Volatility Forecasting With Range-Based EGARCH Models

@article{Brandt2006VolatilityFW,
  title={Volatility Forecasting With Range-Based EGARCH Models},
  author={Michael W. Brandt and Christopher S. Jones},
  journal={Journal of Business \& Economic Statistics},
  year={2006},
  volume={24},
  pages={470 - 486}
}
We provide a simple, yet highly effective framework for forecasting return volatility by combining exponential generalized autoregressive conditional heteroscedasticity models with data on the range. Using Standard and Poor's 500 index data for 1983–2004, we demonstrate the importance of a long-memory specification, based on either a two-factor structure or fractional integration, that allows for some asymmetry between market returns and volatility innovations. Out-of-sample forecasts reinforce… 
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