In this paper, we study the contribution of frictions to expected returns (CFER). In the presence of market frictions, expected returns will be determined not only by risk factors but also by CFER. We derive an option-based formula to estimate CFER within a formal asset pricing setting. Our formula makes no assumptions on the types of frictions nor on investors’ preferences and it enables us to estimate CFER as a simple scaled deviations from put-call parity. We estimate the CFER of the U.S. individual equities using the OptionMetrics database. Four are the main empirical findings. First, the estimated CFER is sizable as it can become twice as large in magnitude as the average U.S. equity risk premium. Second, CFER predicts future stock returns cross-sectionally; the zero-cost long-short portfolio of the CFER-sorted decile portfolios earns the average return and alphas larger than 1.5% per month (t-statistics are above five). Third, consistent with the theoretical prediction, the regression of CFER-adjusted excess returns (excess returns less the estimated CFER) on risk factors yield a zero intercept. This result confirms that the predictability of CFER originates from capturing the effect of market frictions, rather than from omitted risk factors. Fourth, we show that the theoretical range of CFER values and the upper bound of the alpha of the CFER-sorted spread portfolio should be approximately equal to twice the round-trip transaction costs. Our empirical findings verify this prediction given the empirically estimated values of transaction costs. These findings suggest that even the expected returns of large optionable stocks are considerably affected by market frictions. We also show that various option-implied measures such as the implied volatility spread proxy CFER, thus providing a theoretical explanation for their ability to predict stock returns.