The Effect of Analysts' Forecasts on Stock Market Returns: A Composite Multifactor Approach
50 Pages Posted: 3 Jun 2007 Last revised: 25 Mar 2009
Date Written: March 31, 2007
Stock returns forecasting is one of the major objectives of financial analysts. Equity Analysts' forecasts, on the other side, are one of the major sources of information used by less informed investors in their asset allocation decisions. Therefore, analysing which major drivers affect time series of stock returns could allow to shed light over the price revelation process in capital markets. In this paper we propose a model aimed at predicting stock market by combining both macroeconomic and microeconomic factors. We first develop a standard APT approach with multiple macroeconomic factors as regressors. We then integrate the model by explicitly including a metric for intrinsic equity value, basing upon a proxy derived by the weighted average of Stock Market Consensus Forecasts by equity analysts. Third, we complete the model by imposing an ARMA specification for the error term, which allows identifying stock returns' stationarity moving over time. The resulting model shows both a strong 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 for both factors' equal predicting power 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.
Keywords: asset pricing models, forecasting stock returns, APT, autoregressive models, cost of equity
JEL Classification: C32, C53, G12
Suggested Citation: Suggested Citation