Macroeconomic Determinants of Stock Market Volatility: A Comparative GARCH Analysis across Financial Markets with Varying Depth and Liquidity

Pavle Jakšić; Mirela Mitrašević; Darko Marjanović; Branislav Dudić; Miloš Pjanić; Predrag Vidicki

doi:10.31181/ijes1612027288

Authors

Pavle Jakšić Department of Finance, The City Administration of Loznica, Loznica, Serbia Author https://orcid.org/0000-0002-0157-4319
Mirela Mitrašević University of East Sarajevo, Faculty of Business Economics, Bijeljina, Bosnia and Herzegovina Author https://orcid.org/0000-0001-5393-4139
Darko Marjanović Institute of Economic Sciences, Belgrade, Serbia Author https://orcid.org/0000-0001-7336-1964
Branislav Dudić 1) Comenius University Bratislava, Faculty of Management, Bratislava, Slovakia; 2) University Business Academy, Faculty of Economics and Engineering Management, Novi Sad, Serbia Author https://orcid.org/0000-0002-4647-6026
Miloš Pjanić Department for Financial and Banking Management, Faculty of Economics, University of Novi Sad, Subotica, Serbia Author https://orcid.org/0000-0001-8521-8559
Predrag Vidicki University of Novi Sad, Faculty of Technical Sciences, Serbia Author https://orcid.org/0000-0001-7365-9429

DOI:

https://doi.org/10.31181/ijes1612027288

Keywords:

Stock market volatility, GARCH models, Financial market development, Macroeconomic factors, Crisis effects

Abstract

This research investigates how selected macroeconomic determinants influence stock market returns and volatility across financial systems characterized by varying degrees of market depth and liquidity. The analysis focuses on four stock indices—FTSE 100, FTSE China A50, BUDAPEST SE, and SBITOP—over the period 2012–2022, which is further divided into pre-crisis and crisis/post-crisis subperiods to capture the effects of the COVID-19 shock. To account for time-varying and asymmetric volatility dynamics, the study employs customized multivariate GARCH-type models, including EGARCH, PGARCH, and TGARCH specifications, with model selection guided by information criteria. The empirical results confirm that macroeconomic factors such as inflation, interest rates, exchange rates, and commodity prices exert statistically significant effects on stock index returns and volatility, although the magnitude and direction of these effects differ across markets and across time periods. Developed and less liquid markets display distinct volatility transmission mechanisms, particularly during crisis periods. Overall, the findings highlight the relevance of flexible GARCH-based frameworks for understanding market-specific volatility dynamics and provide useful insights for investors and policymakers operating under conditions of heightened uncertainty.

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