Temporal Analysis of Mexico Stock Market Index Volatility using GJR-GARCH model
Temporal Analysis of Mexico Stock Market Index Volatility using GJR-GARCH model

Summary/Abstract: Stocks play a crucial role in the stock market, which is at the very core of every nation's economic growth. Investors, analysts, and others in related fields have turned their attention to stock price analysis. This study empirically investigates the conditional variance (volatility) or empirically estimates the price volatility spillover transmission in the daily returns of IPC Mexico index from Mexico stock market, for the long period January 1993 - July 2023 (which is more than 30 years daily data) using the GJR- GARCH model. There are 7661 daily observations included in the study. The recurrence of outcomes had leptokurtosis, were skewed to the left, and were not normally scattered; there was also confirmation of ARCH effects. The insights of the symmetric GARCH model showed confirmation of volatility clustering and endurance; the results of the GARCH-GJR model demonstrated the leverage impact and volatility clustering in the sample index. Favorable events alter the conditional variance (volatility), resulting in significant asymmetric GJR-GARCH values. This leads to the conclusion that favorable information has greater effects on index return volatility than adverse information. The results of this research constitute vital information for financiers, risk analysts, and regulators.

• Details
• Contents