Forecasting Beta: How Well Does the ‘five-year Rule of Thumb’ Do?

CAPM betas are widely used in practice. While they are estimated from historical data, they are generally applied to a future period. This is appropriate only if the betas are stable over time. However, there is widespread evidence that the CAPM betas vary considerably over time. This raises two questions: is the time-variation in the betas systematic and can systematic variation in the betas be used to generate forecasts which improve on the usual practice of using the betas estimated over the most recent five-year period (the " five-year rule of thumb ")? We address both of these questions. We estimate time-varying betas using both overlapping sub-periods (five-year rolling regressions) and non-overlapping two-year periods. We proceed to explain the time-variation in the betas using two different regression models which we subsequently use for forecasting. We find that, despite the forecasting equations having relatively high within-sample explanatory power, the forecasts generated by these equations are dominated, on average, by the five-year rule of thumb. Further experimentation shows that the five-year rule of thumb is itself dominated by two-, three-, four-, six-and seven-year rules of thumb, with the three-year rule being optimal for our sample.