Optimal Prediction Under Asymmetric Loss / Peter F. Christoffersen, Francis X. Diebold.

By:

Christoffersen, Peter F

Contributor(s):

Material type: Text

TextSeries: Technical Working Paper Series (National Bureau of Economic Research) ; no. t0167.Publication details: Cambridge, Mass. National Bureau of Economic Research 1994.Description: 1 online resource: illustrations (black and white)Online resources:

Available additional physical forms:

Hardcopy version available to institutional subscribers

Abstract: Prediction problems involving asymmetric loss functions arise routinely in many fields, yet the theory of optimal prediction under asymmetric loss is not well developed. We study the optimal prediction problem under general loss structures and characterize the optimal predictor. We compute the optimal predictor analytically in two leading cases. Analytic solutions for the optimal predictor are not available in more complicated cases, so we develop numerical procedures for computing it. We illustrate the results by forecasting the GARCH(1,1) process which, although white noise, is non-trivially forecastable under asymmetric loss.

Tags from this library: No tags from this library for this title. Log in to add tags.

Average rating: 0.0 (0 votes)

Holdings
Item type	Home library	Collection	Call number	Status	Date due	Barcode	Item holds
Working Paper	Biblioteca Digital	Colección NBER	nber t0167 (Browse shelf(Opens below))	Not For Loan

Total holds: 0

Collection: Colección NBER Close shelf browser (Hides shelf browser)

Previous	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	No cover image available	Next
Previous	nber t0164 Evidence on Structural Instability in Macroeconomic Time Series Relations /	nber t0165 Estimating Deterministic Trends in the Presence of Serially Correlated Errors /	nber t0166 Accounting for Dropouts in Evaluations of Social Experiments /	nber t0167 Optimal Prediction Under Asymmetric Loss /	nber t0168 Estimating Multiple-Discrete Choice Models: An Application to Computeri-zzation Returns /	nber t0169 Comparing Predictive Accuracy /	nber t0170 Natural and Quasi- Experiments in Economics /	Next

October 1994.

Prediction problems involving asymmetric loss functions arise routinely in many fields, yet the theory of optimal prediction under asymmetric loss is not well developed. We study the optimal prediction problem under general loss structures and characterize the optimal predictor. We compute the optimal predictor analytically in two leading cases. Analytic solutions for the optimal predictor are not available in more complicated cases, so we develop numerical procedures for computing it. We illustrate the results by forecasting the GARCH(1,1) process which, although white noise, is non-trivially forecastable under asymmetric loss.