Forecasting Realized Volatility with Linear and Nonlinear Models
Journal of Economic Surveys, v. 25, TD n. 1, 2011
p. 6-18,
In this paper, we consider a nonlinear model based on neural networks as well as linear models to forecast the daily volatility of the S&P 500 and FTSE 100 futures. As a proxy for daily volatility, we consider a consistent and unbiased estimator of the integrated volatility that is computed from high-frequency intraday returns. We also consider a simple algorithm based on bagging (bootstrap aggregation) in order to specify the models analysed in this paper.
Michael McAller, Marcelo Medeiros.