September 10 2026, 12 PM ET

A Necessary Lie: Conflict of Interest in Investor-Paid Ratings

Filipp Prokopev (Michigan)

Abstract: Investor payment is widely believed to eliminate conflicts of interest in information sales, including ratings. I show that this conventional wisdom does not hold when the information buyer is a delegated asset manager with market power and its own agency frictions. In contrast to small dispersed investors, a large fund with existing holdings is willing to purchase a biased rating that inflates their market value. The provider prefers to sell distorted ratings when market illiquidity erodes information rents but not distortion rents, which increase with clients' market power. Although bias reduces the information content of the  ratings, it can encourage the provider to expand access to informed trading and improve price informativeness. As such, stricter regulation of rating providers can hurt overall price efficiency. 

September 17 2026, 12 PM ET

Adverse Selection Under Repeated Contracting in U.S. Mortgage Markets

Tim Seida (Northwestern)

Abstract: This paper studies how lender-borrower relationships impact competition, performance, and pricing in U.S. mortgage markets. I establish that lenders learn private information about borrowers during the lending relationship, creating adverse selection among borrowers who switch lenders. Switching borrowers are more likely to miss payments than borrowers who stay with their original lender, and lenders respond by charging switchers higher interest rates. To identify the role of lender private information in generating this adverse selection, I use lender market exits as a quasi-experiment and show that borrowers forced to switch lenders perform better than other borrowers who switch lenders. I then estimate a model of relationship lending with endogenous adverse selection to quantify how policies which eliminate incumbent lenders' information advantage would reduce their incentives to offer lower initial rates. 

September 24 2026, 12 PM ET

Intermediaries and Expected Returns

Avinash Sattiraju (WashU Olin), Taizhi (Steve) Wu (Washu Olin)

Abstract: We develop an option-implied measure of the equity premium motivated by intermediary asset pricing. Modifying the framework of Martin (2017), we replace the market’s risk-neutral variance with the risk-neutral covariance between the aggregate market and intermediary equity. We estimate this intermediation bound using index (SPX) and financial-sector (XLF) options. Empirically, the bound’s performance is highly state-dependent: it closely tracks the market baseline in calm periods but separates sharply during financial distress. Consequently, the intermediation bound delivers substantial out-of-sample forecasting gains for one-year-ahead market returns, with outperformance concentrated almost entirely during periods of impaired risk-bearing capacity of financial intermediaries. Event-study evidence from a bank recapitalization event provides further support for bank net worth mattering for aggregate asset prices. Ultimately, our results demonstrate that intermediary option prices provide a real-time, forward-looking gauge of expected returns exactly when they are most useful to policymakers: financial crises. 

October 1 2026, 12 PM ET

Caught in the queue: Exchange latency and market quality

Richie Ma (UIUC), Brian Peterson (UIUC), Teresa Serra (UIUC)

Abstract: As trading has transitioned to electronic platforms, both traders and exchanges have invested in technologies that reduce trading latency. Yet little is known about how exchange processing latency affects market quality or whether its effects differ across market participants. Using message data from the Chicago Mercantile Exchange (CME), we examine these effects and their distribution between liquidity providers and liquidity takers. To address endogeneity, we exploit cross-commodity processing congestion arising from the shared order-processing system as an instrument for exchange latency. We find that lower exchange latency primarily benefits liquidity providers by increasing market-making revenues while reducing adverse selection costs, but can increase the immediate trading costs borne by liquidity takers. Our findings also reveal a congestion-based externality across commodity markets and highlight the importance of processing capacity in exchange design.

October 8 2026, 12 PM ET

Firm Dynamics and Private Credit

Jared Rutner (UCLA), Theodore Naff (UCLA)

Abstract: Private credit has emerged as the fastest growing source of firm financing globally, representing as much as one third of non-investment grade corporate debt in the United States. This paper studies how private credit shapes firm dynamics and credit allocation by constructing a novel database from the largest private credit data sources and U.S. Census microdata. Using a synthetic control identification strategy, we find that private credit induces an up-or-out dynamic for borrowing firms by increasing the likelihood of firm exit but also raising employment and innovation among surviving firms. The gains among survivors are driven by the relaxation of borrowing constraints implying segmentation with other financing sources. The increased likelihood of exit stems from active lender credit allocation rather than ex-ante firm risk. Private credit lenders' industry specialization drives these outcomes, suggesting specialized knowledge improves screening. We develop a structural model to explain this implied segmentation, whereby high-risk, high-reward firms sort into private credit. This sorting emerges as an equilibrium outcome of optimal leverage choice across the firm risk distribution. 

October 15 2026, 12 PM ET

When Is Aggregate Peer Information More Informative?

Kanying Xu (University of Vaasa, Finland)

Abstract: I show that the informativeness of aggregate peer signals depends on the information span of the peer set. To proxy information span empirically, I construct Peer Information Dispersion (PID) from the distribution of analyst-linked peer exposure across industries. I document a non-monotonic pattern: peer signals are more informative about future profitability when peers are moderately dispersed across industries. This informativeness arises from aggregating individually weak but economically relevant signals beyond historical common components. At moderate dispersion, peer signals are associated with stronger short-term price responses, little subsequent return drift, and greater convergence in analyst beliefs. 

October 22 2026, 12 PM ET

The Market Value of Technological Spillovers

Xinyu Cao (UBC)

Abstract: Does the market price technological spillovers? If so, what determines the spillover value of innovation? I construct a patent-level measure of technological spillovers from peer firms’ equity reactions to focal-firm patent grants, using U.S. patents from 1926 to 2023. Peer returns increase with technological similarity to newly granted patents, while the absolute magnitude of peer reactions predicts forward citations. Market-valued spillover exposure also predicts long-run growth in output and employment, particularly in R&D-intensive sectors. Exposure through technological similarity predicts positive growth, whereas exposure through product-market similarity predicts persistently lower growth. Private patent value passes through to the aggregate valuation of publicly traded sector peers. This pass-through is larger for breakthrough patents, process patents, and technologies in rapidly evolving fields. It is attenuated by market power and financial constraints, while network centrality and technological proximity strengthen it. Measured pass-through is also stronger when the industry and patenting firm are more salient. Overall, the findings establish a market-based measure of technological spillovers, identify their economic determinants, and show how investor attention shapes their recognition in prices.

October 29 2026, 12 PM ET

Misallocation in Banking

Robin Yifan Luo (U Washington)

Abstract: This paper studies how market power distorts the allocation of deposits and loans across banks. Banking complicates the allocation problem because customer demand and bank costs connect the two sides of the balance sheet. We develop and structurally estimate an oligopolistic banking model that measures the welfare gains from reallocating fixed aggregate deposits and loans across institutions. Efficiency requires the allocation of deposits and loans to equalize each side's marginal social surplus across banks, taking their interaction into account. Using U.S. bank data from 1986 through 2021, we estimate that annual welfare losses remain between \$1.3 and \$3.3 billion in 2019 dollars, while their share of sample banks' aggregate net income declines from an average of 7.2 percent through 2006 to 2.2 percent thereafter. The loan side contributes more, while the deposit-loan interaction offsets a substantial share because efficient reallocations often expand one side of a bank and contract the other. We then apply the framework to bank mergers. After completion, surviving acquirers move farther from the efficient marginal-surplus benchmarks, while the merging parties' combined welfare loss declines by \$3.7 million on average. The two patterns can coexist because the welfare loss from misallocation depends not only on the dispersion of the marginal-surplus wedges but on how much banking activity they distort. Furthermore, holding the structural estimates fixed in 2021, we find that subsequent deposit reallocation increasingly moves against the efficient direction, while loan reallocation moves with it. The framework extends beyond bank market power to other sources of marginal-surplus dispersion, including cost wedges across banks, and to other industries in which demand or production links multiple products.

November 12 2026, 12 PM ET

Debt Relief and the Reallocation of Household Labor and Capital

Naman Nishesh (UNC Chapel Hill)

Abstract: I study two large farm-loan waivers that forgave agricultural debt for households in two Indian states in 2014. Using rich bank microdata and quasi-random variation in debt-relief eligibility among otherwise similar farming households,  I examine how relieving legacy debt changes the allocation of household labor and capital across activities. Debt relief does not revive borrowing for the indebted farm. Instead, beneficiary households reduce their reliance on distant wage employment sustained through temporary internal migration, redirect borrowing from farm credit toward locally originated personal and small-business credit, and start more formally registered local non-farm businesses. Districts more exposed to relief also experience greater business formation and higher economic activity. These findings speak to a broader development puzzle: household labor and capital in developing economies remain tied to low-productivity occupations despite the dramatic expansion of credit. The results identify legacy household debt as a financial friction on the reallocation of labor and capital across activities, and show that debt relief can activate this reallocation and support structural change within the household. 

November 19 2026, 12 PM ET

Privacy Capital

Runyu Qi (Swiss Finance Institute & USI Lugano)

Abstract: Privacy is the governance of personal data firms hold and use in production. In this paper, I show that privacy is capital, beyond compliance obligation. I construct the first firm-year measure of privacy capital via a hybrid-LLM approach from privacy policies. Exploiting the 2018-2023 regulatory wave, I provide causal evidence that investment in privacy pays. A one-standard-deviation within-firm increase in privacy capital raises asset turnover by 0.06 standard deviations and ROA by 0.10 standard deviations. Effects are more pronounced for collection-intensive, sharing-intensive, and consumer-facing firms. The mechanism is consistent with governed data being utilized more productively. A simple model rationalizes this seemingly counterintuitive mechanism. Firms over-accumulate data to protect informational advantage, and common regulations let every firm cut back at once. The market initially discounts privacy capital, consistent with concerns that privacy constrains data use and growth opportunities. As its productive benefits become apparent, investors gradually correct this assessment and the discount narrows. Findings carry implications for the ongoing regulatory debate around privacy in the AI era. Privacy regulation imposes real costs, but it can also induce productive capital formation.

Dec 3 2026, 12 PM ET

The Fiscal Spillovers of Firm Uncertainty: Tax Structure and State Financing

Tianchen (Hugo) Zhao (Maryland)

Abstract: TBD 

Dec 10 2026, 12 PM ET

Equity Term Structure and the Decline of the U.S. Long-Term Treasury Premium

Lewis Kang (Iowa)

Abstract: I examine the causes of the U.S. long-term Treasury Premium—measured as covered interest parity deviations against other sovereign risk-free currencies—using a framework that combines (1) the equity term structure and (2) idiosyncratic cash-flow shocks identified through a granular instrumental variables approach. While the search for a strong instrument for equity cash flows was ultimately unsuccessful, the estimation results (excluding residual channels) indicate that variation in the long-term Treasury Premium is driven primarily by the supply channel (≈ 62%), followed by quantitative easing (≈ 25%), and cash-flow–driven equity returns (≈ 11%). Foreign demand for U.S. Treasuries and discount-rate movements play only minor roles, each contributing less than 2%. These findings are preliminary but highlight the dominant roles of Treasury supply and QE. Identifying a robust cash-flow instrument—potentially using firm-level markups within a duration-based framework—may further improve our understanding of how long-duration equity interacts with the long-term Treasury Premium.