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Realized stochastic volatility with general asymmetry and long memory

Manabu Asai, Chia-Lin Chang () and Michael McAleer

Journal of Econometrics, 2017, vol. 199, issue 2, 202-212

Abstract: The paper develops a novel realized stochastic volatility model of asset returns and realized volatility that incorporates general asymmetry and long memory (hereafter the RSV-GALM model). The contribution of the paper ties in with Robert Basmann’s seminal work in terms of the estimation of highly non-linear model specifications (Basmann, 1988), especially for specifying causal effects from returns to future volatility. This paper discusses asymptotic results of a Whittle likelihood estimator for the RSV-GALM model and a test for general asymmetry, and analyzes the finite sample properties. The paper also develops an approach to obtain volatility estimates and out-of-sample forecasts. Using high frequency data for three US financial assets, the new model is estimated and evaluated. The paper compares the forecasting performance of the new model with a realized conditional volatility model.

Keywords: Stochastic volatility; Realized measure; Long memory; Asymmetry; Whittle likelihood; Asymptotic distribution (search for similar items in EconPapers)
JEL-codes: C13 C22 (search for similar items in EconPapers)
Date: 2017
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Working Paper: Realized Stochastic Volatility with General Asymmetry and Long Memory (2017) Downloads
Working Paper: Realized Stochastic Volatility with General Asymmetry and Long Memory (2017) Downloads
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