Earnings forecasting in a global stock selection model and efficient portfolio construction and management

Abstract

Stock selection models often use analysts’ expectations, momentum, and fundamental data. We find support for composite modeling using these sources of data for global stocks during the period 1997–2011. We also find evidence to support the use of SunGard APT and Axioma multi-factor models for portfolio construction and risk control. Three levels of testing for stock selection and portfolio construction models are developed and estimated. We create portfolios for January 1997–December 2011. We report three conclusions: (1) analysts’ forecast information was rewarded by the global market between January 1997 and December 2011; (2) analysts’ forecasts can be combined with reported fundamental data, such as earnings, book value, cash flow and sales, and also with momentum, in a stock selection model for identifying mispriced securities; and (3) the portfolio returns of the multi-factor risk-controlled portfolios allow us to reject the null hypothesis for the data mining corrections test. The earnings forecasting variable dominates our composite model in terms of its impact on stock selection.