Risk Neutral Forecasting
AbstractA notion of forecast quality is defined that is appropriate when returns forecasts are used in a simple investment decision. The relation between the conditional distribution of returns and optimal point forecasts for a risk neutral investor is characterised and it is shown that the conditional mean is a small subset of optimal forecasts. Taking into account potential model misspecification and the structure of the set of optimal forecasts, methods for developing specifically `risk neutral forecasting' models are proposed. Estimation by Empirical Risk Minimisation is shown to converge to parameters associated with optimal decisions and simulations suggest that performance in small samples is acceptable even in unfavourable circumstances. Usefulness of the proposed methods is illustrated with an empirical application in which they dominate popular alternatives.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2001 with number 50.
Date of creation: 01 Apr 2001
Date of revision:
Contact details of provider:
Web page: http://www.econometricsociety.org/conference/SCE2001/SCE2001.html
More information through EDIRC
financial decision-making; empirical risk minimisation;
Other versions of this item:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory
- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
This paper has been announced in the following NEP Reports:
You can help add them by filling out this form.
CitEc Project, subscribe to its RSS feed for this item.
- Dewachter, H.D.R. & Lyrio, M., 2003.
"The Cost of Technical Trading Rules in the Forex Market: A Utility-based Evaluation,"
ERS-2003-052-F&A, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus Uni.
- Dewachter, Hans & Lyrio, Marco, 2006. "The cost of technical trading rules in the Forex market: A utility-based evaluation," Journal of International Money and Finance, Elsevier, vol. 25(7), pages 1072-1089, November.
- Skouras, Spyros, 2003. "An algorithm for computing estimators that optimize step functions," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 349-361, March.
- Fong, Wai Mun & Yong, Lawrence H. M., 2005. "Chasing trends: recursive moving average trading rules and internet stocks," Journal of Empirical Finance, Elsevier, vol. 12(1), pages 43-76, January.
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.