The Information Content of Realized Volatility Forecasts
Torben Andersen*(Northwestern University), Per Frederiksen(Nordea Bank),
Arne Staal from(Lehman Brothers)
Abstract
We examine the relative information content of monthly volatility forecasts
derived from option prices and timeseries forecasts of realized volatility.
If volatility risk is priced the return variance process is different
under the physical and riskneutral pricing measures, which has important
implications for the interpretation of implied volatility as an expectation
of future volatility. We use recent developments in volatility measurement
and modeling to capture and forecast the variance process. Our results
suggest that forecasts of future realized volatility based on past realized
volatility are unbiased, more efficient than VIX modelfree implied volatility,
and roughly as efficient as Black and Scholes implied volatility. Forecasts
of future volatility based on historical realized volatility contain incremental
information relative to both modelfree and BlackScholes implied volatility.
This finding can be explained in the context of priced variance risk.
Given the finding of different information contained in individual volatility
forecasts, we show that conditional volatility forecasts can be improved
upon by combining individual measures. We also show that predictive regressions
of realized volatility on option implied volatility are likely to be misspecified
due to the presence of long memory in such measures and the variance risk
premium.
