We empirically evaluate the predictive power of money growth measured by M2 for stock returns of the S&P 500 index. We use monthly US data and predict multiperiod returns over 1, 3, and 5 years with long-horizon regressions. In-sample regressions show that money growth is useful for predicting returns. Higher recent money growth has a significantly negative effect on subsequent returns of the S&P 500. An out-of-sample analysis shows that a simple model with money growth as a single predictor performs as goods as the constant expected returns model, while models with several predictor variables perform worse than those simple models.