Library Header Image
LSE Research Online LSE Library Services

Multi-asset noisy rational expectations equilibrium with contingent claims

Chabakauri, Georgy, Yuan, Kathy and Zachariadis, Konstantinos E. (2022) Multi-asset noisy rational expectations equilibrium with contingent claims. Review of Economic Studies, 89 (5). 2445 - 2490. ISSN 0034-6527

[img] Text (Chabakauri_multi-asset-noisy-rational-expectations--published) - Published Version
Available under License Creative Commons Attribution Non-commercial.

Download (734kB)

Identification Number: 10.1093/restud/rdab081


We study a noisy rational expectations equilibrium in a multi-asset economy populated by informed and uninformed investors and noise traders. The assets can include state contingent claims such as Arrow-Debreu securities, assets with only positive payoffs, options or other derivative securities. The probabilities of states depend on an aggregate shock, which is observed only by the informed investor. We derive a three-factor CAPM with asymmetric information, establish conditions under which asset prices reveal information about the shock, and show that information asymmetry amplifies the effects of payoff skewness on asset returns. We also find that volatility derivatives make incomplete markets effectively complete, and their prices quantify market illiquidity and shadow value of information to uninformed investors.

Item Type: Article
Official URL:
Additional Information: © 2021 The Authors
Divisions: Finance
Subjects: H Social Sciences > HB Economic Theory
H Social Sciences > HG Finance
JEL classification: D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D82 - Asymmetric and Private Information
G - Financial Economics > G1 - General Financial Markets > G12 - Asset Pricing; Trading volume; Bond Interest Rates
G - Financial Economics > G1 - General Financial Markets > G14 - Information and Market Efficiency; Event Studies
Date Deposited: 22 Sep 2021 15:54
Last Modified: 17 Apr 2024 16:24

Actions (login required)

View Item View Item


Downloads per month over past year

View more statistics