What is the Predictive Power of Consumer Sentiment?

Abstract

This study examines the dynamic relationship between consumer sentiment and four asset categories: macro-financial assets, safe-haven assets, volatile assets, and a risk-free asset. Using monthly data from January 2016 to December 2025, the study investigates whether consumer sentiment contains predictive information for asset returns, or whether financial assets instead act as leading indicators of sentiment. The empirical analysis is based on bivariate Vector Autoregression (VAR) models, Granger-causality tests, Orthogonalized Impulse Response Functions (OIRFs), and Forecast Error Variance Decomposition (FEVD), with macro-financial controls and robustness checks. The results show that the relationship between consumer sentiment and financial assets is not uniform across asset classes. Sentiment has limited predictive power for most traditional assets and the largest cryptocurrencies but does show some predictive ability for more speculative cryptocurrencies such as Dogecoin, XRP, TRX, and partly Cardano. By contrast, the S&P 500 and several major cryptocurrencies, especially Ethereum, Solana, Binance Coin, and Bitcoin, consistently predict consumer sentiment, indicating that they act as leading indicators of expectations. Cardano exhibits a bidirectional relationship, while gold and oil remain largely unrelated to sentiment, and silver shows only weak and time-dependent effects. Overall, the findings suggest that consumer sentiment is not a universal predictor of returns, but rather an asset-specific influence, with the strongest links concentrated in the selected macro-financial assets index and selected major cryptocurrencies.