Proper Event Study Analysis in Securities Litigation

Article excerpt

I. INTRODUCTION

For over two decades, event studies have been prominently used as a valuation technique in various litigation matters including securities litigation. An event study is an empirical technique that measures the effect of new information on the market prices of a company's publicly traded securities. In securities litigation, event study methodology has been widely used in fraud-on-the-market cases as economic evidence of materiality, loss causation, and artificial inflation.

The focus of event studies in securities class actions has been predominantly on disclosures that correct prior misrepresentations. It has become commonplace in securities class actions, however, for defendants' experts to focus event study analyses on days in which the alleged misleading disclosures were made (as opposed to corrective disclosure) for purposes of materiality and loss causation. These event study analyses are generally performed for dates identified in a complaint for which plaintiffs allege that defendants have made false and misleading statements. More often than not, however, such uses of event studies are plainly incorrect and at odds with accepted economic literature regarding the appropriate and proper use of event studies. That is, these event studies of days that misleading information is disclosed are generally not conducted with the level of intellectual rigor that would be expected of a professional economist and the conclusions from such analyses can be improper and erroneous.

Many of the disclosures in a complaint identify dates in which defendants omitted material information. But, an event study is designed to quantify the effect of disclosed information, not undisclosed information. Such use of an event study is completely improper.

Complaints by their nature contain every instance in which defendants reiterate a misstated fact. Consequently, it is improper and a misapplication of event study methodology to draw any conclusion from the lack of statistically significant price reactions on days that merely reiterate the first instance of a misrepresentation. Moreover, a misstatement that confirms prior market expectations would not be expected to result in a price movement. Failure to account for these factors in an event study is incorrect and can result in serious errors and wrong conclusions. The failure of an economist to have engaged in an event study and formulated conclusions about loss causation and materiality without any consideration as to whether the events being studied contain new information versus events that merely repeat prior disclosures is a serious methodological error in event study analyses and should fail under Daubert.1

II. EVENT STUDY METHODOLOGY

As a general proposition, modern finance theory holds that the market price of a stock reflects the expected discounted value of future cash flows to equity holders.2 Thus, new information that causes the market to significantly alter its expectation of future cash flows will cause a prompt repricing of the stock to reflect the new expectations.3 Since the publication in 1969 of a classic paper by Fama, Fisher, Jensen, and Roll,4 financial economists have used event study methodology to measure the effect on market prices of new information relevant to a company's equity valuation. New information may include earnings reports, dividend changes, stock splits, company press releases on current or projected revenues, regulatory rulings, acquisition bids, asset sales, tax legislation, or any other information that is relevant to investors' assessments of future cash flows.5

Event study analysis compares the day-to-day percentage change in the market price of a company's common stock (known as a "return.) to the return predicted by a market model that uses a market index, such as the S&P 500 Index or the NASDAQ Composite Index, and possibly an industry index.6 The market model describes the normal relation between the return on the company's common stock and the return on the market and industry indexes. …