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ABSTRACT We test whether the display of information causally affects investor behavior in a high‐stakes trading environment. Using investor‐level brokerage data from China and a natural experiment, we estimate the impact of a shock that increased the salience of a stock's purchase price but did not change the investor's information set. We employ a difference‐in‐differences approach and find that the salience shock causally increased the disposition effect by 17%. We use microdata to document substantial heterogeneity across investors in the treatment effect. A previously documented trading pattern, the “rank effect,” explains heterogeneity in the change in the disposition effect.
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Learning about latent dynamic trading demand $$^*$$
Abstract We present an equilibrium model of dynamic trading, learning, and pricing by strategic investors with trading targets and price impact. Since trading targets are private, investors filter the child order flow dynamically over time to estimate the latent underlying parent trading demand imbalance and to forecast its impact on subsequent price-pressure dynamics. We prove existence of an equilibrium and solve for equilibrium trading strategies and prices as the solution to a system of coupled ODEs. Trading strategies are combinations of trading towards investor targets, liquidity provision for other investors’ demands, and speculation based on learning about latent underlying trading-demand imbalances.
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- Award ID(s):
- 1812679
- PAR ID:
- 10371582
- Publisher / Repository:
- Springer Science + Business Media
- Date Published:
- Journal Name:
- Mathematics and Financial Economics
- Volume:
- 16
- Issue:
- 4
- ISSN:
- 1862-9679
- Page Range / eLocation ID:
- p. 615-658
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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