The Journal of Finance publishes leading research across all the major fields of finance. It is one of the most widely cited journals in academic finance, and in all of economics. Each of the six issues per year reaches over 8,000 academics, finance professionals, libraries, and government and financial institutions around the world. The journal is the official publication of The American Finance Association, the premier academic organization devoted to the study and promotion of knowledge about financial economics.
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Search results: 3.
Approximating the Asset Pricing Kernel
Published: 04/18/2012 | DOI: 10.1111/j.1540-6261.1997.tb01114.x
DAVID A. CHAPMAN
This article tests a simple consumption‐based asset pricing model by approximating the true asset pricing kernel using low‐order orthonormal polynomials based on the model's state variables. Approximated kernels based solely on next period's consumption growth are not rejected by overall measures of model fit, but they produce statistically and economically large pricing errors. Approximated kernels based on two quarters of future consumption growth and technology shocks have substantially improved overall fit. In particular, the best of these kernels are capable of eliminating the small firm effect.
First‐Order Risk Aversion, Heterogeneity, and Asset Market Outcomes
Published: 07/16/2009 | DOI: 10.1111/j.1540-6261.2009.01482.x
DAVID A. CHAPMAN, VALERY POLKOVNICHENKO
We examine a wide range of two‐date economies populated by heterogeneous agents with the most common forms of nonexpected utility preferences used in finance and macroeconomics. We demonstrate that the risk premium and the risk‐free rate in these models are sensitive to ignoring heterogeneity. This follows because of endogenous withdrawal by nonexpected utility agents from the market for the risky asset. This finding is important precisely because these alternative preferences have frequently been proposed as possible resolutions to various asset pricing puzzles, and they have all been examined exclusively in a representative agent framework.
Is the Short Rate Drift Actually Nonlinear?
Published: 03/31/2007 | DOI: 10.1111/0022-1082.00208
David A. Chapman, Neil D. Pearson
Aït‐Sahalia (1996) and Stanton (1997) use nonparametric estimators applied to short‐term interest rate data to conclude that the drift function contains important nonlinearities. We study the finite‐sample properties of their estimators by applying them to simulated sample paths of a square‐root diffusion. Although the drift function is linear, both estimators suggest nonlinearities of the type and magnitude reported in Aït‐Sahalia (1996) and Stanton (1997). Combined with the results of a weighted least squares estimator, this evidence implies that nonlinearity of the short rate drift is not a robust stylized fact.