An exploration of commonly observed stylized facts with data from experimental asset markets

We analyze data from experimental asset markets with pooled linear regression models to shed some light on the emergence of fat tails and volatility clustering in return distributions. Our data suggest that the arrival of new information is the most important cause for both stylized facts. After new information arrives we see spikes in volatility as this information is digested in the market. We also find that uninformed traders contribute significantly more to fat tails than do informed traders and that the heterogeneity in fundamental information leads to larger returns.