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Research Article Open access CC BY 4.0

A Stochastic Model for Stock Market Price Variation

D. S. A. Wokoma (Bishop), I. U. Amadi, I. S. Aboko

Asian Research Journal of Mathematics · pp. 41–49 · Published 16 Apr 2022

10.9734/arjom/2022/v18i430372

Abstract

This paper develops a differential equation model that could consider environmental effects for decision making and incorporated stochastic parameter in the model. These analyses were logically extended to vector stochastic differential equation that would help in predicting different commodity price processes, and the result obtained by using principal component analysis which is a function of the drift and by imposing a condition on the stochastic part. Furthermore, the results show the level of proportion accounted by first Principal Component Analysis (PCA) a function of the drift. In the circumstance,Kolmogorov-Smirnov (KS) test was carried out; and there exist a difference between distributions of volatility and drift.

Stock market price drift volatility stochastic differential equation principal component analysis

Cited by 1

Stochastic Model of Market Assessments of Stock Returns and Value of Asset Prices in Time-Varying Investment Returns

Bright Okore Osu, Innocent Uchenna Amadi · Trends in Applied Sciences Research · 2023

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