Robust Pricing under Strategic Trading

73 Pages Posted: 27 May 2020 Last revised: 30 Jan 2021

See all articles by Aibo Gong

Aibo Gong

University of Michigan, Ann Arbor

Shaowei Ke

University of Michigan at Ann Arbor - Department of Economics

Yawen Qiu

Shanghai University of Economics and Finance

Rui Shen

The Chinese University of Hong Kong, Shenzhen - School of Management and Economics; Shenzhen Finance Institute

Date Written: January 30, 2021

Abstract

We study strategic trading with a market maker who does not know the joint distribution of public information and an asset's value, and hence cannot interpret information properly. Following a public event, a probabilistic-ally informed trader who knows the distribution and liquidity traders trade. The market maker adopts a robust linear pricing strategy that has the best worst-case payoff guarantee. We show that such a strategy is equivalent to a two-step learning procedure, and characterize the unique linear equilibrium. Expected equilibrium prices exhibit under-reaction to public information. If the trading frequency is arbitrarily high, the market maker fully reveals the distribution in the price eventually.

Keywords: Ambiguity Aversion, Dynamic Strategic Trading, Price Drift, Under-reaction

JEL Classification: G14, D80

Suggested Citation

Gong, Aibo and Ke, Shaowei and Qiu, Yawen and Shen, Rui, Robust Pricing under Strategic Trading (January 30, 2021). Journal of Economic Theory, Forthcoming, Available at SSRN: https://ssrn.com/abstract=3587727 or http://dx.doi.org/10.2139/ssrn.3587727

Aibo Gong

University of Michigan, Ann Arbor ( email )

2350 Hayward Street
Ann Arbor, MI 48109
United States

Shaowei Ke

University of Michigan at Ann Arbor - Department of Economics ( email )

611 Tappan Street
Ann Arbor, MI 48109-1220
United States

Yawen Qiu

Shanghai University of Economics and Finance ( email )

Rui Shen (Contact Author)

The Chinese University of Hong Kong, Shenzhen - School of Management and Economics ( email )

2001 Longxiang Road, Longgang District
Shenzhen, 518172
China

Shenzhen Finance Institute ( email )

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