The changing landscape of behavioral finance

• Date: 01 January 2019
• Author: Alok Kumar
• DOI: http://doi.org/10.1002/rfe.1058
• Published date: 01 January 2019

Rev Financ Econ. 2019;37:3–5. wileyonlinelibrary.com/journal/rfe

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3

© 2019 University of New Orleans

Received: 26 December 2018

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Revised: 10 January 2019

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Accepted: 11 January 2019

DOI: 10.1002/rfe.1058

SPECIAL ISSUE ARTICLE

The changing landscape of behavioral finance

AlokKumar

Department of Finance,Miami Business School, Coral Gables, Florida

Correspondence

Alok Kumar, Department of Finance, Miami Business School, Coral Gables, FL.

Email: akumar@miami.edu

The field of behavioral finance is continually evolving and the range of topics considered “behavioral” is expanding rapidly.

The earliest topics in behavioral finance focused primarily on suboptimal investor behavior (i.e., behavioral biases). For exam-

ple, why do investors fail to follow one of the fundamental prescriptions of portfolio theory and hold under- diversified portfo-

lios? Why do they hold on to losing positions longer than they hold on to a winning position? Why do investors trade actively

when finance theory recommends a “buy and hold” strategy?

Furthermore, several previous studies attempted to quantify the economic costs of these suboptimal decisions, either directly

or indirectly. If the economic costs are high, then it is reasonable to expect that investors would eventually learn from their

mistakes and their behavioral tendencies should weaken over time. But, does this actually happen or is learning difficult for

investors because the feedback is noisy?

While these questions are still interesting and topics of recent research in behavioral finance, several new areas of research

have emerged. In particular, the domain of biases has expanded from psychological to social. How these biases vary across dif-

ferent demographic and cultural groups is also of interest. In particular, are biases concentrated among less sophisticated market

participants such as retail investors or do sophisticated market participants such as institutional investors, equity analysts, and

CEOs exhibit these types of biases too? Furthermore, do individuals who grow up in a collectivist culture or a country where

legal and ethical boundaries are not very well defined exhibit greater deviations from optimal behavior?

More recently, the emerging field of neuroscience has provided tools that allow us to “see” inside the human brain as we

make risky decisions. These “peeks” into the human brain allow us to better understand the determinants of suboptimal investor

behavior. In particular, research has examined whether individuals behave suboptimally because they perceive the information

differently or because they perceive the same information but process them differently. And to what extent are differences in

investor behavior determined by genetic factors and what part of it is determined by experience and environmental factors?

The set of papers in this special issue represents the changing landscape of behavioral finance. Some of the papers present

novel evidence on old research questions while other papers extend the boundaries of behavioral finance. Another recurring

theme in these papers is the dynamic interaction between informational and behavioral factors. In many economic settings, in-

dividuals may appear biased not because of their lack of financial sophistication but rather due to high informational gathering

costs. The high information gathering costs may make them appear biased.

Among the set of papers that investigate traditional topics, Chen and Sabherwal (2019) study uses a novel setting of options

trading to provide additional support for the well- known investor overconfidence bias. Following a period of good performance,

option traders become overconfident about their investment abilities and trade more aggressively. This relation is stronger

among firms that are harder- to- value as they have no analyst coverage. Furthermore, they show that overconfidence- induced

trading is more widespread in the options market as compared to the equity market.

In a similar manner, Fang and Zhu (2019) provide supporting evidence for a behavioral bias induced by name complexity.

Using data from the Chinese stock market, they show that cognitive fluency and name recognition associated with complexity

of stock tickers affect investor behavior and asset prices. In particular, firms with less complex stock tickers attract greater

investor attention, are easier to remember, and are evaluated more positively. Consequently, they have wider investor base, are

traded more frequently, and exhibit better overall performance.

While investors could appear to exhibit suboptimal behavior due to their behavioral biases, it is also possible that these biases

are manifestations of their informational gathering activities. If regulation affects the informational environment and investors’