The Probability of Informed Trading (PIN) is a widely used indicator of information asymmetry risk in the trading of securities. Its estimation using maximum likelihood algorithms has been shown to be problematic, resulting in biased or unavailable estimates, especially in the case of liquid and frequently traded assets. We provide an alternative approach to estimating PIN by means of a Bayesian method that addresses some of the shortcomings in the existing estimation strategies. The method leads to a natural quantification of the uncertainty of PIN estimates, which may prove helpful in their use and interpretation. We also provide an easy to use toolbox for estimating PIN.

A new type of momentum based on the signs of past returns is introduced. This momentum is driven primarily by sign dependence, which is positively related to average return and negatively related to return volatility. An empirical application using a universe of commodity and financial futures offers supporting evidence for the existence of such momentum. Investment strategies based on return signal momentum result in higher returns and Sharpe ratios and lower drawdown relative to time series momentum and other benchmark strategies. Overall, return signal momentum can benefit investors as an effective strategy for speculation and hedging.

In this paper we quantify the differences between market and regulatory assessments of bank portfolio risk, and thereby demonstrate that larger differences significantly reduce corporate lending rates. Specifically, to entice borrowers, banks reduce spreads by approximately 4.3% following a one standard deviation increase in our measure for bank asset-risk differences. This is equivalent to an interest income loss of USD 2.03 million on a loan of average size and duration. The separate effects of market and regulatory risk are much less potent. Our study reveals a disciplinary-competition effect in favor of corporate borrowers when there is information asymmetry between investors and bank regulators.