Further results on forecasting and model selection under asymmetric loss
✍ Scribed by Peter F. Christoffersen; Francis X. Diebold
- Publisher
- John Wiley and Sons
- Year
- 1996
- Tongue
- English
- Weight
- 606 KB
- Volume
- 11
- Category
- Article
- ISSN
- 0883-7252
No coin nor oath required. For personal study only.
✦ Synopsis
We make three related contributions. First, we propose a new technique for solving prediction problems under asymmetric loss using piecewise-linear approximations to the loss function, and we establish existence and uniqueness of the optimal predictor. Second, we provide a detailed application to optimal prediction of a conditionally heteroscedastic process under asymmetric loss, the insights gained from which are broadly applicable. Finally, we incorporate our results into a general framework for recursive prediction-based model selection under the relevant loss function.
' A prediction-error loss function, L ( . ) , is a loss function defined directly on the prediction error, yj .