Firm investment activity and firm characteristics, particularly the market-to-book ratio or q, are functions of the state of the economy and therefore contain information about the dynamic behavior of stock returns. This paper develops a model of a production economy in which real investment is irreversible and subject to convex adjustment costs. During low-q (high-q) periods when the irreversibility constraint (constraint on the rate of investment) is binding, conditional volatility and expected returns on one hand, and market-to-book ratios on the other, should be negatively (positively) related. Empirical tests based on industry portfolios support these predictions for conditional volatility but not for expected returns.

This paper presents a general equilibrium model of a two-sector production economy with irreversible real investment. Irreversibility of investment is the most prominent feature of the productive sector. It restricts capital accumulation, affecting firms’ investment decisions, which in turn determine properties of asset prices. Thus, this model provides a framework for connecting stock returns to firm characteristics that proxy for real economic activity. The primary focus of this paper is on the analysis of the equilibrium and the effects of irreversibility of investment.

[Average return differences among firms sorted on valuation ratios, past investment, profitability, market beta, or idiosyncratic volatility are largely driven by differences in exposures of firms to the same systematic factor related to embodied technology shocks. Using a calibrated structural model, we show that these firm characteristics are correlated with the ratio of growth opportunities to firm value, which affects firms' exposures to capital-embodied productivity shocks and risk premia. We thus provide a unified explanation for several apparent anomalies in the cross-section of stock returns—namely, predictability of returns by these firm characteristics and return comovement among firms with similar characteristics.]

We study asset-pricing implications of innovation in a general-equilibrium overlapping-generations economy. Innovation increases the competitive pressure on existing firms and workers, reducing the profits of existing firms and eroding the human capital of older workers. Due to the lack of inter-generational risk sharing, innovation creates a systematic risk factor, which we call “displacement risk.” This risk helps explain several empirical patterns, including the existence of the growth-value factor in returns, the value premium, and the high equity premium. We assess the magnitude of displacement risk using estimates of inter-cohort consumption differences across households and find support for the model.

We analyze a general equilibrium exchange economy with a continuum of agents who have “catching up with the Joneses” preferences and differ only with respect to the curvature of their utility functions. While individual risk aversion does not change over time, dynamic redistribution of wealth among the agents leads to countercyclical time variation in the Sharpe ratio of stock returns. We show that both the conditional risk premium and the return volatility are negatively related to the level of stock prices. Therefore, our model exhibits many of the empirically observed properties of aggregate stock returns, for example, patterns of autocorrelation in returns, the “leverage effect” in return volatility, and long‐horizon return predictability.

We document a new stylized fact, that the relationship between the volatility of oil futures prices and the slope of the forward curve is nonmonotone and has a V-shape. This pattern cannot be generated by standard models that emphasize storage. We develop an equilibrium model of oil production in which investment is irreversible and capacity constrained. Investment constraints affect firms' investment decisions and imply that the supply elasticity changes over time. Since demand shocks must be absorbed by changes in prices or changes in supply, time-varying supply elasticity results in time-varying volatility of futures prices. Estimating this model, we show it is quantitatively consistent with the V-shape relationship between the volatility of futures prices and the slope of the forward curve.

We propose a general simulation-based procedure for estimating the quality of approximate policies in heterogeneous-agent equilibrium models, which allows us to verify that such approximate solutions describe a near-rational equilibrium. Our procedure endows agents with superior knowledge of the future path of the economy, while imposing a suitable penalty for such foresight. The relaxed problem is more tractable than the original, and results in an upper bound on agents’ welfare. Our method applies to various solution algorithms. We illustrate our approach in two applications: the incomplete-markets model of Krusell and Smith (1998) and the heterogeneous firm model of Khan and Thomas (2008).

Average return differences among firms sorted on valuation ratios, past investment, profitability, market beta, or idiosyncratic volatility are largely driven by differences in exposures of firms to the same systematic factor related to embodied technology shocks. Using a calibrated structural model, we show that these firm characteristics are correlated with the ratio of growth opportunities to firm value, which affects firms' exposures to capital-embodied productivity shocks and risk premia. We thus provide a unified explanation for several apparent anomalies in the cross-section of stock returns—namely, predictability of returns by these firm characteristics and return comovement among firms with similar characteristics.

We propose a theoretically motivated procedure for measuring heterogeneity in firms’ growth opportunities and document its empirical properties. The term “growth opportunities” refers to the component of a firm’s market value that cannot be attributed to its assets in place. This decomposition of firm value underpins many of the theoretical models describing cross-sectional differences in firms’ investment and stock return behavior. However, successful applications of such models depend on the quality of empirical measures of growth opportunities. Our procedure identifies economically significant differences in firms’ growth opportunities which are not captured by the commonly used empirical measures.

We explore the impact of investment‐specific technology (IST) shocks on the cross section of stock returns. Using a structural model, we show that IST shocks have a differential effect on the value of assets in place and the value of growth opportunities. This differential sensitivity to IST shocks has two main implications. First, firm risk premia depend on the contribution of growth opportunities to firm value. Second, firms with similar levels of growth opportunities comove with each other, giving rise to the value factor in stock returns and the failure of the conditional CAPM. Our empirical tests confirm the model's predictions.