Incomplete Information and the Liquidity Premium Puzzle

Management Science, forthcoming

63 Pages Posted: 14 Dec 2018 Last revised: 27 May 2020

See all articles by Yingshan Chen

Yingshan Chen

South China University of Technology

Min Dai

National University of Singapore (NUS) - Department of Mathematics

Luis Goncalves-Pinto

University of New South Wales (UNSW); Chinese University of Hong Kong (CUHK)

Jing Xu

Renmin University of China - School of Finance

Cheng Yan

Durham Business School

Date Written: February 10, 2020

Abstract

We examine the problem of an investor who trades in a market with unobservable regime shifts. The investor learns from past prices and is subject to transaction costs. Our model generates significantly larger liquidity premia compared to a benchmark model with observable market shifts. The larger premia are driven primarily by suboptimal risk exposure, as turnover is lower under incomplete information. In contrast, the benchmark model produces (mechanically) high turnover and heavy trading costs. We provide empirical support for the amplification effect of incomplete information on the relation between trading costs and future stock returns. We also show empirically that such amplification is not driven by turnover. Overall, our results can help explain the large disconnect between theory and evidence regarding the magnitude of liquidity premia, which has been a longstanding puzzle in the literature.

Keywords: Regime Shifts, Incomplete Information, Transaction Costs, Liquidity Premia

JEL Classification: C61, D11, D91, G11

Suggested Citation

Chen, Yingshan and Dai, Min and Goncalves-Pinto, Luis and Xu, Jing and Yan, Cheng, Incomplete Information and the Liquidity Premium Puzzle (February 10, 2020). Management Science, forthcoming, Available at SSRN: https://ssrn.com/abstract=3288878 or http://dx.doi.org/10.2139/ssrn.3288878

Yingshan Chen

South China University of Technology ( email )

Wushan
Guangzhou, AR Guangdong 510640
China

Min Dai

National University of Singapore (NUS) - Department of Mathematics ( email )

Singapore

Luis Goncalves-Pinto (Contact Author)

University of New South Wales (UNSW) ( email )

Kensington
High St
Sydney, NSW 2052
Australia

HOME PAGE: http://luis.goncalvespinto.com/

Chinese University of Hong Kong (CUHK) ( email )

Cheng Yu Tung Building
Shatin
Hong Kong
Hong Kong

Jing Xu

Renmin University of China - School of Finance ( email )

59 Zhongguancun Street
Beijing, 100872
China

Cheng Yan

Durham Business School ( email )

Mill Hill Lane
Durham, Durham DH1 3LB
United Kingdom

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