Generalized (Cross) Spectral Tests for Optimal Forecasts and Conditional Predictive Ability Under Generalized Loss Functions
AbstractUnder the squared error loss, the optimal forecast is the conditional mean, and the one-step forecast error is a martingale difference (MD). The one-step forecast error forms the conditional moment condition obtained from the loss derivative with respect to the forecast. Similarly, under a generalized loss function, the derivative of the loss with respect to the forecast is an MD. Given a loss function, the forecast optimality may be checked by testing for the MD property of the loss derivative. In this paper, we show that the generalized (cross) spectral test of Hong (1999) may be used to evaluate the forecast optimality and that its asymptotic distribution is not affected by the parameter estimation uncertainty, provided that the training sample grows suitably faster than the validation sample and that the parameters are estimated at root-n rate. We also use the generalized (cross) spectral test to compare the conditional predictive ability of competing forecasting models by testing the MD property of their loss differential
Download InfoTo our knowledge, this item is not available for download. To find whether it is available, there are three options:
1. Check below under "Related research" whether another version of this item is available online.
2. Check on the provider's web page whether it is in fact available.
3. Perform a search for a similarly titled item that would be available.
Bibliographic InfoPaper provided by Econometric Society in its series Econometric Society 2004 North American Winter Meetings with number 614.
Date of creation: 11 Aug 2004
Date of revision:
Contact details of provider:
Phone: 1 212 998 3820
Fax: 1 212 995 4487
Web page: http://www.econometricsociety.org/pastmeetings.asp
More information through EDIRC
Generalized (cross) spectum; Optimal forecasts; Generalized loss functions; Parameter estimation error; Martingale difference; Conditional predictive ability;
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 &bull Diffusion Processes
- C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum).
If references are entirely missing, you can add them using this form.