Analysis · Finance

When a Higher Asset Value Does Not Mean a Better Return

By · AI-compiled · Published · Analysis prepared · 1 source · doi.org

An asset starting at 84.57 ends at 252.7952; another starting at 30.50 reaches 91.1701. The first finishes much higher, but both roughly triple. These entries in a 2023 modeling paper reveal why comparing final asset values can mislead when starting values differ.

In An empirical assessment of asset value function for capital market price changes, Okpoye OT, Amadi IU and Azor PA explored four mathematical descriptions of asset prices. Their work presents analytical solutions and numerical illustrations, rather than an experiment testing investment strategies in a market.

The authors combined two return parameters through addition, multiplication and reciprocal forms. They used Ito’s formula, a tool for handling random variation, to derive exponential price expressions. Their tables then varied volatility and return parameters while fixing time and the random increment at one.

The two figures above come from the additive and additive inverse tables, with volatility set to 0.1 and each table’s displayed return parameter set to one. Under those settings, the formulas apply the same growth multiplier to different starting prices. The larger ending value therefore does not establish a superior percentage return, despite the paper’s broader claim that additive inverse effects deliver the highest returns.

Another reported result requires similar care: values rise as volatility increases across the tabulated range. That is a conditional model output with a fixed positive random increment. It neither establishes an observed market association nor demonstrates that increasing volatility causes higher realized returns.

Although the abstract claims confirmation using empirical stock prices, the paper provides no identifiable price dataset, observation dates or forecast error evaluation. Its useful lesson is about comparison: put modeled values on a common starting basis and examine the assumptions producing their differences before interpreting a ranking as evidence of performance.

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