Which equity factors have high and low expected returns? In their February 2017 paper entitled "Forecasting Factor and Smart Beta Returns (Hint: History Is Worse than Useless)", Robert Arnott, Noah Beck and Vitali Kalesnik evaluate attractiveness of eight widely used stock factors. They measure alpha for each factor conventionally via a portfolio that is long (short) stocks with factor values having high (low) expected returns, reformed systematically. They compare factor alpha forecasting abilities of six models:
- Factor return for the last five years.
- Past return over the very long term (multiple decades), a conventionally used assumption.
- Simple relative valuation (average valuation of long-side stocks divided by average valuation of short-side stocks), comparing current level to its past average.
- Relative valuation with shrunk parameters to moderate forecasts by dampening overfitting to past data.
- Relative valuation with shrunk parameters and variance reduction, further moderating Model 4 by halving its outputs.
- Relative valuation with look-ahead full-sample calibration to assess limits of predictability.
They employ simple benchmark forecasts of zero factor alphas. Using 24 years of specified stock data (January 1967 - December 1990) for model calibrations, about 20 years of data (January 1991 - October 2011) to generate forecasts and the balance of data (through December 2016) to complete forecast accuracy measurements, they find that:
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