Do Asset Prices Help Predict Inflation? Evidence from Individual Stock Prices

This paper revisits the predictive power of asset prices for inflation, focusing on individual stock prices rather than aggregate indices. Using a large panel data of firm-level stock prices and applying machine learning techniques, we demonstrate that individual stock prices significantly enhance the accuracy of inflation forecasts, particularly over medium- to long-term horizons and during periods of high inflationary and deflationary pressure. Compared to composite and industry-level stock indices, other aggregate asset prices, and Fama-French factors, individual stock prices contain valuable heterogeneous information, offering richer insights for inflation forecasting. These findings provide new empirical support for macro-finance theory, affirming the predictive value of asset prices from a micro-level perspective.