Abstract

One of the thorniest problems in investment research is to integrate academic research into a viable investment product. Research techniques that have shown promise in academic studies do not translate well into financial products. The concern of this paper is the academic research that indicates that there is usable information in earnings announcements. A number of articles have explored analysts' earnings estimates, analysts' forecasting ability and the reaction of stock prices to earnings announcements. One research areas is the group of stocks whose earnings announcements constitute positive “earnings surprise” given a consensus of analysts' expected earnings. The consensus derives from a twenty quarter, seasonally adjusted earnings trend and the median analysts' forecasts from I/B/E/S, Inc. The quantitative research department of a major securities firm has identified and published a list of “earnings surprise” stocks for the past 9 years. The major issue addressed in this paper is whether the information contained in earnings announcements is useful as a security screening technique for a portfolio selection process, i.e., Do earnings announcements add value to the performance of a portfolio? Previous studies focused on individual securities. There have been no attempts at integrating earnings surprise into a systematic portfolio approach. The study conducts a comprehensive backtest of whether there is new investment information in earnings surprise data when used with a portfolio selection algorithm. Since the focus is on a usable financial product, this study uses economic return performance to evaluate its results rather than the more commonly used statistical methodology. The results indicate that using earnings surprise information in a periodic revision of a portfolio does not add value. Any value added derives from the portfolio selection algorithm not from the fact that the stocks in the analysis are “earnings surprise” stocks. In addition, the earnings surprise stocks are a source of increased volatility when used in 15–30 asset portfolios.

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