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A0266
Title: Choosing between persistent and stationary volatility Authors:  Ilias Chronopoulos - University of Essex (United Kingdom) [presenting]
Liudas Giraitis - Queen Mary University of London (United Kingdom)
George Kapetanios - Kings College, University of London (United Kingdom)
Abstract: A multiplicative volatility model is suggested where volatility is decomposed into a stationary and a non-stationary persistent part. We provide a testing procedure to determine which type of volatility is prevalent in the data. The persistent part of volatility is associated with a nonstationary persistent process satisfying some smoothness and moment conditions. The stationary part is related to stationary conditional heteroskedasticity. We outline theory and conditions that allow the extraction of the persistent part from the data and enable standard conditional heteroskedasticity tests to detect stationary volatility after persistent volatility is taken into account. Monte Carlo results support the testing strategy in small samples. The empirical application of the theory supports the persistent volatility paradigm, suggesting that stationary conditional heteroskedasticity is considerably less pronounced than previously thought.