We find a herding tendency among both amateur and professional investors and conclude that the propensity to herd is lower in the professionals. These results are obtained both when we consider herding into individual stocks and herding into stocks in general. Herding depends on the firm’s systematic risk and size, and the professionals are less sensitive to these variables. The differences between the amateurs and the professionals may be attributable to the latter’s superior financial training. Most of the results are consistent with the theory that herding is information-based. We also find that the herding behavior of the two groups is a persistent phenomenon, and that it is positively and significantly correlated with stock market returns’ volatility. Finally, herding, mainly by amateurs, causes market volatility in the Granger causality sense.

The recent credit crisis has highlighted the importance of market liquidity and its interaction with the price of credit risk. We investigate this interaction by relating the liquidity of corporate bonds to the basis between the credit default swap (CDS) spread of the issuer and the par-equivalent bond yield spread. The liquidity of a bond is measured using a recently developed measure called latent liquidity , which is defined as the weighted average turnover of funds holding the bond, where the weights are their fractional holdings of the bond. We find that bonds with higher latent liquidity are more expensive relative to their CDS contracts after controlling for other realized measures of liquidity. Analysis of interaction effects shows that highly illiquid bonds of firms with a greater degree of uncertainty are also expensive, consistent with limits to arbitrage between CDS and bond markets, due to the higher costs of “shorting” illiquid bonds. Additionally, we document the positive effects of liquidity in the CDS market on the CDS-bond basis. We also find that several firm- and bond-level variables related to credit risk affect the basis, indicating that the CDS spread does not fully capture the credit risk of the bond.

We present a new measure of liquidity known as “latent liquidity” and apply it to a unique corporate bond database. Latent liquidity is defined as the weighted average turnover of investors who hold a bond, in which the weights are the fractional investor holdings. It can be used to measure liquidity in markets with sparse transactions data. For bonds that trade frequently, our measure has predictive power for both transaction costs and the price impact of trading, over and above trading activity and bond-specific characteristics thought to be related to liquidity. Additionally, this measure exhibits relationships with bond characteristics similar to those of other trade-based measures.

In this paper, we model price dispersion effects in over-the-counter (OTC) markets to show that, in the presence of inventory risk for dealers and search costs for investors, traded prices may deviate from the expected market valuation of an asset. We interpret this deviation as a liquidity effect and develop a new liquidity measure quantifying the price dispersion in the context of the US corporate bond market. This market offers a unique opportunity to study liquidity effects since, from October 2004 onwards, all OTC transactions in this market have to be reported to a common database known as the Trade Reporting and Compliance Engine (TRACE). Furthermore, market-wide average price quotes are available from Markit Group Limited, a financial information provider. Thus, it is possible, for the first time, to directly observe deviations between transaction prices and the expected market valuation of securities. We quantify and analyze our new liquidity measure for this market and find significant price dispersion effects that cannot be simply captured by bid–ask spreads. We show that our new measure is indeed related to liquidity by regressing it on commonly-used liquidity proxies and find a strong relation between our proposed liquidity measure and bond characteristics, as well as trading activity variables. Furthermore, we evaluate the reliability of end-of-day marks that traders use to value their positions. Our evidence suggests that the price deviations from expected market valuations are significantly larger and more volatile than previously assumed. Overall, the results presented here improve our understanding of the drivers of liquidity and are important for many applications in OTC markets, in general.