We develop a volatility decomposition derived from flexible local projections to quantify the relative contributions of expected discount rates and cash flows to the variation of dividend yields. Local projections enable the incorporation of large information sets, the use of monthly data along...

We propose the Volume Coefficient of Variation (VCV), the ratio of the standard deviation to the mean of trading volume, as a new and easily computable measure of information asymmetry in security markets. We use a simple microstructure model to demonstrate that VCV is strictly increasing in the...

We propose the Volume Coefficient of Variation (VCV), the ratio of the standard deviation to the mean of trading volume, as a new and easily computable measure of information asymmetry in security markets. We use a microstructure model to demonstrate that VCV is strictly increasing in the...

We propose the Volume Coefficient of Variation (VCV) as a new and simple measure of information asymmetry in security markets. We use a microstructure model to demonstrate that VCV is strictly increasing in the proportion of informed trade. Empirically, we obtain VCV from daily observations of...

Misspecification of agents' information sets or expectation formation mechanisms maylead to noncausal autoregressive representations of asset prices. Annual US stock prices are found to be noncausal, implying that agents' expectations are not revealed to an outside observer such as an...

Stock prices often diverge from measures of fundamental value, which simple present value models fail to explain. This paper tries to find causes for these long-run price movements and their persistence by estimating a STAR model for the price-earnings ratio of the S&P500 index for 1961Q1 -...

This paper applies a heterogeneous agent asset pricing model, featuring fundamentalists and chartists, to the price-dividend and price-earnings ratios of the S&P500 index. Agents update their beliefs according to macroeconomic information, as an alternative to evolutionary dynamics. For...