Value Investing via Bayesian Inference

Classic value investing à la Graham & Dodd (1934) focuses on selecting stocks that seem cheap relative to their intrinsic value and fundamental quality. We use Bayesian inference to account for the large amount of uncertainty within intrinsic value estimation. We find that an undervalued-minus-overvalued (UMO) factor that invests in cheap quality stocks and sells expensive junk stocks selected via Bayesian inference yields high risk-adjusted returns and Sharpe ratios. Our findings suggest that while the relative benefit of accounting for uncertainty via Bayesian inference is not large over shorter holding periods, it pays off for investment horizons longer than a month