Advances and Applications in Statistics
Volume 54, Issue 1, Pages 1 - 20
(January 2019) http://dx.doi.org/10.17654/AS054010001 |
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ANALYSIS OF SHARE PRICES AS MARKOV CHAINS WITH COUNTABLY INFINITE STATES
Felix O. Mettle, Enoch N. B. Quaye, Ravenhill A. Laryea and Louis Asiedu
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Abstract: By considering negative share price changes, the researchers judiciously modeled share prices as geometrically ergodic Markov chains with countably infinite states based on ideas about stochastic processes elsewhere. The model so obtained will serve as a strong statistical foundation to improve stock trading decisions. It is inferred that a similar model can successfully be developed using positive share price changes. The proposed model is applied to share prices of some selected equities; namely, Apple, Google, IBM, 3M Company and Bank of America, with data spanning from 3rd January, 2005 to 19th June, 2017. |
Keywords and phrases: Markov chain, transition probability matrix, long-run probability, geometrically ergodic.
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