In this article we examine the interaction of brokerage search with the Bayesian learning behavior of competitive dealers under asymmetric information. We particularly focus on the effects of price search and discretionary trading on the performance of a dealer market. A search process is...

We use empirical models to examine the predictive ability of dividend and earnings yields for long-term stock returns. Results show that dividend and earnings yields share a similar predictive power for future stock returns and growth. We find that the predictive power of dividend yields...

In this paper, we examine the relationship between volume and return volatility using the transaction data. We introduce transaction and volume imbalance measures to capture the information content of trades. These two information measures are shown to have a strong explanatory power for return...

In this paper, we apply the neural network method to small business lending decisions. We use the neural network to classify the loan applications into the groups of acceptance or rejection, and compare the model results with the actual decisions made by loan officers. Data were collected from a...

This paper examines the relationship among daily information flow, return volatility, and bid-ask spreads based on the framework of the mixture of distribution hypothesis (MDH). The MDH model is modified to permit separate effects of informed and liquidity trading volume on return volatility....