We study the effect of financial constraints on risk and expected returns by extending the investment-based asset pricing framework to incorporate retained earnings, debt, costly equity, and collateral constraints on debt capacity. Quantitative results show that more financially constrained firms are riskier and earn higher expected stock returns than less financially constrained firms. Intuitively, by preventing firms from financing all desired investments, collateral constraints restrict the flexibility of firms in smoothing dividend streams in the face of aggregate shocks. The inflexibility mechanism also gives rise to a convex relation between market leverage and expected stock returns.

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 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.

In this paper we show that the main empirical findings about firm diversification and performance are consistent with the maximization of shareholder value. In our model, diversification allows a firm to explore better productive opportunities while taking advantage of synergies. By explicitly linking the diversification strategies of the firm to differences in size and productivity, our model provides a natural laboratory to investigate several aspects of the relationship between diversification and performance. Specifically, we show that our model can rationalize the evidence on the diversification discount ( Lang and Stulz (1994) ) and the documented relation between diversification and productivity ( Schoar (2002) ).

We study the effect of financial constraints on risk and expected returns by extending the investment‐based asset pricing framework to incorporate retained earnings, debt, costly equity, and collateral constraints on debt capacity. Quantitative results show that more financially constrained firms are riskier and earn higher expected stock returns than less financially constrained firms. Intuitively, by preventing firms from financing all desired investments, collateral constraints restrict the flexibility of firms in smoothing dividend streams in the face of aggregate shocks. The inflexibility mechanism also gives rise to a convex relation between market leverage and expected stock returns.

We examine the network of trading relationships between insurers and dealers in the over‐the‐counter (OTC) corporate bond market. Regulatory data show that one‐third of insurers use a single dealer, whereas other insurers have large dealer networks. Execution prices are nonmonotone in network size, initially declining with more dealers but increasing once networks exceed 20 dealers. A model of decentralized trade in which insurers trade off the benefits of repeat business and faster execution quantitatively fits the distribution of insurers' network size and explains the price–network size relationship. Counterfactual analysis shows that regulations to unbundle trade and nontrade services can decrease welfare.

Dealer quotes in corporate bonds, though indicative, lower trading costs and increase trading volume. Dealers offering higher quality quotes attract more order flow and execute trades at favorable prices. Dealers advertise quotes to manage their inventories and attract orders from nonrelationship clients. However, quote competition is imperfect. The best quotes often fail to attract orders, and trade‐throughs are common. Nevertheless, quote competition is important as clients exploit quotes from other dealers in negotiations, forcing dealers with lower quality quotes to offer price improvements. Quoting is not a zero‐sum game, as more active bond‐level quoting leads to more bond‐level trading.