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CBN Journal of Applied Statistics (JAS)

Keywords

GARCH, heteroscedasticity, MICSS, structural break

Abstract

This study models volatility in the daily Nigeria Stock Exchange 30 index from January 30, 2012 to August 31, 2020, comparing the Modified Iterated Cumulative Sums of Squares (MICSS) and the traditional cumulative sum of squares (CUSUMSQ) approaches. Findings reveal that integrating structural breaks reduces volatility persistence, and the MICSS outperformed the CUSUM and CUSUMSQ algorithms. Also, incorporating structural breaks reduces the impact of good and bad news on volatility. The study emphasizes the importance of adopting a robust methodology, such as the MICSS, in detecting structural breaks when estimating conditional variances, as incorporating structural breaks in the estimation is pivotal for model robustness, avoiding biases, and improving the estimation of volatility dynamics in financial time series. For investors and risk managers, the practical implications of these findings are: incorporating these breaks enhances risk assessment, portfolio allocation, and hedging strategies. For policymakers, incorporating structural breaks can lead to a more informed regulatory framework that helps stabilize the financial markets.

Issue

15

Volume

2

First Page

71

Last Page

92

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