How do equity analysts' forecasts affect market returns?

Stock returns forecasting is one of the major tasks of financial analysts. Equity analysts’ forecasts, on the other hand, are one of the major sources of information used by less informed investors in their asset allocation decisions. Therefore, analysing which major factors affect the time series of stock returns could shed light on the price revelation process in capital markets. In this paper we propose a model aimed at predicting the stock market by combining both macroeconomic and microeconomic factors. We first develop a standard multivariate regression model with multiple macroeconomic factors as regressors. We then extend the model by explicitly including a measure for firm intrinsic equity value, based upon a proxy derived by weighted average stock market consensus forecasts by equity analysts. Third, we complete the model by imposing an ARMA specification for the error term, which enables identification of stock returns’ stationarity over time. The resulting model shows both a robust fitting capability when tested in the in-sample period and a good predictive capability when applied to an out-of-sample period of monthly Italian stock market returns. In particular, we employed specific estimation procedures based upon recently-developed statistics aimed at testing both for equal predictive ability and forecast encompassing. As a major empirical finding, our model suggests that the information conveyed by analysts’ forecasts is indeed a factor in determining future stock prices, even if there is the possibility that the information transferred could be biased.