Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/162304
Authors: 
Asai, Manabu
Chang, Chia-Lin
McAleer, Michael
Year of Publication: 
2017
Series/Report no.: 
Tinbergen Institute Discussion Paper 17-038/III
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 (“Causality tests and observationally equivalent representations of econometric models”, Journal of Econometrics, 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 analyses 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.
Subjects: 
Stochastic Volatility
Realized Measure
Long Memory
Asymmetry
Whittle likelihood
JEL: 
C13
C22
Document Type: 
Working Paper

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