David Xiaoyu Xu

Despite the secular shift to nonbank lending, banks retain a distinctive advantage in providing credit lines (Kashyap, Rajan, and Stein, 2002). We document a new fact about nonbank lending: business development companies (BDCs) extend substantial credit commitments to borrowers, with off-balance-sheet commitments growing faster than total BDC assets. These commitments are concentrated, exposing BDCs to undiversified borrower liquidity shocks, a risk they manage with credit lines from banks. We develop a credit chain model of this layered liquidity insurance. The chain is not a pure pass-through of bank liquidity: it delivers only partial insurance—even when direct bank lending offers full insurance—because of nonbanks' debt financing frictions associated with using bank credit. We provide evidence consistent with our model's implications.

Credit ratings not only inform investors about default risk, but also serve as verifiable quality signals in asset management contracts, giving institutional investors a stake in the ratings. We show that when this stake is high, investors may influence rating outcomes to favor their portfolio positions and managerial compensation. Using a proprietary dataset of Collateralized Loan Obligations (CLOs), we examine the incentives of CLO managers to resist rating downgrades that could trigger overcollateralization test failures, which would reduce the managers' own payoffs. We find, and confirm using a novel instrumental variable, that loans facing greater resistance from CLO managers exhibit a significantly lower likelihood of downgrades in the near term. This effect is more pronounced when managers are above their incentive fee hurdles and when deteriorating loans are harder to liquidate preemptively. The delayed downgrades materialize as multi-notch downgrades within two to three years. Our results demonstrate that beyond fixed-income issuers, investors – typically viewed as rating consumers – can exert strategic influence on rating agencies.

We examine the growth and performance of AI-driven investing. Using investment advisers' regulatory disclosures, labor market data, and fund strategy descriptions, we document that AI-driven investing has grown steadily since the early 2010s and is concentrated among hedge funds. AI hedge funds outperformed non-AI hedge funds in the early years, but this outperformance declined over time, even among early adopters. Contrary to concerns about AI-driven strategy homogeneity, AI hedge funds exhibit lower return comovement than non-AI peers. Our findings highlight both the alpha-generating potential and the limitations of AI as a source of investment performance.

This paper investigates how the spatial distribution of financial intermediaries' human capital affects credit supply. Focusing on residential mortgage markets, we find that shocks to mortgage demand are not met with changes in the number of local loan officers, but instead affect workloads and remote lending. Importantly, evidence from shocks to the supply of loan officers shows these responses are not perfect substitutes for local intermediation. Local loan officers improve the availability of mortgage credit, the efficiency of the application process, and households' refinancing outcomes. Our findings suggest that labor market frictions can distort local credit supply.

Originate-to-distribute lending weakens banks' incentives to produce information about borrowers, but it may also strengthen loan investors' incentives to produce such information. We show that in leveraged loan syndications, pricing adjustments in response to investor demand during bookbuilding are informative about borrower credit quality. Upward spread adjustments predict higher default rates and larger realized losses given default. After syndication, banks revise their confidential supervisory risk assessments accordingly, consistent with learning about borrowers from investors. These patterns suggest that bookbuilding transmits investors' credit information into loan pricing and bank beliefs, partly mitigating the informational drawback of originate-to-distribute lending.

We study the contribution of AI-generated reference prices to intraday price discovery in markets with infrequent trading. Using corporate bond transactions and MarketAxess CP+ quotes, we find that CP+ is more informative about future trade prices than the last trade. Regression analysis shows that CP+ quote updates are systematically related to market-wide movements in bond, equity, and options markets, as well as bond-specific non-public information from the RFQ process. CP+ provides broad coverage across bonds and trading days. Its contribution to price discovery exhibits a bell-shaped relationship with liquidity and increases under market uncertainty. Following a trade report, CP+ updates quickly in the direction of the trade. We show that this can limit its contribution during periods driven by large transitory price shocks.

Mutual funds create liquidity by issuing demandable equity claims against illiquid holdings. We study the informational effects of this liquidity creation by exploiting frequent trading suspensions in China. When a portfolio stock is suspended, its market liquidity vanishes, and the fund's reported valuation becomes stale, leaving the fund mispriced. We find that investors acquire information about suspended stocks held in fund portfolios and reallocate capital toward underpriced funds. This information is subsequently incorporated into stock prices once trading resumes. Our findings suggest that, unlike liquidity created through bank debt, equity-based liquidity from nonbank intermediaries stimulates information acquisition about illiquid assets.

I study dynamic portfolio rebalancing in Collateralized Loan Obligations (CLOs) by developing an industry equilibrium model of nonbank lending, in which CLOs and loan funds arise endogenously in response to a premium for safe securities. When loans deteriorate after issuance, CLOs rebalance their portfolios to maintain collateral quality, which protects senior tranches at the expense of equity investors. This "self-healing" mechanism lowers CLOs' ex-ante funding costs by enabling the issuance of larger safe tranches. As more lenders operate CLOs, their portfolio rebalancing generates greater non-fundamental price pressures, incentivizing other lenders to operate loan funds. Overall, portfolio dynamics facilitate risk sharing across nonbank lenders and increase both total lending and the supply of safe securities relative to static portfolios.

Using detailed data on company visits by Chinese mutual funds, we provide direct evidence of mutual fund information acquisition activities and the consequent informational advantages mutual funds establish in local firms. Mutual funds are more likely to visit local and nearby firms both in and outside of their portfolios, but the ease of travel between fund and firm locations can substantially alleviate geographic distance constraints. Company visits by mutual funds are strongly associated with both fund trading activities and fund trading performance. Our results show that geographic constraints and costly information acquisition amplify information asymmetry in financial markets.