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.

Additional Metadata
Keywords Stochastic Volatility, Realized Measure, Long Memory, Asymmetry, Whittle likelihood, Asymptotic Distribution
JEL Estimation (jel C13), Time-Series Models; Dynamic Quantile Regressions (jel C22)
Persistent URL hdl.handle.net/1765/100161
Series Tinbergen Institute Discussion Paper Series , Econometric Institute Research Papers
Citation
Asai, M, Chang, C-L, & McAleer, M.J. (2017). Realized Stochastic Volatility with General Asymmetry and Long Memory (No. EI2017-09). Econometric Institute Research Papers. Retrieved from http://hdl.handle.net/1765/100161