Asymmetric Volatility Models with Structural Breaks

作者：Rohan Neelabh; Ramanathan T V^*

来源：Communications in Statistics - Simulation and Computation, 2012, 41(9): 1519-1543.

DOI：10.1080/03610918.2011.611403

• Asymmetry
• GARCH model
• Gibbs sampling
• MCMC
• News impact
• Structural break
• Volatility

This article develops an asymmetric volatility model that takes into consideration the structural breaks in the volatility process. Break points and other parameters of the model are estimated using MCMC and Gibbs sampling techniques. Models with different number of break points are compared using the Bayes factor and BIC. We provide a formal test and hence a new procedure for Bayes factor computation to choose between models with different number of breaks. The procedure is illustrated using simulated as well as real data sets. The analysis shows an evidence to the fact that the financial crisis in the market from the first week of September 2008 has caused a significant break in the structure of the return series of two major NYSE indices viz., S & P 500 and Dow Jones. Analysis of the USD/EURO exchange rate data also shows an evidence of structural break around the same time.

• 出版日期2012-10-1