Industry Costs of Equity: Incorporating Prior Information

I examine whether incorporating economically motivated prior information yields more accurate forecasts of industry costs of equity. I find that incorporating the long†run mean of the Capital Asset Pricing Model (CAPM) parameters and the industry characteristics in the cross section produces more accurate parameter estimates, which subsequently translate into more accurate out†of†sample forecasts of industry costs of equity. The outperformance of this method over rolling†window estimates becomes larger as the forecast horizon extends into the future. These findings provide evidence that the CAPM parameters have a long†run mean†reversion property and correlate with the industry characteristics in a systematic way.