Abstract
In the arena of securities fraud litigation, plaintiffs are responsible for calculating monetary damages due to alleged fraudulent behavior of defendants. Typically, a class period (a period of time ranging from a few months to a few years) is delineated; its starting point is the date of first documented fraud, its endpoint is the date on which the alleged fraud surfaces and investors respond accordingly, usually driving the defendants' stock prices to substantially lower values.

In order to estimate the amount of money lost by investors buying a stock that was allegedly overpriced, plaintiffs employ models that "simulate" damages, attempting to broadly recreate securities market behavior during the class period with respect to the stock in question. Efficacy of these models is a matter of constant debate, nonetheless their use proves exponentially cheaper than acquiring and digesting actual market data at the individual transaction level.

One such model is the Proportionate Decay Model, which takes inputs such as date, total shares available for trading, daily trading volume, stock price, and alleged true value of the stock price and returns an estimate of how many shares were affected during the class period and the resulting aggregate damages on these shares.

Under a contractual agreement with Berger & Montague, P.C., a Proportionate Decay Model program has been implemented in the Microsoft Excel Visual Basic environment. The model provides both single-trader and double-trader analysis in Excel spreadsheets containing summaries of the aggregate damages and graphs of the stock prices and trading volumes. The capability of the firm to compute aggregate damages in-house saves money, time, and allows for instantaneous revisions and recomputations without the added burden of reformatting the output each time.