NATIONAL BUREAU OF ECONOMIC RESEARCH
NATIONAL BUREAU OF ECONOMIC RESEARCH

A Rehabilitation of Stochastic Discount Factor Methodology

John H. Cochrane

NBER Working Paper No. 8533
Issued in October 2001
NBER Program(s):   AP

In a recent Journal of Finance article, Kan and Zhou (1999) find that the 'Stochastic discount factor' methodology using GMM is markedly inferior to traditional maximum likelihood even in a simple test of the static CAPM with i.i.d. normal returns. This result has gained wide attention. However, as Jagannathan and Wang (2001) point out, this result flows from a strange assumption: Kan and Zhou allow the ML estimate to know the mean market return ex-ante. I show how this information advantage explains Kan and Zhou's results. In fact, when treated symmetrically, the discount factor - GMM and traditional methodologies behave almost identically in linear i.i.d. environments.

download in pdf format
   (194 K)

email paper

This paper is available as PDF (194 K) or via email.

Machine-readable bibliographic record - MARC, RIS, BibTeX

Document Object Identifier (DOI): 10.3386/w8533

Users who downloaded this paper also downloaded these:
Burnside w16634 Identification and Inference in Linear Stochastic Discount Factor Models
Jagannathan and Wang w8098 Empirical Evaluation of Asset Pricing Models: A Comparison of the SDF and Beta Methods
Cochrane w7169 New Facts in Finance
Cochrane w8066 The Risk and Return of Venture Capital
Farnsworth, Ferson, Jackson, and Todd w8791 Performance Evaluation with Stochastic Discount Factors
 
Publications
Activities
Meetings
Data
People
About

Support
National Bureau of Economic Research, 1050 Massachusetts Ave., Cambridge, MA 02138; 617-868-3900; email: info@nber.org

Contact Us