The Good and the Bad of Value Investing: Applying a Bayesian Approach to Develop Enhancement Models

Value investing was first identified by Graham and Dodd in the mid-30's as an effective approach to investing. Under this approach stocks are rated as being cheap or expensive largely based on some valuation multiple such as the stock's price-to-earnings or book-to-market ratio. Numerous studies have found that value investing does perform well across most equity markets but it is also true that over most reasonable time horizons, the majority of value stocks underperform the market. The reason for this is that the poor valuation ratios for many companies are reflective of poor fundamentals that are only worsening. The typical value measures do not provide any insights into those stocks whose performance is likely to mean-revert and those that will continue along their recent downhill path. The hypothesis in this paper is that the value stocks most likely to mean-revert are those that are financially sound. Further, it is proposed that we should be able to gain some insights into the financial strength of the value companies using fundamental accounting data. We apply a Bayesian model averaging approach to a set of fundamental accounting variables to forecast, the probability of each value stock outperforming the market. These probability estimates are then used as the basis for enhancing a value portfolio that has been formed using some valuation multiple. The positive note from our study of the US, UK and Australian equity markets is that it appears that fundamental accounting data can be used to enhance the performance of a value investment strategy. The bad news is that the sources of accounting data that play the greatest role in providing such insights would seem to vary both across time and across markets.