Anthony Waikel

Assistant Professor of Finance

UMass Dartmouth, Charlton College of Business

Senior Research Fellow, FDIC

The Credit Consequences of Parental Cosigning on Mortgages,

with Hua Kiefer (link)

Under review

Parental cosigning on mortgages is a rapidly growing response to declining housing affordability. Using administrative data linking mortgage records to quarterly credit reports, we compare intergenerational borrowers to propensity score matched solo borrowers around mortgage origination. Intergenerational borrowers purchase more expensive homes in weaker neighborhoods, pay higher rates, and refinance less often even when in the money. Yet they default less because the parent acts as a backstop that keeps the mortgage current. On average, cosigning does not generate spillovers onto non-mortgage debt, but this average masks variation in the child's independent financial capacity. When the child could have qualified alone, the parent lowers mortgage default risk with no excess credit card strain. When the child is constrained, the parent enables a mortgage the child cannot independently sustain, and the resulting overextension leads to elevated credit card debt, higher delinquency, and larger credit score declines. Parental cosigning amplifies the child's financial position, providing security to those who are viable and enabling overreach for those who are not.

Figure on the left: Credit card delinquency around mortgage origination for those who needed a parent to obtain a mortgage (green line) and those who cosigned with a parent but could have qualified independently (blue line).

Presentations: FDIC CFR Seminar (2025), Interagency Risk Quantification Forum (2025), Southern Finance Association Annual Meeting (2025), Financial Management Association Annual Meeting (2025), Federal Reserve Supervisory Research Forum (2025), Eastern Finance Association Annual Meeting (2026)

Lending to Internet Strangers: Screening and Monitoring under Borrower Anonymity,

with Filipe Correia and António Martins (link)

Under review

We study online informal lending among anonymous individuals conducted without contracts, collateral, or legal enforcement. Using data on requests, funding, performance, and matched surveys, we show that pseudonymous identities build trust through repeat borrowing and reputation through verified repayment. Higher prices substitute credit history for first-time borrowers, increasing the chances of funding. Within funded loans, we observe a positive price-default gradient. Overlap in borrowers’ and lenders’ online activity predicts both funding and repayment, suggesting that shared culture substitutes for geographic or social proximity. Connectedness matters for ex-ante screening rather than ex-post monitoring. This market intermediates millions, and profits concentrate among few lenders.

Figure on the left: on the top, average lender returns sequentially removing the top lenders. On the bottom, default rate by decile of promised interest.

Presentations: Future Finance and Economics Association Conference (2023), Southwest Finance Association Annual Meeting (2024, coauthor), Boulder Summer Conference on Consumer Financial Decision Making (2024, coauthor), Brazilian Econometrics Meeting (2024, coauthor), American Finance Association Annual Meeting (PhD Poster Session 2023), FDIC Consumer Research Symposium (2024), Eastern Finance Association Annual Meeting (2025, coauthor), FDIC Bank Research Conference (2025), CEPR European Workshop on Household Finance (2026, coauthor)

Incentivizing Retail Traders: Evidence from Daily High-Water Marks on a Social Trading Platform (link)

with Justin Mohr

Fintech platforms have influenced consumer behavior and introduced `gamified' interfaces that alter retail investor attention. A new innovation in this space is social trading platforms, which allow retail investors to manage investable portfolios and pair that visibility with performance pay that looks like an institutional high water mark contract. I study a social trading platform that pays retail portfolio managers a cash bonus every day their fund closes above its previous high closing point (high water mark). Using 3.6 million trades from 5,000 funds, I employ a differences-in-differences design around each bonus to show that achieving a bonus generates a one day return spike of 1.6 percentage points above the previous day, but these gains immediately disappear. This spike is costly and managers create it by selling recent winners to lock in the bonus, but sacrifice future upside. A counterfactual analysis reveals that 63% of funds would realize higher alpha and 57% would collect additional bonuses by not trading at all. On average, traders destroy 2.5% of fund value around each event. The evidence shows that daily high water mark incentives draw retail traders' attention, amplify short term trading focus, and leave both traders and their investors worse off.

Figure on the left: Differences-in-Differences result around achieving a performance bonus.

Presentations: FDIC Internal Seminar (2024), Southwest Finance Association Annual Meeting (2025, 2026), Southern Finance Association Annual Meeting (2025, 2026), Financial Management Association Annual Meeting (2026)

Fund Manager Skill of Retail Investors,

with Daniel Rettl and Arjun Goel

Presentations: Eastern Finance Association Annual Meeting (2026), Financial Management Association European Conference (2026, coauthor), Financial Management Association Annual Meeting (2026)

The Dynamic Effect of Static Fee Caps,

with Spencer Stone

News Reactions and Information Networks Among Retail Traders,

with Miguel Puertas

The Role of Collateral in Credit Card Markets,

with Hua Kiefer

Presentations: Financial Management Association Early Ideas (2025)

Online Financing without FinTech: Evidence from Online Informal Loans during the Pandemic, 

with Filipe Correia and António Martins

Journal of Economics and Business (link)

We present the first comprehensive dataset on an online informal micro-lending community. These informal loans are small, short duration, and high-cost. Using our unique micro data, and the Covid-19 pandemic as a laboratory, we uncover different types of information contained on loan terms and on the narratives of market participants. First, loan terms reflect the aggregate economic context of borrowers and lenders. Second, narratives among market participants contain additional and timely information about aggregate and individual borrower circumstances. Third, lenders imperfectly screen on both loan terms and narrative information. These findings highlight the role of data in FinTech. Transparency on micro-loans can improve the efficiency of the credit market, democratizing access to finance for borrowers, while protecting lenders. 

Figure on the left: term structure of interest rates of informal loans.