We consider asset pricing in a monetary economy where liquid assets are held to lower transaction costs. The ensuing model extends the capital asset pricing model (CAPM) and the consumption CAPM by deriving real money growth as an additional factor determining returns. Empirically, the two model versions compare favorably to other theoretical asset pricing models along several dimensions, supporting the traditional intertemporal asset pricing perspective. A value premium arises because value firms are sensitive to liquidity shocks but growth firms are not. Although no alternative factor drives out the money growth factor, the conditioning CAY factors of Lettau and Ludvigson (2001b) add explanatory power.

In a general real business cycle model, we derive a pricing kernel that involves only production function arguments. The productivity shock is the single factor and the capital stock relative to a productivity measure is the conditioning variable. The model compares favorably with the complementary consumption-based and market-based approaches and with the Fama-French three-factor model. A size premium arises from differences in unconditional sensitivities—small firms are more sensitive to productivity shocks—and a value premium from differences in conditional sensitivities to productivity shocks—growth firms are more sensitive to productivity shocks when the productivity risk premium is low.

We present a theoretical perspective that motivates the use of the Generalized Least Squares R-Square, prominently advocated by Lewellen et al. [Lewellen, J., Nagel, S., Shanken, J., forthcoming. A skeptical appraisal of asset-pricing tests. Journal of Financial Economics], as an evaluation measure for multivariate linear asset pricing models. Adapting results from Shanken [Shanken, J., 1985. Multivariate tests of the zero-beta CAPM. Journal of Financial Economics 14, 327–348] and Kandel and Stambaugh [Kandel, S., Stambaugh, R.F., 1995. Portfolio inefficiency and the cross-section of expected returns. Journal of Finance 50, 157–184], we provide various interpretations and a graphical account in mean-variance space of this measure, facilitating a better understanding of its properties. We furthermore relate it to another leading evaluation metric, the HJ-distance of Hansen and Jagannathan [Hansen, L.P., Jagannathan, R., 1997. Assessing specification errors in stochastic discount factor models. Journal of Finance 52, 557–590]. Additionally, we present a comparison between these evaluation measures using mean-variance mathematics in risk-return space, and we provide a simple formula for calculating both model evaluation measures that involves only the parameters of the mean-variance asset and factor frontiers.

An intertemporal general equilibrium model relates financial asset returns to movements in aggregate output. The model is a standard neoclassical growth model with serial correlation in aggregate output. Changes in aggregate output lead to attempts by agents to smooth consumption, which affects the required rate of return on financial assets. Since aggregate output is serially correlated and hence predictable, the theory suggests that stock returns can be predicted based on rational forecasts of output. The empirical results confirm that stock returns are a predictable function of aggregate output and also support the accompanying implications of the model.

An intertemporal general equilibrium model relates financial asset returns to movements in aggregate output. The model is a standard neoclassical growth model with serial correlation in aggregate output. Changes in aggregate output lead to attempts by agents to smooth consumption, which affects the required rate of return on financial assets. Since aggregate output is serially correlated and hence predictable, the theory suggests that stock returns can be predicted based on rational forecasts of output. The empirical results confirm that stock returns are a predictable function of aggregate output and also support the accompanying implications of the model.