Further Results on Forecasting and Model Selection under Asymmetric Loss.
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. Copyright 1996 by John Wiley & Sons, Ltd.
Year of publication: |
1996
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Authors: | Christoffersen, Peter F ; Diebold, Francis X |
Published in: |
Journal of Applied Econometrics. - John Wiley & Sons, Ltd.. - Vol. 11.1996, 5, p. 561-71
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Publisher: |
John Wiley & Sons, Ltd. |
Saved in:
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