An information-theoretic asset pricing model

Ghosh, Anisha, Julliard, Christian ORCID: 0000-0001-8177-7441 and Taylor, Alex. P (2024) An information-theoretic asset pricing model. Journal of Financial Econometrics. ISSN 1479-8409 (In Press)

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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 SDF (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 a compensation for 2.5% tail events. The I-SDF offers a powerful benchmark relative to which competing theories and investment strategies can be evaluated

Item Type:	Article
Divisions:	Finance
Subjects:	H Social Sciences > HG Finance H Social Sciences > HB Economic Theory
JEL classification:	G - Financial Economics > G1 - General Financial Markets > G11 - Portfolio Choice; Investment Decisions G - Financial Economics > G1 - General Financial Markets > G12 - Asset Pricing; Trading volume; Bond Interest Rates C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods: General > C13 - Estimation C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C53 - Forecasting and Other Model Applications
Date Deposited:	22 Nov 2024 15:39
Last Modified:	12 Dec 2024 04:35
URI:	http://eprints.lse.ac.uk/id/eprint/126155

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