Subjective expectations and asset prices both revolve around distorted probabilities. Subjective expectations are expectations under biased probabilities, and asset prices are expectations under risk-neutral probabilities. Given this link, asset pricing techniques designed to estimate a Stochastic Discount Factor (SDF) can be used to estimate a Subjective Belief Factor (SBF), i.e., a distortion that characterizes many subjective expectations even for non-financial variables. Using the Survey of Professional Forecasters and Blue Chip, we find that differences between subjective expectations and statistical expectations for 24 macroeconomic variables can be summarized (average R-squared of 50%) by a single SBF related to real GDP growth and the T-bill rate. This SBF also accurately replicates differences across the 24 variables in the serial correlation of forecast errors and under/overreaction. Further, the SBF can be used to succinctly incorporate subjective beliefs data into asset pricing models, even those involving many expectations. Applying our measured SBF to a model of cross-sectional stock returns, we estimate that distorted beliefs account for the majority of excess returns for the Fama-French factors and explain about two thirds of the variation in returns across 176 anomalies, while the remaining third is attributed to preferences/risk. Our results support models like robust control and certain versions of diagnostic expectations in which agents’ beliefs across different variables are characterized by a single probability distortion.