Do the Selection of Volatility Models Depend on the Choice of Error Distributions: A Study on DS30 Index of the Dhaka Stock Exchange Limited, Bangladesh
Year: 2025
Type: article
Abstract: Research purpose: This study aims to explore whether the choice of the error distributions mattersin the case of selecting the best-fitted models for the 30 blue-chip stocks from the Dhaka StockExchange (DSE), Bangladesh.Design/methodology/approach: The study encompasses the DS30 index of the DSE, from 1 January2015 to 31 March 2025, and the data have been converted into logarithmic return form. To fulfill theobjectives, the researchers compared the Generalized Autoregressive Conditional Heteroscedastic(GARCH) along with the Exponential GARCH (EGARCH) under three alternative error distributions,namely normal, Student's t, and generalized error distributions. Then, the researchers employedARMA with GARCH and EGARCH techniques. For the model selections, two popular criteria — AICand BIC —have been considered.Findings: The models MA(1)-GARCH(1,2), MA(1)-EGARCH(1,1); MA(1)-GARCH(1,1), MA(1)-EGARCH(1,1); and MA(1)-GARCH(1,1), MA(1)-EGARCH(1,1) have been determined as the preferredmodels under Normal, Student's t, and Generalized error distributions, respectively. However, themodels selected under Student’s t error distributions have been proven to be superior. Hence, thechoice of error distributions is crucial when modeling the volatility of the DS30 index.Practical implications and originality: This is a novel research work that might guide the investors,who generally target the blue-chip stocks having good fundamentals, for their investments in DSE,Bangladesh.Research limitations: The comprehensive nature of this investigation necessarily imposed certainmethodological constraints, precluding the inclusion of several additional ARCH/GARCH variants andalternative distributional assumptions within the analytical framework.Keywords: Stationary, Heteroscedasticity, Autocorrelation, GARCH, EGARCH, AIC, BICJEL classification: C520, C530
Source: JKKNIU Business Review
Authors: Rahman, Md. Habibur, Mahmud, Aslam
Institution: Jatiya Kabi Kazi Nazrul Islam University
Language: English
Subfield: Finance
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W7093346446
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