Sep 2026· INTERNATIONAL JOURNAL OF APPLIED SCIENCE AND MATHEMATICAL THEORY· 0 citations
Abstract
Accurate estimation of asset value changes in capital markets is fundamental to informed
investment decision-making, particularly in highly volatile sectors. While stochastic models such
as Geometric Brownian Motion (GBM), Jump Diffusion, and stochastic volatility models have
been widely applied to capture price dynamics, these approaches do not incorporate time
dependent delay mechanisms that reflect realistic investor behaviour such as delayed asset
liquidation in anticipation of price appreciation. The systems of stochastic equations were solved
adopting Ito’s theorem where explicit solutions for assessing asset values were obtained.
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. Most existing studies
model price dynamics using geometric Brownian motion or stochastic volatility models without
incorporating delay-dependent mechanisms. 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. To this end, the study provided actionable insights for investors,
portfolio managers, and policymakers seeking optimal timing strategies to enhance wealth
creation in capital markets.
This paper simultaneously applied Stochastic Delay Differential Equations (SDDEs) alongside
Stochastic Differential Equations (SDEs) 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...
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