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 propose a “debt view” to explain the dominant international role of the dollar. Within a simple capital-structure model with debt-currency choice, we show that the “dominant currency” is the one that (1) depreciates in global downturns over horizons of typical debt maturity and (2) has the steepest nominal yield curve. Empirically, we show the dollar fits this description better than other major currencies. The debt view can explain dollar-debt-issuance patterns over the past two decades. It also offers insights into the future of the dominance of the dollar in the aftermath of the COVID-19 crisis.

Most assets are traded in multiple interconnected trading venues. This paper develops an equilibrium model of decentralized markets that accommodates general market structures with coexisting exchanges. Decentralized markets can allocate risk among traders with different risk preferences more efficiently, thus realizing gains from trade that cannot be reproduced in centralized markets. Market decentralization always increases price impact. Yet, markets in which assets are traded in multiple exchanges, whether they are disjoint or intermediated, can give higher welfare than the centralized market with the same traders and assets. In decentralized markets, demand substitutability across assets is endogenous and heterogeneous among traders.

We propose that investment strategies should be evaluated based on their net-of-trading-cost return for each level of risk, which we term the “implementable efficient frontier.” While numerous studies use machine learning return forecasts to generate portfolios, their agnosticism toward trading costs leads to excessive reliance on fleeting small-scale characteristics, resulting in poor net returns. We develop a framework that produces a superior frontier by integrating trading-cost-aware portfolio optimization with machine learning. The superior net-of-cost performance is achieved by learning directly about portfolio weights using an economic objective. Further, our model gives rise to a new measure of “economic feature importance.”

We characterize the unique equilibrium in an economy populated by strategic CARA investors who trade multiple risky assets with arbitrarily distributed payoffs. We use our explicit solution to study the joint behavior of illiquidity of option contracts. Option bid-ask spreads are proportional to risk aversion and risk-neutral variances of option payoffs. Spreads may decrease in risk aversion, physical variance, open interest, and increase after earnings announcements in a result contrary to conventional wisdom. All these predictions are confirmed empirically using a large panel data set of U.S. stock options.

We build a model of endogenous, innovation-driven growth in which innovative firms have costly access to outside financing and hoard cash reserves to maintain financial flexibility. We show that financing frictions slow down Schumpeterian creative destruction by discouraging entry. As a result, financing frictions importantly affect the composition of growth, by reducing the contribution of entrants but spurring the contribution of incumbents. We investigate the net impact of these countervailing effects on the equilibrium growth rate and welfare.

An overlapping generations model with investors having heterogeneous investment horizons leads to a two-factor asset pricing model. The risk premiums are determined by the exposure to the market (myopic betas) and the future return on the efficient portfolio (non-myopic betas), which is identified nonparametrically from equilibrium. Non-myopic betas are priced in the cross-section of stocks, producing increasing and economically significant risk-return relation. In the model with funding constraints, low non-myopic beta stocks deliver higher risk-adjusted returns. Empirically, a betting against non-myopic beta portfolio generates superior performance relative to common factor models and is negatively correlated with the market betting against beta portfolio.

We study survival, price impact, and portfolio impact in heterogeneous economies. We show that, under the equilibrium risk-neutral measure, long-run price impact is in fact equivalent to survival, whereas long-run portfolio impact is equivalent to survival under an agent-specific, wealth-forward measure. These results allow us to show that price impact and portfolio impact are two independent concepts: a nonsurviving agent with no long-run price impact can have a significant long-run impact on other agents' optimal portfolios.

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.