We introduce human traders into an agent based financial market simulation prone to bubbles and crashes. We find that human traders earn lower profits overall than do the simulated agents (“robots”) but earn higher profits in the most crash-intensive periods. Inexperienced human traders tend to destabilize the smaller (10 trader) markets, but have little impact on bubbles and crashes in larger ...

This paper offers an explanation for stock market crashes which focuses on the role of rational but uninformed traders. We show that uninformed traders can precipitate a price crash because as prices decline, they surmise that informed traders received negative information, which leads them to reduce their demand for assets and drive the price of stocks even lower. The model yields several impl...

This paper tests whether traders react more strongly as a series of similar earnings surprises continues, as predicted by several important behavioral finance models. We compile measures of buying and selling from NYSE TAQ data for a large ten-year sample. Results show strong, consistent, evidence that small traders exhibit an increasing reaction – with significant increases in reaction strengt...

This Letter investigates the stochastic dynamics of a simplified agent-based microscopic model describing stock market evolution. Our mathematical model includes a stochastic market and a sealed-bid double auction. The dynamics of the model Ž . are determined by the game of two types of traders: i ‘intelligent’ traders whose strategy is based on nonlinear technical 1 Ž . data analysis and ii ‘r...

Recent years have seen extensive investigation of the information aggregation properties of markets. However, relatively little is known about conditions under which a market will aggregate the private information of rational risk averse traders who optimize their portfolios over time; in particular, what features of a market encourage traders to ultimately reveal their private information thro...

Prediction markets have been shown to be a useful tool for forecasting the outcome of future events by aggregating public opinion about the event’s outcome. In this paper, we investigate an important aspect of prediction markets the effect of different information related parameters on the behavior of the traders in the market. We have developed a multi-agent based system that incorporates diff...

The ease of Internet stock trading has lured relatively inexperienced investors into the financial markets. We study the consequences of the influx of these uninformed traders with a dynamic equilibrium framework. Our results show that these strategic uninformed online traders who adopt feedback strategies cannot outperform those who do not follow feedback strategies and that feedback trading c...

In this chapter we survey asset pricing in dynamic economies with heterogeneous, rational traders. By ‘rational’ we mean traders whose decisions can be described by preference maximization, where preferences are restricted to those which have an subjective expected utility (SEU) representation. By ’heterogeneous” we mean SEU traders with different and distinct payoff functions, discount factors...

Using a simultaneous-move herding model of rational traders who infer other traders’ private information on the value of an asset by observing their aggregate actions, this study seeks to explain the emergence of fat-tailed distributions of transaction volumes and asset returns in financial markets. Without making any parametric assumptions on private information, we analytically show that trad...

People often demand a greater price when selling goods that they own than they would pay to purchase the same goods-a well-known economic bias called the endowment effect. The endowment effect has been found to be muted among experienced traders, but little is known about how trading experience reduces the endowment effect. We show that when selling, experienced traders exhibit lower right ante...