An information-theoretic asset pricing model

Anisha Ghosh, Christian Julliard and Alex. P Taylor

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: We show that a non-parametric estimate of the pricing kernel, extracted using an information-theoretic approach, delivers smaller out-of-sample pricing errors and a better cross-sectional fit than leading multi-factor models. The information stochastic discount factor (I-SDF) identifies sources of risk not captured by standard factors, generating very large annual alphas (20–37%) and Sharpe ratio (1.1). The I-SDF extracted from a wide cross-section of equity portfolios is highly positively skewed and leptokurtic, and implies that about a third of the observed risk premia represent compensation for 2.5% tail events. The I-SDF offers a powerful benchmark relative to which competing theories and investment strategies can be evaluated.

Keywords: pricing kernal; relative entropy; cross-sectional asset pricing; factor models; factor mimicking portfolios; alpha (search for similar items in EconPapers)
JEL-codes: C13 C53 G11 G12 (search for similar items in EconPapers)
Pages: 40 pages
Date: 2025-01-13
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Published in Journal of Financial Econometrics, 13, January, 2025, 23(1). ISSN: 1479-8409

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