Using an aggregate credit spread index, we find that it has substantial predictive power for corporate bond returns over short and long horizons. The return predictability is economically and statistically significant and robust to various controls. The credit spread index and its components...

In this paper we analyze the frequency and information content of small Nasdaq stock trades and their impacts on return volatility at the intraday interval. We employ an autoregressive conditional duration (ACD) model to estimate the intensity of the arrival and information content of trades by...

We examine the relative yields of Treasuries and municipals using a generalized model that includes liquidity as a state factor. Using a unique transaction dataset, we are able to estimate the liquidity risk of municipals and its effect on bond yields. We find that a substantial portion of the...

This paper examines short‐run information transmission between the U.S. and U.K. markets using the S&P 500 and FTSE 100 index futures. Ultrahighfrequency futures data are employed—which have a number of advantages over the low‐frequency spot data commonly used in previous studies—in...

Examines the impact of income tax rates on stock price and trading volume by analyzing the behavior of ex-dividend day premiums before and after TRA '86.

This article investigates the international information transmission between the U.S. and Greek stock markets using daily data from the Athens Stock Exchange (ASE) and the S&P 500 Index returns. It employs a bivariate exponential GARCH-t (EGARCH-t) that allows for both mean and variance...

This article investigates the international information transmission between the U.S. and Greek stock markets using daily data from the Athens Stock Exchange (ASE) and the S&P 500 Index returns. It employs a bivariate exponential GARCH-t (EGARCH-t) that allows for both mean and variance...

Using a comprehensive data set and an array of 27 macroeconomic, stock and bond predictors, we find that corporate bond returns are highly predictable based on an iterated combination model. The large set of predictors outperforms traditional predictors substantially, and predictability...