We include simultaneously both realized volatility measures based on high-frequency asset returns and implied volatilities backed out of individual traded at the money option prices in a state space approach to the analysis of true underlying volatility. We model integrated volatility as a latent fi…rst order Markov process and show that our model is closely related to the CEV and Barndorff-Nielsen & Shephard (2001) models for local volatility. We show that if measurement noise in the observable volatility proxies is not accounted for, then the estimated autoregressive parameter in the latent process is downward biased. Implied volatility performs better than any of the alternative realized measures when forecasting future integrated volatility. The results are largely similar across the stock market (S&P 500), bond market (30-year U.S. T-bond), and foreign currency exchange market ($/£ ).
Originalsprog
Engelsk
Udgivelsessted
Aarhus
Udgiver
CREATES, Institut for Økonomi, Aarhus Universitet
Antal sider
36
Status
Udgivet - 14 feb. 2010
Forskningsområder
Autoregression, bipower variation, high-frequency data, implied volatility, integrated volatility, Kalman fi lter, moving average, option prices, realized volatility, state space model, stochastic volatility.