An empirical investigation of trading on asymmetric information and heterogeneous prior beliefs
ABSTRACT The purpose of this study is to identify and analyze inter-temporal trading patterns attributable to informed trading. Recent theoretical models posit that heterogeneous prior beliefs provide a source of trading volume in addition to the commonly accepted trading motives of liquidity and asymmetric information. After separating informed from uninformed trading using the estimation procedure of Easley et al. [Journal of Finance 51 (1996) 1405], we test for the presence of trading on heterogeneous beliefs as opposed to asymmetric information. The empirical findings confirm the existence of trading on heterogeneous prior beliefs and generally support the inter-temporal patterns proposed by Wang [Journal of Financial Markets 1 (1998) 321].
Article: Market Efficiencies and Market Risks[show abstract] [hide abstract]
ABSTRACT: Numerous papers constructed or simulated financial markets at an agent level, aiming to explain the non-stationarity of price processes. All such papers agree that the heterogeneity of agents and of pricing models creates a dynamics in terms of pricing models used that explains not only the non-stationarity of price processes, but also stylised facts such as bubbles and fat tails. However, all these results issue from very specific parametric set-ups, and even if multiple approaches confirm it, there is no proof of the aforementioned results outside of such specifications. By modeling agents as black boxes that receive information that they transform into an output information, information according to which they then act upon the financial market, we show that the diversity of agents is directly associated to the resulting quality of the information efficiency of the market : homogenous agents lead to good information propagation but poor information aggregation by the price, while heterogenous agents lead to good information aggregation but poor information propagation. This difference in quality of efficiency explains, outside of any parametric model, the dynamics of the number of different pricing models used within artificial stock markets.