The Impact of Salience on Investor Behavior: Evidence from a Natural Experiment

• DOI: http://doi.org/10.1111/jofi.12851
• Author: CARY FRYDMAN,BAOLIAN WANG
• Date: 01 February 2020
• Published date: 01 February 2020

THE JOURNAL OF FINANCE •VOL. LXXV, NO. 1 •FEBRUARY 2020

The Impact of Salience on Investor Behavior:

Evidence from a Natural Experiment

CARY FRYDMAN and BAOLIAN WANG∗

ABSTRACT

Wetest 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 em-

ploy 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 trad-

ing pattern, the “rank effect,” explains heterogeneity in the change in the disposition

effect.

IN MOST MODELS OF INVESTOR behavior, the manner in which information is

displayed has little impact on portfolio choice. Yet, evidence from several

laboratory experiments indicates that information display can substantially

affect investor behavior. For example, manipulating the presentation of an

asset’s past performance can affect subjects’ risk-taking (Gneezy and Potters

(1997), Thaler et al. (1997)), mutual fund choice (Choi, Madrian, and Laibson

(2010)), and willingness to sell losing stocks (Frydman and Rangel (2014)).

Outside the laboratory, it is less clear whether a change in information

display would also have a large effect on trading decisions. One recent exper-

iment finds that when subjects make decisions over the course of a calendar

year—compared to a single laboratory session—the effect of information

display on portfolio risk-taking largely disappears (Beshears et al. (2017)).

This result highlights the importance of the experimental setting. Thus, there

∗Cary Frydman is at the Department of Finance and Business Economics, USC Marshall School

of Business. Baolian Wang is at Warrington College of Business, University of Florida. We are

thankful for comments from Kenneth Ahern; Nicholas Barberis; Itzhak Ben-David; Justin Birru;

Bing Han; Alex Imas; Danling Jiang; An Li; Juhani Linnainmaa; Mark Seasholes; and seminar

participants from Ohio State University, University of Southern California, Nankai University,

Renmin University in China, Peking University,University of Pennsylvania, the Cognition and De-

cision Laboratory at Columbia University,the 2016 Caltech Junior Behavioral Finance conference,

the 2017 Conference on China’s Financial Markets and Growth Rebalancing, the 2017 Interdisci-

plinary Symposium on Decision Neuroscience, the 2017 Miami Behavioral Finance Conference, the

2018 CFP Academic Research Colloquium for Financial Planning, and the 2018 China Financial

Research Conference. Frydman acknowledges financial support from NSF grant #1749824. The

authors have read The Journal of Finance’s disclosure policy and have no conflicts of interest to

disclose.

DOI: 10.1111/jofi.12851

C2019 the American Finance Association

229

230 The Journal of Finance R

is a need for additional empirical evidence from a higher-stakes and more

natural trading environment.

In this paper, we use a combination of microdata from a Chinese brokerage

house and a natural experiment to estimate the causal effect of a change in

information display on individual investor trading decisions. Specifically, we

obtain data from a brokerage house that increased the salience of a stock’s

capital gain by making it more visually prominent on the investor’s online

trading screen (Figure 1). To assess the impact on investor behavior, we

measure the disposition effect, which is the greater tendency to sell stocks

with capital gains compared to capital losses (Shefrin and Statman (1985),

Odean (1998)).1We hypothesize that increasing the salience of a stock’s capital

gain will increase the disposition effect.

In general, there are three main challenges in estimating the causal

effect of information display on investor behavior in the field. First, in many

circumstances, the display of information is correlated with the information

itself. For example, newspapers and online brokerages often prominently

display a list of daily winner and loser stocks, which confounds the content

of information (the daily return) with the salience of information (its display

on the list) (though see Kaniel and Parham (2017) and Wang (2019)). Here,

we use a unique shock to the display of information about a stock’s capital

gain that is uncorrelated with the capital gain itself. Because information on

the capital gain was available to investors before the change in information

display, this did not affect the information content of the capital gain, but

rather made it more salient and easier for the investor to process. We therefore

refer to the change as a “salience shock” rather than an information shock.

Second, estimating the effect on the average investor’s behavior can mask

important heterogeneity that makes the size of the effect hard to interpret.

In particular, investors who hold many stocks in their portfolio may exhibit

greater changes in behavior because more information becomes prominently

displayed on their trading screen. This could lead the average effect to be

overestimated if larger investors contribute more observations to the analysis

than smaller investors. Our data provide information on trades at the account

level, and thus we can estimate the effect at the individual level (Taubinsky

and Rees-Jones (2018)).

The third challenge is that the change in display may coincide with a

distinct but unobserved shock that also affects trading behavior. The salience

shock that we study generated a natural experiment that provides a control

group, which we use to control for common time-series variation in the

disposition effect. In particular, our data provide information on the method of

trade—internet, phone, or in-person (Barber and Odean (2002)). Because the

change in information display occurred online, the salience shock should not

1The disposition effect has been documented among both individual and professional investors.

It is an extremely robust effect that has been found among a wide variety of asset classes and

international markets. For a comprehensive review of the disposition effect, see Kaustia (2010)

and Barber and Odean (2013).

Impact of Salience on Investor Behavior 231

Panel A: Before October 2004

Panel B: After October 2004

3073.44 -11.02 -0.36% 1270 10694.5 -89.84 -0.83%1934 6908.67 -64.56 -0.93%817.3 3312.84 -5.76 -0.17%701.4 2171.64 -21.62 -0.99%557.7

3073.44 -11.02 -0.36% 1270 10694.5 -89.84 -0.83%1934 6908.67 -64.56 -0.93% 817.3 3312.84 -5.76 -0.17%701.4 2171.64 -21.62 -0.99% 557.7

StockID Name Shares SharesS BrkEvn PrchPrice Price MktValue PaperGain RlzdGain TotalGain FrznShr TraderID Non-tradable

StockID Name Shares SharesS Price MktValue FrznShrs TraderID Non-tradable

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Figure 1. Change in information display. Panel A shows an example of the trading platform screen prior to the salience shock in October 2004.

Panel B shows an example of the trading platform screen after the salience shock, when five variables were added: (I) break-even price (column

#5), (II) weighted-average purchase price (column #6), (III) paper gain/loss (column #9), (IV) realized gain/loss (column #10), and (V) total gain/loss

(column #11). After the salience shock, the font color for each stock was a function of whether the stock was trading at a gain (red) or at a loss (blue).

The English translations in both panels and the red rectangles highlighting the added variables in the bottom panel are for display purposes only

and were not presented to investors.