| By: |
Asai, M.;
Chang, C-L.;
McAleer, M.J. |
| 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. |
| Keywords: |
Stochastic Volatility, Realized Measure, Long Memory, Asymmetry, Whittle likelihood, Asymptotic Distribution |
| JEL: |
C13 C22 |
| Date: |
2017–04–01 |
| URL: |
http://d.repec.org/n?u=RePEc:ems:eureir:100161&r=for |