Fraud by Hindsight
G. Mitu Gulati
Duke University School of Law
Jeffrey J. Rachlinski
Cornell Law School
Donald C. Langevoort
Georgetown University Law Center
Georgetown Public Law Research Paper No. 442820; Georgetown Law and Econ. Research Paper No. 442820; Cornell Legal Studies Research Paper No. 05-007
In securities-fraud cases, courts routinely admonish plaintiffs that they are not permitted to rely on allegations of "fraud by hindsight." In effect, courts disfavor plaintiffs' use of evidence of bad outcomes to support claims of securities fraud. Disfavoring hindsight evidence appears to tap into a well known, well-understood, and intuitively accessible problem of human judgment of "20/20 hindsight." Events come to seem predictable after unfolding, and hence, bad outcomes must have been predicted by people in a position to make forecasts. Psychologists call this phenomenon the hindsight bias. The popularity of this doctrine among judges deciding securities cases suggests that judges actively seek techniques that enable them to correct for psychological biases that might otherwise affect their decision-making.
This paper assesses the hypothesis that judges have adopted the "fraud-by-hindsight" doctrine so as to avoid erroneous judgment infected with the hindsight bias. We find that although judges have identified a real problem in human judgment, they are not developing a doctrine to remedy the influence of hindsight on judgment. Rather, they are using this problem of human judgment as the justification for expanding their authority to manage the complex, high-stakes securities cases that come before them. The result provides judges with the greater case-management authority they seek, but leaves the securities litigation without a meaningful doctrine to ameliorate the influence of hindsight on judgment.
Number of Pages in PDF File: 61
JEL Classification: K0, K2
Date posted: February 22, 2005
© 2015 Social Science Electronic Publishing, Inc. All Rights Reserved.
This page was processed by apollo7 in 0.266 seconds