Abstract
This study revisits the predictability of individual stock returns by focusing on the investors' expectations of future stock prices. It hypothesizes that expectations cause events, and thus provide predictive power to forecast stock returns. Based on this premise, a model that relies on the investors' information set at time t and formulates expectational positions on stock prices for the near- and medium-term future periods is designed and estimated. The methodology is structural time series analysis under a statespace (time-varying) estimation process. The estimated model is put further to test to predict the one-, five-, and ten-days step-ahead ex-ante forecasts of a test sample of individual stocks in the Russel-1000 portfolio. The results are encouraging, particularly in terms of the Rasps that are computed.
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