Pub Date : 2025-07-30DOI: 10.1016/j.jfineco.2025.104143
Iván Alfaro , Hoonsuk Park
Using daily banking and credit card data for thousands of households linked to U.S. publicly listed employers, we find novel evidence that firm-specific uncertainty persistently reduces future spending and spurs precautionary savings. A one-standard-deviation rise in option-implied firm volatility—akin to the S&P 500 VIX—predicts a $106 monthly spending drop (8 hours of wages) and a $193 increase in bank balances, reflecting notable cutbacks in typical non-durable goods and services. The mechanism operates through heightened household risks: firm uncertainty expands both income and consumption risk over the next year, with the largest effects among lower and top earners (notably the top 1%). Employers only partly shield earnings, while households only partly self-insulate consumption risk via smoothing channels. Detrimental uncertainty effects on households are stronger than firm stock price declines.
{"title":"Firm uncertainty and households: Spending, savings, and risks","authors":"Iván Alfaro , Hoonsuk Park","doi":"10.1016/j.jfineco.2025.104143","DOIUrl":"10.1016/j.jfineco.2025.104143","url":null,"abstract":"<div><div>Using daily banking and credit card data for thousands of households linked to U.S. publicly listed employers, we find novel evidence that firm-specific uncertainty persistently reduces future spending and spurs precautionary savings. A one-standard-deviation rise in option-implied firm volatility—akin to the S&P 500 VIX—predicts a $106 monthly spending drop (8 hours of wages) and a $193 increase in bank balances, reflecting notable cutbacks in typical non-durable goods and services. The mechanism operates through heightened household risks: firm uncertainty expands both income and consumption risk over the next year, with the largest effects among lower and top earners (notably the top 1%). Employers only partly shield earnings, while households only partly self-insulate consumption risk via smoothing channels. Detrimental uncertainty effects on households are stronger than firm stock price declines.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"172 ","pages":"Article 104143"},"PeriodicalIF":10.4,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144724706","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-29DOI: 10.1016/j.jfineco.2025.104132
Agostino Capponi , Ruizhe Jia , Kanye Ye Wang
The blockchain settlement layer facilitates systematic frontrunning, resulting in inefficient block-space allocation. Private transaction pools can reduce these inefficiencies and enhance welfare. However, full adoption is limited by misaligned incentives between users and validators. Validators are reluctant to forgo rents they earn from frontrunning – referred to as maximal extractable value – leading to a partial adoption equilibrium in which frontrunning persists. Our empirical analysis of Ethereum’s Flashbots private pool supports these findings: validators earn higher revenues, users facing greater frontrunning risk are more likely to use the private pool, and attackers’ cost-to-revenue ratios in private pools converge to one.
{"title":"Maximal extractable value and allocative inefficiencies in public blockchains","authors":"Agostino Capponi , Ruizhe Jia , Kanye Ye Wang","doi":"10.1016/j.jfineco.2025.104132","DOIUrl":"10.1016/j.jfineco.2025.104132","url":null,"abstract":"<div><div>The blockchain settlement layer facilitates systematic frontrunning, resulting in inefficient block-space allocation. Private transaction pools can reduce these inefficiencies and enhance welfare. However, full adoption is limited by misaligned incentives between users and validators. Validators are reluctant to forgo rents they earn from frontrunning – referred to as maximal extractable value – leading to a partial adoption equilibrium in which frontrunning persists. Our empirical analysis of Ethereum’s Flashbots private pool supports these findings: validators earn higher revenues, users facing greater frontrunning risk are more likely to use the private pool, and attackers’ cost-to-revenue ratios in private pools converge to one.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"172 ","pages":"Article 104132"},"PeriodicalIF":10.4,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144721158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-28DOI: 10.1016/j.jfineco.2025.104134
Darren Aiello , Asaf Bernstein , Mahyar Kargar , Ryan Lewis , Michael Schwert
We study how state pension windfalls affect property prices near state borders, where theory suggests real estate reflects the value of additional public resources. Windfalls, representing a source of state revenue about half the size of total taxes, provide economically significant and plausibly exogenous variation in fiscal conditions. We find that each dollar of pension asset returns increases border house prices by approximately two dollars, suggesting that governments allocate additional funds towards high-value projects or tax abatement rather than wasting incremental resources. Evidence of larger effects in financially constrained municipalities highlights how fiscal resources amplify welfare effects of economic shocks.
{"title":"The marginal value of public pension wealth: Evidence from border house prices","authors":"Darren Aiello , Asaf Bernstein , Mahyar Kargar , Ryan Lewis , Michael Schwert","doi":"10.1016/j.jfineco.2025.104134","DOIUrl":"10.1016/j.jfineco.2025.104134","url":null,"abstract":"<div><div>We study how state pension windfalls affect property prices near state borders, where theory suggests real estate reflects the value of additional public resources. Windfalls, representing a source of state revenue about half the size of total taxes, provide economically significant and plausibly exogenous variation in fiscal conditions. We find that each dollar of pension asset returns increases border house prices by approximately two dollars, suggesting that governments allocate additional funds towards high-value projects or tax abatement rather than wasting incremental resources. Evidence of larger effects in financially constrained municipalities highlights how fiscal resources amplify welfare effects of economic shocks.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"172 ","pages":"Article 104134"},"PeriodicalIF":10.4,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144714098","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-28DOI: 10.1016/j.jfineco.2025.104140
Aaron Goodman , Indira Puri
We document a new anomaly that we prove standard preference models are unable to capture, regardless of functional form or parametric specification used. Analyzing trading behavior in the binary option market for retail investors, we find that market participants purchase binary options although strictly dominant bull spreads are available at lower prices: 15% of S&P index, 19% of gold, and 25% of silver trades violate no-dominance conditions consistently across three different asset classes. Buyers of dominated binaries lose on average 34% of the contract price by forgoing the dominating product. We prove that neither prospect theory nor ambiguity aversion nor other popular theoretical justifications for retail anomalies such as rational inattention and salience, can capture these results. We also test for, and reject, standard financial explanations including trading costs, liquidity, exchange fixed effects, and noise trading. We show that our results are consistent with retail investors valuing simple, easy-to-understand binary bets. Our work provides a theoretically-grounded empirical impetus for research in behavioral finance which goes beyond historically pervasive utility frameworks.
{"title":"Overvaluing simple bets: Evidence from the options market","authors":"Aaron Goodman , Indira Puri","doi":"10.1016/j.jfineco.2025.104140","DOIUrl":"10.1016/j.jfineco.2025.104140","url":null,"abstract":"<div><div>We document a new anomaly that we prove standard preference models are unable to capture, regardless of functional form or parametric specification used. Analyzing trading behavior in the binary option market for retail investors, we find that market participants purchase binary options although strictly dominant bull spreads are available at lower prices: 15% of S&P index, 19% of gold, and 25% of silver trades violate no-dominance conditions consistently across three different asset classes. Buyers of dominated binaries lose on average 34% of the contract price by forgoing the dominating product. We prove that neither prospect theory nor ambiguity aversion nor other popular theoretical justifications for retail anomalies such as rational inattention and salience, can capture these results. We also test for, and reject, standard financial explanations including trading costs, liquidity, exchange fixed effects, and noise trading. We show that our results are consistent with retail investors valuing simple, easy-to-understand binary bets. Our work provides a theoretically-grounded empirical impetus for research in behavioral finance which goes beyond historically pervasive utility frameworks.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"172 ","pages":"Article 104140"},"PeriodicalIF":10.4,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144714097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-28DOI: 10.1016/j.jfineco.2025.104141
Gustavo Manso , Alejandro Rivera , Hui (Grace) Wang , Han Xia
Unlike labor income, human capital is inseparable from individuals and does not completely accrue to creditors. Therefore, human capital investment is more resilient to “debt overhang” than labor supply. We develop a dynamic model displaying this difference. We find that while both labor supply and human capital investment are hump-shaped in household indebtedness, human capital investment declines less aggressively as indebtedness builds up. Importantly, because human capital is only valuable when households expect to supply labor, the greater reduction in labor supply due to debt overhang back-propagates into ex-ante human capital investment. We provide empirical support for the model.
{"title":"Household debt overhang and human capital investment","authors":"Gustavo Manso , Alejandro Rivera , Hui (Grace) Wang , Han Xia","doi":"10.1016/j.jfineco.2025.104141","DOIUrl":"10.1016/j.jfineco.2025.104141","url":null,"abstract":"<div><div>Unlike labor income, human capital is inseparable from individuals and does not completely accrue to creditors. Therefore, human capital investment is more resilient to “debt overhang” than labor supply. We develop a dynamic model displaying this difference. We find that while both labor supply and human capital investment are hump-shaped in household indebtedness, human capital investment declines less aggressively as indebtedness builds up. Importantly, because human capital is only valuable when households expect to supply labor, the greater reduction in labor supply due to debt overhang back-propagates into ex-ante human capital investment. We provide empirical support for the model.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"172 ","pages":"Article 104141"},"PeriodicalIF":10.4,"publicationDate":"2025-07-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144714099","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-26DOI: 10.1016/j.jfineco.2025.104144
Toomas Laarits , Marco Sammon
Retail investors trade hard-to-value stocks. We document a large and persistent spread in the stock-level intensity of retail trading, even allowing for known biases in the attribution of retail trades. Stocks with a high share of retail-initiated trades exhibit higher shares of intangible capital, longer duration cash flows, and a higher likelihood of being mispriced. Consistent with retail-favored stocks being harder to value, we document that these stocks are less sensitive to earnings news and more sensitive to retail order imbalances. Such segmentation of trading intensity arises in a model where informed investors face a trade-off between the benefits of hiding their trades within noisy retail investor order flow and the costs of producing information about the fundamentals of hard-to-value stocks.
{"title":"The retail habitat","authors":"Toomas Laarits , Marco Sammon","doi":"10.1016/j.jfineco.2025.104144","DOIUrl":"10.1016/j.jfineco.2025.104144","url":null,"abstract":"<div><div>Retail investors trade hard-to-value stocks. We document a large and persistent spread in the stock-level intensity of retail trading, even allowing for known biases in the attribution of retail trades. Stocks with a high share of retail-initiated trades exhibit higher shares of intangible capital, longer duration cash flows, and a higher likelihood of being mispriced. Consistent with retail-favored stocks being harder to value, we document that these stocks are less sensitive to earnings news and more sensitive to retail order imbalances. Such segmentation of trading intensity arises in a model where informed investors face a trade-off between the benefits of hiding their trades within noisy retail investor order flow and the costs of producing information about the fundamentals of hard-to-value stocks.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"172 ","pages":"Article 104144"},"PeriodicalIF":10.4,"publicationDate":"2025-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144713118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-25DOI: 10.1016/j.jfineco.2025.104146
Pengfei Sui , Baolian Wang
We examine how stakes affect investor behaviors. In our unique setting, investors trade stocks in real accounts using their own money and simultaneously in a simulated setting. Our real-world within-investor estimation shows that investors exhibit stronger biases and perform worse in higher-stakes real accounts than in lower-stakes simulated accounts. Investors exhibit strong biases in both types of accounts, and the biases in both are strongly positively correlated. Such behavioral consistency suggests that low-stakes experiments are informative about real-world behaviors. Using additional account-level datasets, we demonstrate external validity by documenting a stronger (reverse) disposition effect on stocks (funds) with greater portfolio weights.
{"title":"Stakes and investor behaviors","authors":"Pengfei Sui , Baolian Wang","doi":"10.1016/j.jfineco.2025.104146","DOIUrl":"10.1016/j.jfineco.2025.104146","url":null,"abstract":"<div><div>We examine how stakes affect investor behaviors. In our unique setting, investors trade stocks in real accounts using their own money and simultaneously in a simulated setting. Our real-world within-investor estimation shows that investors exhibit stronger biases and perform worse in higher-stakes real accounts than in lower-stakes simulated accounts. Investors exhibit strong biases in both types of accounts, and the biases in both are strongly positively correlated. Such behavioral consistency suggests that low-stakes experiments are informative about real-world behaviors. Using additional account-level datasets, we demonstrate external validity by documenting a stronger (reverse) disposition effect on stocks (funds) with greater portfolio weights.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"172 ","pages":"Article 104146"},"PeriodicalIF":10.4,"publicationDate":"2025-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144703221","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-23DOI: 10.1016/j.jfineco.2025.104137
Carlo Altavilla , Andrew Ellul , Marco Pagano , Andrea Polo , Thomas Vlassopoulos
Do banks extending government-guaranteed loans simultaneously reduce their risk exposure to firms? Using unique euro-area credit register data and the COVID-19 guarantee programs as a laboratory, we find that 1 euro of guaranteed lending was associated with a reduction of 28 cents in non-guaranteed credit, relative to other banks lending to the same firm. Substitution was highest for riskier and smaller firms in more affected sectors and for stronger banks. Nevertheless, banks offered cheaper credit and longer maturities to guaranteed loan recipients, especially more fragile ones. This improvement in lending terms is the flipside of credit substitution.
{"title":"Loan guarantees, bank lending and credit risk reallocation","authors":"Carlo Altavilla , Andrew Ellul , Marco Pagano , Andrea Polo , Thomas Vlassopoulos","doi":"10.1016/j.jfineco.2025.104137","DOIUrl":"10.1016/j.jfineco.2025.104137","url":null,"abstract":"<div><div>Do banks extending government-guaranteed loans simultaneously reduce their risk exposure to firms? Using unique euro-area credit register data and the COVID-19 guarantee programs as a laboratory, we find that 1 euro of guaranteed lending was associated with a reduction of 28 cents in non-guaranteed credit, relative to other banks lending to the same firm. Substitution was highest for riskier and smaller firms in more affected sectors and for stronger banks. Nevertheless, banks offered cheaper credit and longer maturities to guaranteed loan recipients, especially more fragile ones. This improvement in lending terms is the flipside of credit substitution.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"172 ","pages":"Article 104137"},"PeriodicalIF":10.4,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687354","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-23DOI: 10.1016/j.jfineco.2025.104135
Kristian Blickle , Zhiguo He , Jing Huang , Cecilia Parlatore
We study how competition between asymmetrically informed banks, one specialized and one nonspecialized, affects loan prices. Both banks possess “general” signals regarding the borrower’s quality, which they use to screen loans. The specialized bank also has access to a “specialized” signal on which it bases its loan pricing. This private information-based pricing makes the specialized bank bid more aggressively, mitigating the informational rent effect that gives it monopolistic power. Our findings explain why loans from specialized lenders feature lower interest rates and better ex post performance. Supporting empirical evidence emphasizes the role of specialized information in shaping credit market outcomes.
{"title":"Information-based pricing in specialized lending","authors":"Kristian Blickle , Zhiguo He , Jing Huang , Cecilia Parlatore","doi":"10.1016/j.jfineco.2025.104135","DOIUrl":"10.1016/j.jfineco.2025.104135","url":null,"abstract":"<div><div>We study how competition between asymmetrically informed banks, one specialized and one nonspecialized, affects loan prices. Both banks possess “general” signals regarding the borrower’s quality, which they use to screen loans. The specialized bank also has access to a “specialized” signal on which it bases its loan pricing. This private information-based pricing makes the specialized bank bid more aggressively, mitigating the informational rent effect that gives it monopolistic power. Our findings explain why loans from specialized lenders feature lower interest rates and better ex post performance. Supporting empirical evidence emphasizes the role of specialized information in shaping credit market outcomes.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"172 ","pages":"Article 104135"},"PeriodicalIF":10.4,"publicationDate":"2025-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687353","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-07-22DOI: 10.1016/j.jfineco.2025.104138
Bin Li , Alberto G. Rossi , Xuemin (Sterling) Yan , Lingling Zheng
We construct real-time machine learning strategies based on a “universe” of fundamental signals. The out-of-sample performance of these strategies is economically meaningful and statistically significant, but considerably weaker than those documented by prior studies that use curated sets of signals as predictors. Strategies based on a simple recursive ranking of each signal’s past performance also yield substantially better out-of-sample performance. We find qualitatively similar results when examining past-return-based signals. Our results underscore the key role of feature engineering and, more broadly, inductive biases in enhancing the economic benefits of machine learning investment strategies.
{"title":"Machine learning from a “Universe” of signals: The role of feature engineering","authors":"Bin Li , Alberto G. Rossi , Xuemin (Sterling) Yan , Lingling Zheng","doi":"10.1016/j.jfineco.2025.104138","DOIUrl":"10.1016/j.jfineco.2025.104138","url":null,"abstract":"<div><div>We construct real-time machine learning strategies based on a “universe” of fundamental signals. The out-of-sample performance of these strategies is economically meaningful and statistically significant, but considerably weaker than those documented by prior studies that use curated sets of signals as predictors. Strategies based on a simple recursive ranking of each signal’s past performance also yield substantially better out-of-sample performance. We find qualitatively similar results when examining past-return-based signals. Our results underscore the key role of feature engineering and, more broadly, inductive biases in enhancing the economic benefits of machine learning investment strategies.</div></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"172 ","pages":"Article 104138"},"PeriodicalIF":10.4,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144680204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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