Forecasting (LOG) Volatility Models
AbstractA number of volatility forecasting studies have led to the perception that the ARCH- and Stochastic Volatility-type models provide poor out-of-sample forecasts of volatility. This is primarily based on the use of traditional forecast evaluation criteria concerning the accuracy and the unbiasedness of forecasts. In this paper we provide an assessment of volatility forecasting. We use the Log- Volatility framework to show how the inherent noise in the approximation of the actual- and unobservable - volatility by the squared return results in a misleading forecast evaluation. We argue that evaluation problems are likely to be exacebated by non-normality of the shocks and that non-linear and utility-based criteria can be more suitable for the evaluation of volatility forecasts.
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Bibliographic InfoPaper provided by Exeter University, Department of Economics in its series Discussion Papers with number 9814.
Date of creation: 1998
Date of revision:
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ECONOMETRICS ; ECONOMETRIC MODELS ; FORECASTING TECHNIQUES ; FORECASTS;
Find related papers by JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
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