An important question facing experimental economists is whether behavior inside the laboratory is a good indicator of behavior outside the laboratory. We begin with a model that assumes the choices that individuals make depend not just on financial implications, but also on the nature and extent of scrutiny by others, the particular context in which a decision is embedded, and the manner in which participants are selected. To the extent that lab and naturally-occurring environments systematically differ on any of these dimensions, the results obtained inside and outside the lab need not correspond. Based on theory and empirical evidence, we argue that lab experiments are a useful tool for generating qualitative insights, but are not well-suited for obtaining deep structural parameter estimates. We conclude that the sharp dichotomy sometimes drawn between lab experiments and data generated in natural settings is a false one. Each approach has strengths and weaknesses, and a combination of the two is likely to provide deeper insights than either in isolation.

We study herd behavior in a laboratory financial market with financial market professionals. We compare two treatments: one in which the price adjusts to the order flow in such a way that herding should never occur, and one in which the presence of event uncertainty makes herding possible. In the first treatment, traders seldom herd, in accordance with both the theory and previous experimental evidence on student subjects. A proportion of traders, however, engage in contrarianism, something not accounted for by the theory. In the second treatment, on the one hand, the proportion of herding decisions increases, but not as much as the theory would suggest; on the other hand, contrarianism disappears altogether. In both treatments, in contrast with what theory predicts, subjects sometimes prefer to abstain from trading, which affects negatively the process of price discovery.

This paper presents an online-experiment on overconfidence in the context of financial markets. Our subject pool consists of institutional investors, investment advisors and individual investors, all of them being registered users of a large online platform for market sentiment data. Due to their registration, several socioeconomic characteristics of participants can be controlled for in our analysis. It turns out that there are stable differences in overconfidence between the three investor groups. Moreover, investment experience and age have a significant impact on the degree of overconfidence which goes surprisingly in opposite direction. We argue that these results have important implications for studies analyzing the impact of experience on behavior in (financial) markets.

Tendencies of individuals to behave like those around them leads to cascading phenomenon, in which an idea or behavior spreads quickly throughout a social network, being adopted by nearly all individuals in an area. We crawl the Twitter social graph and monitor users ' posts, or 'tweets, ' for several weeks, monitoring the spread of keywords, or 'hashtags, ' along the graph structure. We simulate cascades on the Twitter graph using previous models and compare the results to the real cascade data. Additionally, we perform sentiment analysis on the tweets, determining whether a user has a positive or negative position on a hashtag. Finally, we isolate clusters in the network, examining the variance in sentiment within a cluster, observing the distribution of group sentiment As social creatures, human beings base their decisions not only on their personal goals and motives, but also largely take into account the decisions of those around them. The tendency of individuals to base their decisions on the decisions of others in a group leads to a cascading phenomenon [Bikchandani 1998], in which an idea

Most real world situations that are susceptible to herding are also characterized by direct payoff externalities. Yet, the bulk of the theoretical and experimental literature on herding has focused on pure informational externalities. In this paper we experimentally investigate the effects of several different forms of payoff externalities (e.g., network effects, first-mover advantage, etc.) in a standard information-based herding model. Our results are based on an internet experiment with more than 6000 subjects, including a subsample of 267 consultants from an international consulting firm. We also replicate and review earlier cascade experiments. Finally, we study reputation effects (i.e., the influence of success models) in the context of herding.

We undertook the first market trading experiments that allowed heterogeneously informed subjects to trade in endogenous time, collecting over 2000 observed trades. Subjects ’ decisions were generally in line with the predictions of exogenous-time financial herding theory when that theory is adjusted to allow rational informational herding and contrarianism. While herding and contrarianism did not arise as frequently as predicted by theory, such behavior occurs in a significantly more pronounced manner than in comparable studies with exogenous timing. Types with extreme information traded earliest. Of those with more moderate information, those with signals conducive to contrarianism traded earlier than those with information conducive to herding. JEL Classification: C91, D82, G14.