Estimating Financial Fraud Damages with Response Coefficients

Abstract

Shareholder class action litigation most often deals with allegations that defendants made misrepresentations and/or omissions that caused the stock price to be higher than it otherwise would have been. We show how regression analysis of the response of share prices and investor expectations to news can be exploited in estimating a priori what would have been the effect of the truth had it been told at the time it was covered up. Mindful that there will be statistical error associated with the estimate of such coefficients, their application will nonetheless usually be an improvement over an unadjusted event study under any of the following, frequently encountered, circumstances: (1) it is necessary to isolate the impact of a revelation of the relevant truth on a stock price in the presence of confounding, material news; (2) inflation per share builds up in magnitude over time in response to multiple, sequential misrepresentations; and, (3), it would be useful to put bounds on the proportionate liability of an auditor co-defendant.

Keywords: securities, fraud, damages, econometrics

JEL Classification: G14, K22