Bayesian testing volatility persistence in stochastic volatility models with jumps

• Main Authors: LIU, Xiaobin, LI, Yong
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2014
• Subjects: Bayesian analysis; Calibration of stochastic volatility; Bayesian statistics; Financial time series; Financial econometrics; Volatility modelling; Finance
• Online Access: https://ink.library.smu.edu.sg/soe_research/2202; https://ink.library.smu.edu.sg/context/soe_research/article/3201/viewcontent/Bayesian_testing_volatility_persistence_in_stochastic_volatility_models_with_jumps_2014_afv.pdf
• Institution: Singapore Management University

Whether or not there is a unit root persistence in volatility of financial assets has been a long-standing topic of interest to financial econometricians and empirical economists. The purpose of this article is to provide a Bayesian approach for testing the volatility persistence in the context of stochastic volatility with Merton jump and correlated Merton jump. The Shanghai Composite Index daily return data is used for empirical illustration. The result of Bayesian hypothesis testing strongly indicates that the volatility process doesn’t have unit root volatility persistence in this stock market.