Forecasting Nonlinear Functions of Returns Using LINEX Loss Functions
AbstractThis paper applies LINEX loss functions to forecasting nonlinear functions of variance. We derive the optimal one-step-ahead LINEX forecast for various volatility models using data transformations such as ln(y2t) where yt is the return of the asset. Our results suggest that the LINEX loss function is particularly well-suited to many of these forecasting problems and can give better forecasts than conventional loss functions such as mean square error (MSE).
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Bibliographic InfoArticle provided by Society for AEF in its journal Annals of Economics and Finance.
Volume (Year): 2 (2001)
Issue (Month): 1 (May)
LINEX Loss Function; Forecasting; Volatility;
Find related papers by JEL classification:
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
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