Between March and August 2020, S&P and Moody’s downgraded approximately 25% of collateral feeding into CLOs and only 2% of tranche values, with rating actions concentrating in junior tranches. Both S&P and Moody’s modeling indicate that the impacts should have been considerably larger, especially for higher-rated tranches. Neither changes in correlation nor the accumulation of pre-COVID-19 protective cushions can explain the downgrade asymmetry on upper tranches. Instead, CLO managers repositioned their collateral pools to dampen the negative credit shock and rating agencies incorporated qualitative adjustments in their CLO ratings. Important potential policy and market implications from these findings are discussed.

Pandemic fraud is geographically concentrated and stimulated local purchases, with effects on prices. Recipients of fraudulent Paycheck Protection Program (PPP) funds significantly increased their home purchasing rate compared to recipients of non-fraudulent PPP funds, and house prices in high-fraud ZIP codes increased 5.8 percentage points more than in low-fraud ZIP codes within the same county. In a horse race, pandemic fraud is one of the largest and most robust factors explaining house price appreciation during COVID. ZIP codes with fraud also experienced heightened vehicle purchases and other consumer spending in 2020-21, with a return to normal in 2022.

Commercial loan valuations crucially depend on accurate loan income, but underwritten income on commercial mortgage‐backed securities (CMBS) loans is commonly overstated relative to actual property income. Consistent with these differences being originator‐specific, income overstatement in CMBS 2.0 deals varies widely and persistently across originators, is priced by originators, is related across property types within an originator, is predictable ex ante, and is accompanied by inflation of past financials. Risk retention and associated regulation had no discernible effect on income overstatement. Originator income overstatement is highly predictive of pre‐ and COVID‐period loan distress. Overall, recent market stresses reveal large systemic differences in underwriting standards across originators.

This paper examines apparent fraud among securitized nonagency loans using three indicators: unreported second liens, owner occupancy misreporting, and appraisal overstatements. We find that around 48% of loans exhibited at least one indicator of misrepresentation. Surprisingly, misreporting is similar in both low and full documentation loans and is associated with a 51% higher likelihood of delinquency. Two-thirds of loans with unreported second liens had the same originator issuing both the first and second lien. Misrepresentations in MBS pools can explain substantial cross-sectional differences in future losses. Losses were predictable and initiating from apparent fraud by MBS underwriters and loan originators.

Fraud indicators within the Paycheck Protection Program (PPP), a major COVID relief program, are highly geographically concentrated. ZIP codes and counties with high rates of suspicious PPP loans are strongly socially connected, with evidence that fraud spreads spatially over time through social networks. Individuals in suspicious social media groups have higher rates of PPP fraud, and socially connected ZIP codes frequently use the same specific FinTech lenders, consistent with social networks influencing detailed loan decisions. Our findings suggest that more proactive data analysis is needed for fraud prevention, detection, and prosecution to prevent the social spread of fraudulent schemes.

This paper investigates whether Tether, a digital currency pegged to the U.S. dollar, influenced Bitcoin and other cryptocurrency prices during the 2017 boom. Using algorithms to analyze blockchain data, we find that purchases with Tether are timed following market downturns and result in sizable increases in Bitcoin prices. The flow is attributable to one entity, clusters below round prices, induces asymmetric autocorrelations in Bitcoin, and suggests insufficient Tether reserves before month‐ends. Rather than demand from cash investors, these patterns are most consistent with the supply‐based hypothesis of unbacked digital money inflating cryptocurrency prices.

Ten years after the financial crisis, the central question of what explains the rise and fall in house prices remains unresolved. We provide a unified framework to examine four excess credit supply variables and three speculation variables that have been proposed in the literature. Credit supply variables, particularly subprime share and worse originator share, strongly relate to future zip-code-level house price changes in the boom and bust, whereas none of the speculation variables consistently relate to house prices within MSAs. Pre-trends, supply elasticity, and depressed areas suggest these relations are not driven by lenders anticipating house price growth.

This paper examines whether employees involved in residential mortgage-backed security (RMBS) securitization experienced internal and external labor market consequences relative to similar non-RMBS employees in the same banks and why. Senior RMBS bankers experienced similar levels of job retention, promotion, and external job opportunities. Even signers of RMBS deals with high loss and misreporting rates or deals implicated in lawsuits experienced no adverse internal or external labor market outcomes. These findings are likely not explained by targeted or delayed employee discipline, small legal fines, or protection due to pending litigation but are consistent with implicit upper-management approval of RMBS activities.

Municipal bonds exhibit considerable retail pricing variation, even for same‐size trades of the same bond on the same day, and even from the same dealer. Markups vary widely across dealers. Trading strongly clusters on eighth price increments, and clustered trades exhibit higher markups. Yields are often lowered to just above salient numbers. Machine learning estimates exploiting the richness of the data show that dealers that use strategic pricing have systematically higher markups. Recent Municipal Securities Rulemaking Board rules have had only a limited impact on markups. While a subset of dealers focus on best execution, many dealers appear focused on opportunistic pricing.

In the $793 billion Paycheck Protection Program, we examine metrics related to potential misreporting including nonregistered businesses, multiple businesses at residential addresses, abnormally high implied compensation per employee, and large inconsistencies with jobs reported in another government program. These measures consistently concentrate in certain FinTech lenders and are cross‐verified by seven additional measures. FinTech market share increased significantly over time, and suspicious lending by FinTechs in 2021 is four times the level at the start of the program. Suspicious loans are being overwhelmingly forgiven at rates similar to other loans.