Using the altman z-score to optimize value investing strategies: an empirical analysis

Abstract

This thesis investigates whether value strategies in the S&P500 can be improved by filtering out potentially distressed stocks. For this purpose, various value signals are combined with the Altman Z-Score, a widely used insolvency forecasting method. Through an empirical analysis of in-sample and out-of-sample data, this paper shows that while combinations of enterprise multiples and the Z-Score yield the highest risk-adjusted returns in the in-sample period, these strategies cannot outperform the market or corresponding value-only strategies in the out-of sample period. The hypothesis that strategies with the Z-Score as a safety filter can outperform classical value strategies thus cannot be proven.