Advanced GARCH Modeling Techniques and Risk-Return Relationship in the Vietnamese Stock Market
Abstract
This study investigates the Vietnamese stock market volatility focusing on the VN-INDEX from the Ho Chi Minh Stock Exchange, during the period 2004-2024. Both symmetric and asymmetric GARCH models are implemented with three different error term distribution assumptions to analyse the volatility persistence and clustering as well as any leverage effects on stock returns. The best fitting model for the dataset seems to be the EGARCH (2,1) using a Skew-t distribution assumption. The positive risk-return link is confirmed, with higher volatility associated with greater expected returns. This is one of the very few studies focused on a long period that moreover includes the effects that some unexpected exogenous shocks (like the Covid-19 pandemic and other recent geopolitical events) could generate on the parameters estimates. Thus, it can encompass different market phases, including years of economic growth, stability, volatility, and downturns, thus offering a comprehensive view of the Vietnamese market’s behaviour under dissimilar economic and financial conditions. This research offers valuable insights into the nature of uncertainty in the Vietnamese stock market, helping investors in their decision-making processes and contributing to the overall understanding of the market. Indeed, understanding volatility and its implications is essential for investors, policymakers, and researchers, particularly in emerging markets like Vietnam, where financial systems are evolving rapidly.
Copyright (c) 2026 Anna Grazia Quaranta, Francesca Pampurini
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