Estimation of Asset Value Changes Using Stochastic Models for Capital Market Investments in Oando Plc, Nigeria

Abstract

This paper simultaneously applied Stochastic Delay Differential Equations alongside Stochastic Differential Equations through both multiplicative return structures within an emerging capital market context such as Nigeria. However, no prior study including Amadi & Okpoye (2022) and Okpoye et al. (2023) had simultaneously incorporated time-dependent delay parameters into multiplicative and structures, nor applied such a framework within an emerging capital market context like Nigeria. It was observed that investors often engage in delayed asset liquidation, expecting appreciation over time; however, the quantitative implications of such delay under stochastic market uncertainty remained insufficiently understood. Simulations were performed for varying levels of delay parameters and return rates (1.0000 and 2.0000), under constant volatility, to determine whether delayed strategies generate statistically superior financial outcomes in comparison to immediate asset liquidation. Results indicated that the presence of delay significantly enhances asset values under both return structures, with delayed investments yielding consistently higher returns than non-delayed ones. The analysis further revealed that an increase in return rates amplifies these gains, confirming that delay and rate of return interaction contribute positively to wealth accumulation. Goodness-of-fit tests using the Kolmogorov–Smirnov (KS) procedure showed that asset values with delay and without delay do not originate from the same distribution at a 1% significance level. This statistical divergence suggests that delay is not only financially advantageous but also structurally alters the stochastic behaviour of asset values, implying higher risk–return sensitivity. Moreover, graphical results corroborated these findings by displaying upward trajectories for delayed assets, contrasted with low or stagnant returns for non-delayed strategies. Overall, the study contributed to financial modelling literature by demonstrating how delay-driven investment strategies can serve as profit-maximizing approaches in uncertain market environments.

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