Journal of the Operational Research Society

, Volume 20, Issue 2, pp 199–207

Prediction with a Generalized Cost of Error Function

  • C. W. J. Granger
General Paper

DOI: 10.1057/jors.1969.52

Cite this article as:
Granger, C. J Oper Res Soc (1969) 20: 199. doi:10.1057/jors.1969.52

Abstract

Classical prediction theory limits itself to quadratic cost functions, and hence least-square predictors. However, the cost functions that arise in practice in economics and management situations are not likely to be quadratic in form, and frequently will be non-symmetric. It is the object of this paper to throw light on prediction in such situations and to suggest some practical implications. It is suggested that a useful, although sub-optimal, manner of taking into account generalized cost functions is to add a constant bias term to the predictor. Two theorems are proved showing that under fairly general conditions the bias term can be taken to be zero when one uses a symmetric cost function. If the cost function is a non-symmetric linear function, an expression for the bias can be simply obtained.

Copyright information

© Operational Research Society 1968

Authors and Affiliations

  • C. W. J. Granger
    • 1
  1. 1.University of NottinghamNottingham