Portfolio Optimization Technique: Mean – Variance and Bayesian Approaches in the Nigerian Stock Market

Abstract

The Nigerian Stock Market provides a complex and dynamic environment for investors. In this dynamic context, portfolios optimization is mandatory for an effective risk-return balance with the objective of accomplishing financial goals and objectives. This study delves into two prominent portfolio optimization methodologies: the Mean-Variance Approach and the Bayesian Approach. The mean-variance approach, sought to solve the optimization problem by analyzing the means and variances of a certain collection of stocks in order to achieve maximum return on investment. However, the simplicity of the mean-variance approach gives rise to various limitations. This study seeks to address some of these limitations by employing the Bayesian method, which is primarily grounded in probability theory and Bayes' theorem. The methodologies were used to construct optimal portfolios with daily data of the Nigerian stock market from 2018 to 2024 with particular focus on the NSE 30 equities of the Nigerian stock market. The work is based on building optimizations models, a statistical analysis of the historical market data and a review of recent data, effects and market expectations. The results of this study demonstrate the flexibility of Bayesian portfolios to construct portfolios that potentially produce higher returns by various weightings of past and recent data. However, the mean-variance approach is good in the matter of risk-return balance. The paper contributes to the current discourse on the effective portfolio optimization strategies by providing an in-depth knowledge of their implications in the Nigerian Stock Market.

DOI: https://doi.org/10.5281/zenodo.21842197