We develop a dynamic model of investment, financing, and cash management decisions in which investment is lumpy and firms face capital supply uncertainty. We characterize optimal policies explicitly, demonstrate that smooth-pasting conditions may not guarantee optimality, and show that firms may not follow standard single barrier policies. In the model, firms with high investment costs differ in their behaviors from firms with low investment costs, financing policy does not follow a strict pecking order, and the optimal payout policy may feature several regions with both incremental and lumpy dividend payments.

We extend Duffie et al.’s (2005) search-theoretic model of over-the-counter (OTC) asset markets, allowing for a decentralized inter-dealer market with arbitrary heterogeneity in dealers’ valuations (or, equivalently, inventory costs). We develop a solution technique that makes the model fully tractable and allows us to derive, in closed form, theoretical formulas for key statistics analysed in empirical studies of the intermediation process in OTC markets. A calibration to the market for municipal bonds allows us to quantify important unobservable characteristics of this market, including the severity of search and bargaining frictions and the nature of heterogeneity across dealers. We use our calibrated model to study the effect of these market characteristics on total welfare and the distribution of gains from trade across customers and dealers.

We develop a dynamic model of banking to assess the effects of liquidity and leverage requirements on banks’ financing decisions and insolvency risk. In this model, banks face taxation, issuance costs of securities, and default costs and maximize shareholder value by choosing their debt-to-asset ratio, deposits-to-debt ratio, liquid asset holdings, equity issuance and default policies in response to these frictions as well as regulatory requirements. Our analytic characterization of the bank policy choices shows that imposing liquidity requirements leads to lower bank losses in default at the cost of an increased likelihood of default. Combining liquidity and leverage requirements reduces both the likelihood of default and the magnitude of bank losses in default.

We study an economy populated by three groups of myopic agents: constrained agents subject to a portfolio constraint that limits their risk taking, unconstrained agents subject to a standard nonnegative wealth constraint, and arbitrageurs with access to a credit facility. Such credit is valuable as it allows arbitrageurs to exploit the limited arbitrage opportunities that emerge endogenously in reaction to the demand imbalance generated by the portfolio constraint. The model is solved in closed-form, and we show that, in contrast to existing models with frictions and logarithmic agents, arbitrage activity has an impact on the price level and generates both excess volatility and the leverage effect. We show that these results are due to the fact that arbitrageurs amplify fundamental shocks by levering up in good times and deleveraging in bad times.

When investors have incomplete information, expected returns, as measured by an econometrician, deviate from those predicted by standard asset pricing models by including a term that is the product of the stock’s idiosyncratic volatility and the investors’ aggregated forecast errors. If investors are biased this term generates a relation between idiosyncratic volatility and expected stocks returns. Relying on forecast revisions from IBES, we construct a new variable that proxies for this term and show that it explains a significant part of the empirical relation between idiosyncratic volatility and stock returns.

We study the existence of dynamic equilibria with endogenously complete markets in continuous-time, heterogenous agents economies driven by diffusion processes. Our main results show that under appropriate conditions on the transition density of the state variables, market completeness can be deduced from the primitives of the economy. In particular, we prove that a sufficient condition for market completeness is that the volatility of dividends be invertible and provide higher order conditions that apply when this condition fails as is the case in the presence of fixed income securities. In contrast to previous research, our formulation does not require that securities pay terminal dividends, and thus allows for both finite and infinite horizon economies.

The representative-agent Lucas model stresses aggregate risk and hence does not allow us to study the impact of agents’ heterogeneity on the dynamics of equilibrium trading volume. In this paper, we investigate under what conditions non-informational heterogeneity, i.e., differences in preferences and endowments, leads to nontrivial trading volume in equilibrium. We present a non-informational no-trade theorem that provides necessary and sufficient conditions for zero equilibrium trading volume in a continuous-time Lucas market model with heterogeneous agents, multiple goods, and multiple securities. We explain in detail how no-trade equilibria are related to autarky equilibria, portfolio autarky equilibria, and peculiar financial market equilibria, which play an important role in the literature on international risk sharing.

We develop a dynamic model of investment, financing, and cash management decisions in which investment is lumpy and firms face capital supply uncertainty. We characterize optimal policies explicitly, demonstrate that smooth-pasting conditions may not guarantee optimality, and show that firms may not follow standard single barrier policies. In the model, firms with high investment costs differ in their behaviors from firms with low investment costs, financing policy does not follow a strict pecking order, and the optimal payout policy may feature several regions with both incremental and lumpy dividend payments.