We develop a microstructure model that, in contrast to previous models, allows one to estimate the frequency and quality of private information. In addition, the model produces stationary asset price and trading volume series. We find evidence that information arrives frequently within a day and...

We develop a method for measuring the foresight agents have. We first dichotomize an agent's information at current date t into knowledge up to date t + f and expectations after t + f. We then form a residual-based test statistic that allows us to compare prediction errors for econometric models...

For conditional heteroskedasticity models, the authors study the identification condition that is required for consistency of a non-Gaussian quasi-maximum-likelihood estimator. They show that, if the conditional mean is zero or if a symmetry condition is satisfied, then the identification...

We develop a theoretical model that replicates three observed phenomena in securities markets: serial correlation in trades; serial correlation in squared price changes (conditional heteroskedasticity); and more persistent serial correlation in trades than in squared price changes. In the model...

We study the effect of income uncertainty on consumption in a model that includes precautionary saving. In contrast to previous studies, we focus on time-series variation in income uncertainty. Our time-series measure of income uncertainty is constructed from a panel of forecasts. We find...