Return Predictability under Equilibrium Constraints on the Equity Premium
Davide Pettenuzzo (),
Allan Timmermann and
Rossen Valkanov
Additional contact information
Rossen Valkanov: Rady School of Management, University of California, San Diego
No 37, Working Papers from Brandeis University, Department of Economics and International Business School
Abstract:
This paper proposes a new approach for incorporating theoretical constraints on return forecasting models such as non-negativity of the conditional equity premium and sign restrictions on the coefficients linking state variables to the equity premium. Our approach makes use of Bayesian methods that update the estimated parameters at each point in time in a way that optimally exploits information in these constraints. Using a variety of predictor variables from the literature on predictability of stock returns, we find that theoretical constraints have an important effect on the coefficient estimates and can significantly reduce biases and estimation errors in these. In out-of-sample forecasting experiments we find that models that exploit the theoretical restrictions produce better forecasts than unconstrained models.
Keywords: Return Predictability; Constraints; Out-of-Sample Forecasts (search for similar items in EconPapers)
JEL-codes: C22 G12 G14 (search for similar items in EconPapers)
Pages: 34 pages
Date: 2008-10
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
http://www.brandeis.edu/economics/RePEc/brd/doc/Brandeis_WP37.pdf First version, 2008 (application/pdf)
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:brd:wpaper:37
Access Statistics for this paper
More papers in Working Papers from Brandeis University, Department of Economics and International Business School Contact information at EDIRC.
Bibliographic data for series maintained by Andrea Luna ().