Evaluating Nigeria Exchange Group All Share Index: Insights from Linear and GARCH Modeling Techniques Authors

Abstract

This study investigates the volatility of the Nigeria Exchange Group All Share Index (ASI) using linear regression and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) modeling techniques. Despite prevalent public concerns regarding stock market instability, our analysis reveals that these perceptions are often exaggerated, driven largely by historical price levels and media representation. We employed a linear regression model to analyze monthly historical ASI data from 1985 to 2023, establishing a significant positive relationship between time and ASI values, with an R2 value of 0.7493, indicating that approximately 75% of the variance in ASI can be explained by the model. The Breusch-Godfrey test highlighted significant serial correlation in the residuals, necessitating further analysis using GARCH models to account for time-varying volatility. Our findings suggest that traditional asset pricing models may overlook alter- native risk measures that investors prioritize, emphasizing the need for a more nuanced understanding of market behavior. The adequacy of the model is achieved with a p-value 0.000017. Overall, this study contributes to the existing literature by offering insights into the dynamics of the Nigerian stock market and its volatility patterns, which are crucial for investors and policymakers alike.