An empirical q-factor model consisting of the market factor, a size factor, an investment factor, and a profitability factor largely summarizes the cross section of average stock returns. A comprehensive examination of nearly 80 anomalies reveals that about one-half of the anomalies are insignificant in the broad cross section. More importantly, with a few exceptions, the q-factor model's performance is at least comparable to, and in many cases better than that of the Fama-French (1993) 3-factor model and the Carhart (1997) 4-factor model in capturing the remaining significant anomalies.

[A new methodology for equity valuation arises from the perspective of managers' supply of capital assets. Under q-theory, managers optimally adjust the supply of assets to changes in their market value. The first-order condition of investment then provides a valuation equation that infers asset prices from managers' costs of supplying the assets. This equation fits well the Tobin's q levels across many testing assets, including portfolios formed on q. With current investment-to-capital as the only input, the supply approach does not require cash flow forecasts or discount rate estimates, both of which are notoriously difficult to obtain in practice.]

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.

Most anomalies fail to hold up to currently acceptable standards for empirical finance. With microcaps mitigated via NYSE breakpoints and value-weighted returns, 65% of the 452 anomalies in our extensive data library, including 96% of the trading frictions category, cannot clear the single test hurdle of the absolute t-value of 1.96. Imposing the higher multiple test hurdle of 2.78 at the 5% significance level raises the failure rate to 82%. Even for replicated anomalies, their economic magnitudes are much smaller than originally reported. In all, capital markets are more efficient than previously recognized. Received June 12, 2017; editorial decision October 29, 2018 by Editor Stijn Van Nieuwerburgh.

This paper is a new incarnation of the defunct work previously circulated under the titles "Neoclassical Factors," "An equilibrium three-factor model," "Production-based factors," "A better three-factor model that explains more anomalies," and "An alternative three-factor model." We are extremely grateful to Robert Novy-Marx

A new methodology for equity valuation arises from the perspective of managers' supply of capital assets. Under q-theory, managers optimally adjust the supply of assets to changes in their market value. The first-order condition of investment then provides a valuation equation that infers asset prices from managers' costs of supplying the assets. This equation fits well the Tobin's q levels across many testing assets, including portfolios formed on q. With current investment-to-capital as the only input, the supply approach does not require cash flow forecasts or discount rate estimates, both of which are notoriously difficult to obtain in practice.

A detailed treatment of aggregation and capital heterogeneity substantially improves the performance of the investment CAPM. Firm-level predicted returns are constructed from firm-level accounting variables and aggregated to the portfolio level to match with portfolio-level stock returns. Working capital forms a separate productive input besides physical capital. The model simultaneously fits the value, momentum, investment, and profitability premiums and partially explains positive stock-fundamental return correlations, the procyclical and short-term dynamics of the momentum and profitability premiums, and the countercyclical and long-term dynamics of the value and investment premiums. However, the model falls short in explaining momentum crashes. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online..