Market efficiency in the age of big data

Martin, Ian W.R. ORCID: 0000-0001-8373-5317 and Nagel, Stefan (2022) Market efficiency in the age of big data. Journal of Financial Economics, 145 (1). 154 - 177. ISSN 0304-405X

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Abstract

Modern investors face a high-dimensional prediction problem: thousands of observable variables are potentially relevant for forecasting. We reassess the conventional wisdom on market efficiency in light of this fact. In our equilibrium model, N assets have cash flows that are linear in J characteristics, with unknown coefficients. Risk-neutral Bayesian investors learn these coefficients and determine market prices. If J and N are comparable in size, returns are cross-sectionally predictable ex post. In-sample tests of market efficiency reject the no-predictability null with high probability, even though investors use information optimally in real time. In contrast, out-of-sample tests retain their economic meaning.

Item Type:	Article
Official URL:	https://www.sciencedirect.com/journal/journal-of-f...
Additional Information:	© 2021 The Authors
Divisions:	Finance
Subjects:	H Social Sciences > HG Finance H Social Sciences > HB Economic Theory
JEL classification:	G - Financial Economics > G1 - General Financial Markets > G14 - Information and Market Efficiency; Event Studies 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 > C11 - Bayesian Analysis
Date Deposited:	15 Dec 2021 09:18
Last Modified:	08 Nov 2024 21:36
URI:	http://eprints.lse.ac.uk/id/eprint/112960

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