Abstract
This paper studies the features of the stock return volatility using GARCH models and the presence of structural breaks in return variance of VNIndex in the Vietnam stock market by using the iterated cumulative sums of squares (ICSS) algorithm. Using a long-span data, GARCH and GARCH in mean (GARCH-M) models seems to be effective in describing daily stock returns’ features. About structural breaks, when applying ICSS to standardized residuals filtered from GARCH (1, 1) model, the number of volatility shifts significantly decreases in comparison with the raw return series. Events corresponding to those breaks and altering the volatility pattern of stock return are found to be country-specific. Not any shifts are found during global crisis period. Further evidence also reveals that when sudden shifts are taken into account in the GARCH models, volatility persistence remarkably reduces and that the conditional variance of stock return is much affected by past trend of observed shocks and variance. Our results have important implications regarding advising investors on decisions concerning pricing equity, portfolio investment and management, hedging and forecasting. Moreover, it is also helpful for policy-makers in making and promulgating the financial policies.
Highlights
Volatility is a fundamental concept in the discipline of finance
Following Inclan and Tiao (1994), clear effects of regime changes gained from iterated cumulative sums of squares (ICSS) algorithm on volatility of stock market return and reduction in highly persistent volatility of stock return were presented in the papers of Aggarwal, Inclan et al (1999), Susmel (2000), Malik and Hassan (2004), Malik, Farooq et al (2005), Wang and Moore (2009), and Long (2008)
Lamoureux and Latrapes (1990) and some other researchers showed that volatility persistence was overestimated when standard GARCH models were applied to a series with underlying sudden changes in variance
Summary
Volatility is a fundamental concept in the discipline of finance. Considerable volatilities have been found in the past few years in mature and emerging financial markets worldwide. A procedure based on an iterated cumulative sums of squares (ICSS) by Inclan and Tiao (1994) is commonly used to detect number of (significant) sudden changes in variance in time series, as well as to estimate the time. The linkage between volatility shifts in Vietnam stock market with impacts from global crisis in US in 2008 is mentioned. These detected volatility regimes are included in the standard GARCH model to calculate the "true" estimate of volatility persistence.
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