Template-Type: ReDIF-Paper 1.0

Author-Name: Ai Deng
Author-X-Name-First: Ai
Author-X-Name-Last: Deng
Author-Email: dengai@bu.edu
Author-Workplace-Name: Department of Economics, Boston University

Title: Understanding Spurious Regression in Financial Economics

Abstract: This paper provides an asymptotic theory for the spurious regression analyzed by
Ferson, Sarkissian and Simin (2003). The asymptotic framework developed by Nabeya
and Perron (1994) is used to provide approximations for the various estimates and
statistics. Also, using a fixed-bandwidth asymptotic framework, a convergent t test
is constructed, following Sun (2005). These are shown to be accurate and to explain
the simulation findings in Ferson et al. (2003). Monte Carlo studies show that our
asymptotic distribution provides a very good finite sample approximation for sample
sizes often encountered in finance. Our analysis also reveals an important potential
problem in the theoretical hypothesis testing literature on predictability. A possible
reconciling interpretation is provided.


Length: 39 pages
Creation-Date: 2005-12
Revision-Date: 
Publication-Status:
File-URL: http://www.bu.edu/econ/workingpapers/papers/spurious.pdf
File-Format: Application/pdf
File-Function: 
Number: WP2005-048
Classification-JEL: 
Keywords: spurious regression, observational equivalence, Nabeya-Perron asymptotics,
fixed-b asymptotics, data mining, nearly integrated, nearly white noise (NINW)
Handle: RePEc:bos:wpaper:WP2005-048