An Analytical Framework for Assessing Asset Pricing Models and Predictability

47 Pages Posted: 19 Mar 2008

See all articles by René Garcia

René Garcia

Université de Montréal - CIREQ - Département de sciences économiques; University of Montreal

Nour Meddahi

Imperial College Business School

Roméo Tédongap

ESSEC Business School

Date Written: March 2008

Abstract

New insights about the connections between stock market volatility and returns, the pricing of long-run claims, or return predictability have recently revived interest in consumption-based equilibrium asset pricing. The recursive utility model is prominently used in these contexts to determine the price of assets in equilibrium. Often, solutions are approximate and quantities of interest are computed through simulations. We propose an approach that delivers closed-form formulas for price-consumption and price-dividend ratios, as well as for many of the statistics usually computed to assess the ability of the model to reproduce stylized facts. The proposed framework is flexible enough to capture rich dynamics for consumption and dividends. Closed-form formulas facilitate the economic interpretation of empirical results. We illustrate the usefulness of our approach by investigating the properties of long-run asset pricing models in many empirical dimensions.

Keywords: Equilibrium Asset Pricing, Equity Premium, Risk-free Rate Puzzle, Predictability

JEL Classification: G12, G11, C10, C50

Suggested Citation

Garcia, René and Meddahi, Nour and Tédongap, Roméo, An Analytical Framework for Assessing Asset Pricing Models and Predictability (March 2008). Available at SSRN: https://ssrn.com/abstract=1109080 or http://dx.doi.org/10.2139/ssrn.1109080

René Garcia (Contact Author)

Université de Montréal - CIREQ - Département de sciences économiques ( email )

C.P. 6128, succursale Centre-Ville
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University of Montreal ( email )

United States

Nour Meddahi

Imperial College Business School ( email )

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London, SW7 2AZ
United Kingdom

Roméo Tédongap

ESSEC Business School ( email )

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France
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+33134439734 (Fax)

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