The performance of portfolio managers depends on market timing, volatility timing, and security selection. We develop holdings-based performance measures that adjust for risk using stochastic discount factors, display all three components in a consistent framework, and avoid strong assumptions about managers’ behavior. Previous models leave out some of the components of performance, and correcting for this we deliver better measures of selectivity. Sorting stocks held by funds on selectivity produces a quintile spread in four-factor alphas greater than 2.5% per year before costs and more than 1.7% greater than found using the Daniel, Grinblatt, Titman, and Wermers (1997) measure.

We analyze the out-of-sample performance of variables shown to forecast future mutual fund alphas. The degree of predictability, as measured by alpha spreads from quintile sorts or cross-sectional regression slopes, falls by at least half post-sample. These declines appear to be primarily the result of changes in the level of arbitrage activity in the market, with mutual fund competition appearing to play a secondary role. We find no evidence that the declines are the result of data snooping or learning by investors or fund managers. Finally, we show that corporate bond fund performance exhibits similar dependence on measures of bond market arbitrage activity.

In the investment theory, firms with high expected investment growth earn higher expected returns than firms with low expected investment growth, holding investment and expected profitability constant. Building on cross-sectional growth forecasts with Tobin’s q, operating cash flows, and change in return on equity as predictors, an expected growth factor earns an average premium of 0.84% per month (t = 10.27) in the 1967–2018 sample. The q5 model, which augments the Hou–Xue–Zhang (2015, Rev. Finan. Stud., 28, 650–705) q-factor model with the expected growth factor, shows strong explanatory power in the cross-section and outperforms the Fama–French (2018, J. Finan. Econom., 128, 234–252) six-factor model.

Many recently proposed, seemingly different factor models are closely related. In spanning tests, the q-factor model largely subsumes the Fama–French five- and six-factor models, and the q5 model subsumes the Stambaugh–Yuan four-factor model. Their “mispricing” factors are sensitive to the construction procedure, and once replicated via the traditional approach, are close to the q-factors, with correlations of 0.8 and 0.84. Finally, consistent with the investment CAPM, valuation theory predicts a positive relation between the expected investment and the expected return.

We develop a model-free measure of the variance premium by constructing option portfolios whose returns are highly correlated with realized stock variance. This effectively decomposes returns into realized variance minus implied variance. We apply this decomposition to document a novel quarterly cross-sectional continuation pattern in both realized variance and implied variance of individual stocks. Implied variance underanticipates the seasonality of realized variance, so options that performed well at quarterly lags continue to earn high returns in the future. Quarterly periodicity in realized stock variance only occurs on days with analyst earning revisions, suggesting an informational channel for this pattern.

In the investment theory, firms with high expected investment growth earn higher expected returns than firms with low expected investment growth, holding investment and expected profitability constant. Building on cross-sectional growth forecasts with Tobin’s q, operating cash flows, and change in return on equity as predictors, an expected growth factor earns an average premium of 0.84% per month (t = 10.27) in the 1967–2018 sample. The q5 model, which augments the Hou–Xue–Zhang (2015, Rev. Finan. Stud., 28, 650–705) q-factor model with the expected growth factor, shows strong explanatory power in the cross-section and outperforms the Fama–French (2018, J. Finan. Econom., 128, 234–252) six-factor model.

Numerous trading strategies examined in options research exhibit remarkably high mean returns and Sharpe ratios. We show some of these seemingly “good deals” are due to look-ahead biases. These biases stem from using information unavailable at the portfolio formation time to filter out observations suspected of being noisy or erroneous. Our results suggest that elevated Sharpe ratios may serve as potential indicators of such look-ahead biases. Furthermore, deviating from previous literature findings, we show that illiquidity is not strongly priced in stock options and that only a small set of stock characteristics are in fact associated with option expected returns.

This paper investigates the performance of option investments across different stocks by computing monthly returns on at‐the‐money straddles on individual equities. We find that options with high historical returns continue to significantly outperform options with low historical returns over horizons ranging from 6 to 36 months. This phenomenon is robust to including out‐of‐the‐money options or delta‐hedging the returns. Unlike stock momentum, option return continuation is not followed by long‐run reversal. Significant returns remain after factor risk adjustment and after controlling for implied volatility and other characteristics. Across stocks, trading costs are unrelated to the magnitude of momentum profits.