Making financial decisions under risk and uncertainty has become part of everyday life. Traditional finance explores the objective side of risk, analysing the decisions made by perfectly rational individuals in efficient market conditions. Behavioural finance seeks to connect theory with...

Human judgments are systematically affected by various biases and distortions. The main goal of our study is to analyze the effects of five well-documented behavioral biases—namely, the disposition effect, herd behavior, availability heuristic, gambler’s fallacy and hot hand fallacy—on the...

This paper provides evidence that the 52-week high serves as a psychological barrier, inducing expectational errors and underreaction to news. Two clear predictions emerge and are confirmed in the data. First, nearness to a 52-week high induces expectational errors; evidence from earnings...

We use novel data on individual activity in a sports betting market to study the effect of past performance sequences on individual behavior in a real market. The revelation of fundamental values in this market enables us to disentangle whether behavior is caused by sentiment or by superior...

This survey introduces and reviews the field of behavioral finance. It outlines the traditional finance approach, which builds upon rational acting investors, its assumptions, and its shortcomings. Moreover, it surveys the main findings from psychology and sociology that contrast with this...

Finance is in the midst of a paradigm shift, from a neoclassical based framework to a psychologically based framework. Behavioral finance is the application of psychology to financial decision making and financial markets. Behavioralizing finance is the process of replacing neoclassical...

Human judgments are systematically affected by various biases and distortions. The main goal of our study is to analyze the effects of five well-documented behavioral biases — namely, the disposition effect, herd behavior, availability heuristic, gambler's fallacy and hot hand fallacy — on...

We examine how the return predictability of deep learning models varies with stocks’ vulnerability to investors’ behavioral biases. Using an extensive list of anomaly variables, we find that the long-short strategy based on deep learning signals generates greater returns for stocks that are...

A pervasive feature in the finance industry is relative performance, which can include extrinsic (money), intrinsic (self-image), and reputational (status) motives. In this paper, we model a portfolio decision with two assets and investigate how reputational motives (i.e., the public...

A pervasive feature in the finance industry is relative performance, which can include extrinsic (money), intrinsic (self-image), and reputational (status) motives. In this paper, we model a portfolio decision with two assets and investigate how reputational motives (i.e., the public...