MODELLING NIGERIAN STOCK RETURNS WITH ARMA-EGARCH: A VOLATILITY ANALYSIS
Abstract
This study analyzes the volatility of Nigerian stock returns from January 2, 2010, to December 31, 2022, using ARMA-EGARCH models with Generalized Error Distribution (GED). Four model specifications are assessed: ARMA-EGARCH (1,1), ARMA-EGARCH (1,2), ARMA-EGARCH (2,1), and ARMA-EGARCH (2,2). The focus is on model selection, parameter estimation, and diagnostic testing to determine the best model for capturing volatility dynamics. The ARMA-EGARCH (2,2) GED model emerges as the best based on AIC, BIC, and high log-likelihood values, offering a good balance of fit and complexity. The ARMA-EGARCH (1,1) GED model is noted for effectively balancing simplicity and fit while capturing volatility and asymmetric effects. However, all models show limitations in fully capturing volatility dynamics and maintaining parameter stability, particularly concerning volatility clustering. The ARMA-EGARCH (2,2) model consistently performs best across various statistical criteria, including AIC and BIC. Although it provides a robust fit, it has some limitations in serial correlation and model stability. This indicates the need for further model refinement and exploration to enhance forecasting accuracy and address intrinsic limitations. These findings are valuable for investors and policymakers in understanding stock market volatility modelling both in Nigeria and globally.
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