We propose a dynamic model of investment and trade in a market of a specialized technology subject to two main frictions. First, agents cannot raise outside capital. Second, a random group of agents will have the opportunity to invest in new technology and these opportunities are not contractible. The first friction implies the presence of invesment cycles with abundant invesment and low returns in booms and little invesment and high returns in recessions. Only when the second friction is present invesment cycles are constrained inefficient. Often the inefficiency is two-sided with too much invesment in booms and too little in recessions from a social point of view. Interventions targetting only the underinvesment in recessions might make all agents worse off. Also, the two-sided inefficiency typically implies too volatile prices and too frequent realizations of abnormally low prices compared to fundamentals.

We characterize equilibrium leverage dynamics in a trade‐off model in which the firm can continuously adjust leverage and cannot commit to a policy ex ante. While the leverage ratchet effect leads shareholders to issue debt gradually over time, asset growth and debt maturity cause leverage to mean‐revert slowly toward a target. Investors anticipate future debt issuance and raise credit spreads, fully offsetting the tax benefits of new debt. Shareholders are therefore indifferent toward the debt maturity structure, even though their choice significantly affects credit spreads, leverage levels, the speed of adjustment, future investment, and growth.

In sharp contrast to most previous crisis episodes, the Treasury market experienced severe stress and illiquidity during the COVID-19 crisis, raising concerns that the safe-haven status of US Treasuries may be eroding. We document large shifts in Treasury ownership and temporary accumulation of Treasury and reverse repo positions on dealer balance sheets during this period. We build a dynamic equilibrium asset pricing model in which dealers subject to regulatory balance sheet constraints intermediate demand/supply shocks from habitat agents and provide repo financing to levered investors. The model predicts that Treasury inconvenience yields, measured as the spread between Treasuries and overnight-index swap rates (OIS), as well as spreads between dealers’ reverse repo and repo rates, should be highly positive during the COVID-19 crisis, as is confirmed in the data. The same model framework, adapted to the institutional setting in 2007–2009, can also explain the negative Treasury-OIS spread observed during the Great Recession.

We find that shocks to the equity capital ratio of financial intermediaries—Primary Dealer counterparties of the New York Federal Reserve—possess significant explanatory power for cross-sectional variation in expected returns. This is true not only for commonly studied equity and government bond market portfolios, but also for other more sophisticated asset classes such as corporate and sovereign bonds, derivatives, commodities, and currencies. Our intermediary capital risk factor is strongly procyclical, implying countercyclical intermediary leverage. The price of risk for intermediary capital shocks is consistently positive and of similar magnitude when estimated separately for individual asset classes, suggesting that financial intermediaries are marginal investors in many markets and hence key to understanding asset prices.

We introduce uncertainty into Holmstrom and Milgrom (1987) to study optimal long-term contracting with learning. In a dynamic relationship, the agent’s shirking not only reduces current performance, but also increases the agent’s information rent due to the persistent belief manipulation effect. We characterize the optimal contract using the dynamic programming technique in which information rent is the unique state variable. In the optimal contract, the optimal effort is front-loaded and stochastically decreases over time. Furthermore, the optimal contract exhibits an option-like feature in that incentives increase after good performance. Implications about managerial incentives and asset management compensations are discussed. Received August 31, 2015; editorial decision October 20, 2016 by Editor Francesca Cornelli.

What makes an asset a “safe” asset? We study a model where two countries each issue sovereign bonds to satisfy investors’ safe asset demands. The countries differ in the float of their bonds and the fundamental resources available to rollover debts. A sovereign’s debt is safer if its fundamentals are strong relative to other possible safe assets, not merely strong on an absolute basis. If demand for safe assets is high, a large float enhances safety through a market depth benefit. If demand for safe assets is low, then large debt size is a negative as rollover risk looms large.

We develop a structural credit model to examine how interactions between default and liquidity affect corporate bond pricing. The model features debt rollover and bond-price-dependent holding costs. Over the business cycle and in the cross-section, the model matches average default rates and credit spreads in the data, and captures variations in bid-ask and bond-CDS spreads. A structural decomposition reveals that default-liquidity interactions can account for 10%–24% of the level of credit spreads and 16%–46% of the changes in spreads over the business cycle. Further, liquidity-related corporate bond financing costs amount to 6% of the total issuance amount from 1996 to 2015. Received July 12, 2015; editorial decision April 15, 2017 by Editor Andrew Karolyi.

Using granular data covering both regulated (brokerage‐financed) and unregulated (shadow‐financed) margin accounts in China, we provide novel evidence on retail investors' margin trading behavior and its price implications. We first show that retail investors' decisions to lever up in stock trading despite the hefty borrowing cost is related to their lottery preferences. We then show that margin borrowing affects investors' trading behavior—investors are more likely to liquidate their holdings as they approach margin calls. Finally, we show that margin‐induced trading aggregates to affect asset prices and contributes to shock spillovers across stocks (e.g., from lottery stocks to nonlottery stocks).

We provide causal evidence on the value of asset pledgeability by exploiting a unique feature of Chinese corporate bond markets: bonds with identical fundamentals are traded on two segmented markets with different rules for repo transactions. Using a policy shock that rendered AA+ and AA bonds ineligible for repo on one market only, we compare how bond prices changed across markets and rating classes around this event. When the haircut increases from 0% to 100%, bond yields increase by 39 bps to 85 bps. These estimates help us infer the magnitude of the shadow cost of capital in China.