Identifying the Value and Novelty of Financial Market Information
Paper Session
Saturday, Jan. 8, 2022 3:45 PM - 5:45 PM (EST)
- Chair: Philip Bond, University of Washington
Information Chasing versus Adverse Selection
Abstract
Contrary to the prediction of the classic adverse selection theory, more informed traders could receive better pricing relative to less informed traders in over-the-counter financial markets. Dealers actively chase informed orders to better position their future quotes and avoid winner's curse in subsequent trades. On a multi-dealer platform, dealers' incentive of information chasing exactly offsets their fear of adverse selection. In a more general setting, information chasing can dominate adverse selection when dealers face differentially informed speculators, while adverse selection dominates when dealers face differentially informed trades from a given speculator. These two seemingly contrasting predictions are supported by empirical evidence from the UK government bond market.Herding Behavior between Rating Agencies
Abstract
We investigate whether credit rating agencies systematically follow each other’s rating decisions. Therefore, we rely on the rotation of rating analysts within credit rating agencies and their impact on the rating. Using this institutional setup, we disentangle causal herding behavior from simple co-movement between credit rating agencies due to changes in firm fundamentals. Rating analysts have substantial influence on ratings, and we use their individual optimism or pessimism as instrumental variables to estimate causal effects of a rating change induced by an analyst on other agencies’ ratings. For our comprehensive sample of U.S. and European firms, rated between 1995 - 2016 by S&P, Moody’s and Fitch, we find significant herding behavior among credit rating agencies. The average herding behavior amounts to 0.4 notches for a one notch change at another credit rating agency, which is roughly half the size of the simple co-movement between credit rating agencies.Uncertainty about What's in the Price
Abstract
Speculators face uncertainty about which signals are already reflected in the price. We present a model in which speculators update the probability that their information is truly novel rather than stale based on recent price movements and market makers are aware that speculators may be trading on stale news. The model predicts an asymmetric price response to past price movements: after a recent price increase, buy volume—because it may result from speculators trading on stale news—has a lower price impact than sell volume (and vice versa after a recent price decrease). Using a comprehensive sample of order flow imbalances and price impact costs, we find strong support for this prediction.Discussant(s)
Maryam Farboodi
,
Massachusetts Institute of Technology
Jian Li
,
University of Chicago
Jordan Nickerson
,
Massachusetts Institute of Technology
Brandon Yueyang Han
,
University of Maryland
JEL Classifications
- G3 - Corporate Finance and Governance