Research

Municipal-Treasury Spreads and Local Stock Returns

Accepted at Journal of Financial and Quantitative Analysis

This study shows that municipal bond yields are informative about the risk exposures and expected returns of local firms. An investment strategy that buys (sells) firms located in states where the municipal-Treasury spread is high (low) earns a return that exceeds 0.35% per month. This return differential cannot be explained by limits-to-arbitrage, industry agglomeration, or a host of prominent asset-pricing characteristics. Rather, the municipal-Treasury spread predicts stock returns because it serves as an observable proxy of local fundamentals, such as labor productivity. Firms’ risk exposures are higher and state-level fundamentals are weaker in states with higher municipal-Treasury spreads.

Presented at: University of Michigan (2020), Washington University in St. Louis (2020), University of Georgia (2020), IU-Bloomington (2020), Purdue University (2020), University of Alberta (2020), University of South Carolina (2020), Cornerstone Research - NYC (2020), Federal Reserve Board (2020), Midwest FA (2020), Eastern FA (2020), Virtual Municipal Finance Workshop (2020), AFBC PhD Forum (2019), UNC-Chapel Hill (2019)

The Kuldeep Shastri Outstanding Doctoral Student Paper

SWFA Best Doctoral Student Paper in Investments

Investment Under Upstream and Downstream Uncertainty

With Gill Segal

The Journal of Finance, 2026, 81(1), 413–457. https://doi.org/10.1111/jofi.70010

- See the Internet Appendix and the Additional Notes here

- See Kenan Institute Business Insight

The impact of uncertainty shocks on firm-level economic activity depends on their origin in supply-chains. Upstream (downstream) uncertainty from suppliers (customers) is associated with variability over future input (output) prices. Consequently, a real-option production model with time-to-build suggests that only upstream uncertainty suppresses investment since upstream (downstream) uncertainty affects the shorter-run (longer-run). Consistently, production-network data show that upstream uncertainty affects firm-level outcomes negatively. Conversely, downstream uncertainty affects firm-level outcomes more weakly but positively. At the macro-level, these two uncertainties oppositely predict aggregate growth and asset prices. Overall, downstream uncertainty has an expansionary effect, in contrast to other facets of uncertainty.

Presented at: University of Rochester (2025), Pennsylvania State University (2024), University of Virginia (2024), ASSA (2024), SITE Macroeconomics of Uncertainty and Volatility (2023), SITE New Frontiers in Asset Pricing (2023), University of Iowa (2023), North Carolina State University (2023), CFEA (2022), FMA (2022), University of Western Australia (2022), Texas A&M Young Scholars Finance Consortium (2022), Midwest FA (2022), Eastern FA (2022), FMCG (2022), New Zealand Finance Meeting (2021), AFBC (2021), Northern FA (2021), Korea University (2021), Wabash River Finance Conference (2021), European Economic Association (2021), Indian School of Business Summer Research Conference (2021), IU-Bloomington (2021)

Best Paper Award at 2021 ISB Summer Research Conference

Best Paper in Asset Pricing -- Runner Up (2021 Financial Markets and Corporate Governance Conference)

WRDS Best Paper Award (2022 Eastern Finance Association Meeting)

Counterparty Risk: Implications for Network Linkages and Asset Prices

With Yunzhi Hu and Gill Segal

Review of Financial Studies, 2023, 36(2), 814–858. https://doi.org/10.1093/rfs/hhac044

- See the Internet Appendix and the Data for the R/S Spread (Updated through Dec-24) here

- See Kenan Institute Business Insight

We study the relation between trade credit, asset prices, and production-network linkages. Empirically, firms extending more trade credit earn 7.6% p.a. lower risk premia and maintain longer relationships with customers. Using a production-based model, we quantitatively explain these novel facts. Trade credit reduces the departure probability of high-quality customers, thereby reducing firms’ exposures to systematic costs incurred in finding new customers. The mechanism predicts that the aggregate amount of trade credit proxies for customer-search costs, and that suppliers with shorter-duration links to customers command higher expected returns. We confirm these and other novel predictions in the data.

Presented at: Western FA (2021), CICF (2021), World Symposium on Investment Research (2021), NBER SI Capital Market and the Economy (2020), SITE Asset Pricing, Macro Finance, and Computation (2020), European FA (2020), FIRS (2020), Kentucky Bourbon Conference (2020), UConn Finance Conference (2020), Boston College (2020), Northeastern University (2020), Ball State University (2020), Triangle Macro-Finance Workshop (2020), Midwest FA (2020), Conference in Corporate Policies and Asset Prices (2019), Kelley Finance Junior Conference (2019), CIRANO Conference on Networks in Trade and Finance (2019), UNC-Chapel Hill (2019)

The Utilization Premium

With Gill Segal

Management Science, 2024, 70(1), 207-224. https://doi.org/10.1287/mnsc.2022.4647

- See the Internet Appendix and the Code and Data here

We study the interaction of flexible capital utilization and depreciation for expected returns and investment of firms. Empirically, an investment strategy that buys (sells) equities with low (high) utilization rates earns 5% p.a. Utilization predicts excess returns beyond other production-based variables. We reconcile this novel utilization premium quantitatively using a production model. The model suggests that flexible utilization is important for matching the cross-sectional distribution of investment and stock prices jointly. A model without flexible utilization yields many counterfactuals that flexible utilization addresses by making depreciation fluctuate endogenously. Overall, utilization tightens the link between firms’ production and valuations.

Presented at: RCFS/RAPS Winter Conference (2020), ANU Asset Pricing Conference (2020), UT Dallas Finance Conference (2019), Northern FA (2019), Midwest FA (2019), UNC-Chapel Hill (2017)

A New Lease on Firm Behavior

With Matteo Binfarè, Robert Connolly, and Crocker Liu

Journal of Corporate Finance, 2025, 94, 102793 (Lead Article). https://doi.org/10.1016/j.jcorpfin.2025.102793

- See the ASC842 Leasing Data here

When firms have discretion in valuing their balance sheet debt, how do they make this valuation decision given its impact on firm value? Firms make extensive use of operating leases, but unlike other types of debt, their balance sheet value is set by the firm. Using novel information on operating leases, we examine firm behavior in valuing these leases. We find that 20% of firms report higher-than-expected rates, reflecting their cost of unsecured rather than collateralized borrowing. These firms have poor information quality, operate in competitive markets, and understate lease and debt ratios by 15%.

Presented at: University of Miami (2021), FMA (2021), FMCG (2021), Eastern FA (2021), Midwest FA (2021), Conference on Asia-Pacific Financial Markets (2020), University of Missouri (2020)

Best Paper in Accounting -- Runner Up (2021 Financial Markets and Corporate Governance Conference)

Real-time Forecasts of State and Local Government Budgets with an Application to COVID-19

With Eric Ghysels and Nazire Özkan

National Tax Journal, 2022, 75(4), 731–763. https://doi.org/10.1086/721844

- See the Internet Appendix here

Using a sample of the 48 contiguous US states, we consider the problem of forecasting state governments’ revenues and expenditures in real time using models that feature mixed-frequency data. We find that mixed-data sampling (MIDAS) regressions that predict low-frequency fiscal outcomes using high-frequency macroeconomic and financial market data outperform traditional fiscal forecasting models in both a relative and an absolute sense. We also consider an application of forecasting fiscal outcomes in the face of the economic uncertainty induced by the coronavirus pandemic. Overall, we show that MIDAS regressions provide a simple tool for predicting fiscal outcomes in real time.

Presented at: UNC-Chapel Hill (2017)

Uncertainty After Dark: Evidence from 19 Million Nights of Sleep

With Gill Segal and Chao Ying

Using minute-level wearable-device data on 51,191 adults from the National Institutes of Health (NIH), covering over 19 million person-nights, we show that sleep quality is a high-frequency biomarker of macroeconomic and financial uncertainty. Positive shocks to uncertainty reduce deep sleep and sleep efficiency for several nights–a “wake-and-see” effect that complements the classic “wait-and-see” channel. Heterogeneity is economically meaningful: effects are larger in higher-income areas, yet comparable across race, gender, and education. Finally, nights of unusually poor sleep–net of environmental or time-zone effects–predict lower next-day market liquidity and weaker opening-hour equity returns. Conversely, when worse-than-expected macro news is released before the market opens, better sleep is associated with more negative early session returns, consistent with improved market efficiency. These results connect uncertainty to a measurable human capital cost and reveal a two-way link between nightly physiology and market conditions.

Presented at: FSU Truist Beach Conference (2026), University of Kentucky Finance Conference (2026), Western FA (2026), CICF (2026), SITE Macroeconomics of Uncertainty and Volatility (2026, Scheduled), Northern FA (2026, Scheduled)

Speculation in the Age of Indexation

With Christian Heyerdahl-Larsen and Preetesh Kantak

Revise and resubmit at Journal of Monetary Economics

We study how investor speculation about common and stock-specific risks impacts asset prices in an economy with multiple assets and heterogeneous agents. Our theory predicts that disagreement-driven speculation on common (stock-specific) risk drives flows into (out of) portfolios exposed to common risk. Consequently, bets on the common component of returns become concentrated, amplifying volatility and reducing diversification benefits. We test these predictions using a novel empirical setting: exchange-traded funds. Consistent with our theory, we find that as common (i.e., ETF-level) speculation rises, indexes aligned with this common exposure attract more flows and exhibit greater volatility and intra-index return correlation.

Presented at: Spring Finance Workshop (2025), Midwest FA (2025), Northern FA (2024), Western FA (2024), Frontiers of Factor Investing Conference (2024), UNC Kenan-Flagler Finance Ph.D. Alumni Conference (2023), SFS Cavalcade (2022), UT Dallas Finance Conference (2022), UNSW Asset Pricing Workshop (2022), SAFE Asset Pricing Workshop (2022), CICF (2022), FMA Conference on Derivatives and Volatility (2022), SoFiE (2022), Federal Reserve Bank of St. Louis (2021), IU-Bloomington (2021)

The Relative Price Premium

With Christian Heyerdahl-Larsen, Preetesh Kantak, and Yun Joo An

This study shows that relative price dispersion impacts risk premia. Notably, firms associated with goods and services that have increased (decreased) in price relative to the headline inflation rate earn high (low) returns. We refer to this return spread of 0.88% per month as the relative price premium. We rationalize the premium via a consumption-based asset-pricing model that features imperfectly substitutable goods and an investor with preferences for the mix of goods consumed. As shocks to relative prices induce the investor to consume a suboptimal bundle of goods, high price dispersion signals bad times for the investor and the economy.

Presented at: FIRS (2026), UNC Kenan-Flagler Finance Ph.D. Alumni Conference (2026), Mid-Atlantic Research Conference in Finance (2026), University of Cincinnati (2025), Drexel University (2024), University of Alabama (2024), Northern FA (2024), SoFiE (2024), North American Summer Meeting of the Econometric Society (2024), McGill University (2024), HEC Montreal (2024), CIREQ-CMP Econometrics Conference in Honor of Eric Ghysels (2024), Finance Down Under (2024), Korea University / KAIST (2024), Federal Reserve Board (2023), UNSW Asset Pricing Workshop (2023), CICF (2023), SoFiE (2023), AiE Conference in Honor of Joon Y. Park (2023), Eastern FA (2023), UVA-Darden (2022), IU-Bloomington (2022)

Litzenberger Best Paper Award (2026 UNC Alumni Conference)

CFA Institute Asia-Pacific Research Exchange Best Paper Award (2024 FDU)

Risk from the Inside Out: Understanding Firm Risk through Employee News Consumption

With Fahiz Baba-Yara and Preetesh Kantak

- See the Firm-Level Attention Data here

We use employee news consumption to characterize firms’ exposures to macroeconomic risk, making use of data covering two billion employee-article interactions per day across millions of firms. We find that, in the time-series, employees consume more macroeconomic news following the onset of bad times. In the cross-section, firms whose employees were reading more macroeconomic news ex-ante are more exposed to changing economic conditions ex-post. Consistent with the notion that employee news consumption provides insights into firms’ risk exposures, we show that the more exposed firms hedge more, yet have higher costs of capital and subsequently lower investment and hiring rates.

Presented at: Northern FA (2025), Monash University (2025), RMIT (2025), Deakin University (2025), University of Wisconsin-Madison (2025), Texas A&M Young Scholars Finance Consortium (2025), McMaster University (2025), Santiago Finance Workshop (2024), Macro Finance Society (2024), Pre-SoFiE Conference (2024), CIREQ-CMP Econometrics Conference in Honor of Eric Ghysels (2024), University of Iowa Conference on Social Networks and Peer Effects (2024), Silicon Prairie Finance Conference (2024), USC Macro-Finance Reading Group (2024), ASU Sonoran Winter Finance Conference (2024), ASSA (2024), Millennium Management, LLC (2024), Financial Research Association (2023), NBER SI Big Data and High-Performance Computing for Financial Economics (2023), SITE Macroeconomics of Uncertainty and Volatility (2023), 5th Federal Reserve Board Conference on Nontraditional Data, Machine Learning, and Natural Language Processing in Macroeconomics (2023), UNC-Chapel Hill (2023), Bocconi University (2023), CFEA (2023), Midwest FA (2023), PanAgora Asset Management (2023), Dolomite Summer Finance Conference (2023), Bristol Financial Markets Conference (2023), FMA (2023), BI Norwegian (2022), IU-Bloomington (2022)

2023 Crowell Prize Finalist (PanAgora Asset Management)

Municipal Bond Yields and Local Economic Conditions [New draft coming soon]

This study shows that the municipal yield curve predicts local economic outcomes. Notably, higher municipal-Treasury spreads forecast lower coincident economic activity and lower gross state product in the future. These results are not only stronger among states with stricter balanced budget restrictions, but evidence from the inter-state trade network also shows that poor economic conditions in one state spill over to that state’s closer trade partners. Moreover, the current level of the municipal-Treasury spread also forecasts a state’’s future tax revenues. Overall, the results indicate that a state’s cost of municipal debt contains valuable information about the local economy’s trajectory.