We propose a model of strategic renegotiation in which businesses are sequentially interconnected through their liabilities. This financing structure, which we refer to as a credit chain, gives rise to externalities, as each lender's willingness to provide concessions to its borrower depends on how this lender's own liabilities are expected to be renegotiated. We highlight how government interventions aimed at preventing default waves should account for private renegotiation incentives and their interlinkages. In particular, we contrast the consequences of targeted subsidy and debt reduction programs following economic shocks such as a pandemic or financial crisis.

We propose a tractable framework to examine the role of intermediary capital in the allocation and pricing of credit. In our model, regulated financial intermediaries compete with unregulated investors, targeting distributions of heterogeneous borrowers. We derive a sufficient statistic that characterizes intermediaries’ cross-sectional lending decisions and provide a novel intermediary asset pricing equation that accounts for the endogenous segmentation of marginal investors across securities. These formulae reveal the central role of intermediaries’ shadow cost of capital in both credit allocation and pricing. Our results can concurrently rationalize a broad array of empirical facts documented in the context of credit markets.

We classify asset pricing anomalies into those exacerbating mispricing (build-up anomalies) and those resolving it (resolution anomalies). We estimate the dynamics of price wedges for well-known anomaly portfolios and map them to firm-level mispricings. We find that several prominent anomalies like momentum and profitability further dislocate prices. Multi-factor models designed to eliminate one-month alphas still produce large price wedges. Our estimates yield a novel decomposition of Tobin’s q, revealing that q’s mispricing component has substantial explanatory power for firm investment. Overall, our results suggest that financial intermediaries chasing build-up anomalies negatively affect price efficiency and associated real capital allocation.

We study security issuers' decisions on whether to pool assets when facing counterparties endowed with market power, as is common in over-the-counter markets. Our analysis reveals how buyers' market power may render the pooling of assets suboptimal — both privately and socially — in particular, when the potential gains from trade are large. Pooling assets then reduces the elasticity of trade volume in the relevant part of the payoff distribution, exacerbating the inefficient rationing associated with the exercise of buyers' market power. Our analysis provides insight on the determinants of asset-backed securities issuance, including regulatory reforms affecting financial institutions' liquidity.

Over-the-counter (OTC) markets attract substantial trading volume despite exhibiting frictions absent in centralized limit-order markets. We compare the efficiency of OTC and limit-order markets when traders' expertise is endogenous. We show that asymmetric access to counterparties in OTC markets yields increased rents to expertise acquisition for a few well-connected core traders. When the existence of gains to trade is uncertain, traders' higher expertise in OTC markets can improve allocative efficiency. In contrast, when expertise primarily causes adverse selection, competitive limit-order markets tend to dominate. Our model provides guidance for policymakers and empiricists evaluating the efficiency of market structures.

I develop a model of venture capital (VC) intermediation that quantitatively explains central empirical facts about VC activity and can evaluate its macroeconomic relevance. I find that VC-backed innovations' impact is significantly larger than suggested by observed aggregate venture exit valuations, even after accounting for large exposures to systematic and uninsurable idiosyncratic risks. The risk properties of venture capital play a quantitatively important role in both explaining empirical regularities and shaping the value of ventures' contributions to economic growth. The model is analytically tractable and yields exact solutions, despite the presence of matching frictions, imperfect risk sharing, and endogenous growth.

We examine the importance of cross-sectional asset pricing anomalies (alphas) for the real economy. We develop a novel quantitative model of the cross-section of firms that features lumpy investment and informational inefficiencies, while yielding distributions in closed form. Our findings indicate that anomalies can cause material real inefficiencies, raising the possibility that agents that help to eliminate them add significant value to the economy. The framework reveals that the magnitude of alphas alone is a poor indicator of real implications, and highlights the importance of alpha persistence, the amount of mispriced capital, and the Tobin's q of firms affected.

Intermediation chains represent a common pattern of trade in over-the-counter markets. We study a classic problem impeding trade in these markets: an agent uses his market power to inefficiently screen a privately informed counterparty. We show that, generically, if efficient trade is implementable via any incentive-compatible mechanism, it is also implementable via a trading network that takes the form of a sufficiently long intermediation chain. We characterize information sets of intermediaries that ensure this striking result. Sparse trading networks featuring long intermediation chains might thus constitute an efficient market response to frictions, in which case no regulatory action is warranted.

We characterize optimal voluntary disclosures by a privately informed agent facing a counterparty endowed with market power in a bilateral transaction. Although disclosures reveal some of the agent's private information, they may increase his information rents by mitigating the counterparty's incentives to resort to inefficient screening. We show that when disclosures are restricted to be ex post verifiable, the informed agent optimally designs a disclosure plan that is partial and that implements socially efficient trade in equilibrium. Our results shed light on the conditions necessary for asymmetric information to impede trade and the determinants of disclosures' coarseness.

We propose a parsimonious model of bilateral trade under asymmetric information to shed light on the prevalence of intermediation chains that stand between buyers and sellers in many decentralized markets. Our model features a classic problem in economics where an agent uses his market power to inefficiently screen a privately informed counterparty. Paradoxically, involving moderately informed intermediaries also endowed with market power can improve trade efficiency. Long intermediation chains in which each trader's information set is similar to those of his direct counterparties limit traders' incentives to post prices that reduce trade volume and jeopardize gains to trade.

This paper develops a theoretical framework to shed light on variation in credit rating standards over time and across asset classes. Ratings issued by credit rating agencies serve a dual role: they provide information to investors and are used to regulate institutional investors. We show that introducing rating-contingent regulation that favors highly rated securities may increase or decrease rating informativeness, but unambiguously increases the volume of highly rated securities. If the regulatory advantage of highly rated securities is sufficiently large, delegated information acquisition is unsustainable, since the rating agency prefers to facilitate regulatory arbitrage by inflating ratings. Our model relates rating informativeness to the quality distribution of issuers, the complexity of assets, and issuers' outside options. We reconcile our results with the existing empirical literature and highlight new, testable implications, such as repercussions of the Dodd-Frank Act.