for stock market prices. International Journal of Mathematics and Computational Methods.

Available:http://www.iaras.org/iaras/journals/ijmcm

Agwuegbo SO, Adewole AP, Maduegbuna AN. A random walk model for stock market prices. Journal of Mathematics and Statistics. 2010;6(3):342-346.

ISSN 1549-3644

Amadi IU, Ogbogbo CP, Osu BO. Stochastic analysis of stock price changes as markov chain in finite states. Global Journal of Pure and Applied Sciences. 2022;28(28):91-98.

DOI: https://dx.doi.org/10.4314/gipas.v28i1.11

Amadi IU, Wobo GO. A mathematical model analysis for estimating stock market price changes. International Journal of Applied Science and Mathematical Theory. 2022;8(2). E-ISSN 2489-009x P-ISSN 2695 - 1908.

Amadi IU, Vivian MJ. A stochastic analysis of stock price variation assessment in Oando Nigeria, plc. International Journal of Mathematical Analysis and Modelling. 2022;5(1):216-228.

Ghimmett GR, Stirzaker DR. Probability and random processes. Oxford Science Publications, New York; 1982.

Dennie Zii. A first course in differential equation with modeling application. Brooks/cole, Boston, USA; 2013.

Amadi IU, Davies I, Osu BO. A series Solution to asset valuation and pricing of linear evolutions with stochastic partial derivatives. International journal of Mathematical Analysis and Modelling. 2022;5(3):44-64.