There is a large literature covering volatility forecasts with high-frequency tick data. Much of this has surrounded the concept of "realized volatility", such as:
- "Realized Volatility and Correlation" (Andersen, Bollerslev, Diebold, and Labys 1999)
- "Modeling and Forecasting Realized Volatility" (Andersen, Bollerslev, Diebold, and Labys 1999)
Other efforts have looked at high/low data to improve the forecast without including all the tick data.
What's the best way for forecast volatility using high-frequency data?
Note: A similar question was previously asked on Wilmott.