Charles J. Hadlock, Jing Huang, Paul Obermann, Joshua R. Pierce
{"title":"Protecting Your Friends: The Role of Connections in Division Manager Careers","authors":"Charles J. Hadlock, Jing Huang, Paul Obermann, Joshua R. Pierce","doi":"10.1017/s0022109024000334","DOIUrl":"https://doi.org/10.1017/s0022109024000334","url":null,"abstract":"<p>We find that division managers who are connected to the CEO are substantially less likely than others to depart from the firm and are more likely to be promoted. Connected managers are protected when performance is poor, and they display no special ability to improve performance given this protection. Connections matter more in weak governance/incentive environments, and the external labor market and stock market appear skeptical of connected managers’ talents. While much of the evidence suggests inefficient favoritism, connected managers are protected more in peripheral segments, suggesting a possible efficiency benefit in helping to resolve intrafirm information problems.</p>","PeriodicalId":48380,"journal":{"name":"Journal of Financial and Quantitative Analysis","volume":"219 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141885952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Variance Decomposition and Cryptocurrency Return Prediction","authors":"Suzanne S. Lee, Minho Wang","doi":"10.1017/s002210902400022x","DOIUrl":"https://doi.org/10.1017/s002210902400022x","url":null,"abstract":"<p>This article examines how realized variances predict cryptocurrency returns in the cross section using intraday data. We find that cryptocurrencies with higher variances exhibit lower returns in subsequent weeks. Decomposing total variances into signed jump and jump-robust variances reveals that the negative predictability is attributable to positive jump and jump-robust variances. The negative pricing effect is more pronounced for smaller cryptocurrencies with lower prices, less liquidity, more retail trading activities, and more positive sentiment. Our results suggest that cryptocurrency markets are unique because retail investors and preferences for lottery-like payoffs play important roles in the partial variance effects.</p>","PeriodicalId":48380,"journal":{"name":"Journal of Financial and Quantitative Analysis","volume":"46 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-04-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141866570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zsolt Katona, Marcus O. Painter, Panos N. Patatoukas, Jean Zeng
{"title":"On the Capital Market Consequences of Big Data: Evidence from Outer Space","authors":"Zsolt Katona, Marcus O. Painter, Panos N. Patatoukas, Jean Zeng","doi":"10.1017/s0022109023001448","DOIUrl":"https://doi.org/10.1017/s0022109023001448","url":null,"abstract":"We use the introduction of satellite coverage of major retailers to study the capital market implications of unequal access to big data. Satellite data enabled sophisticated investors with access to such data to formulate profitable trading strategies, especially by targeting the upcoming reports of retailers with bad news for the quarter. The introduction of satellite data led to more informed short-selling activity, less informed individual buying activity, and lower stock liquidity around the reports of retailers with satellite coverage. We conclude that unequal access to big data can increase information asymmetry among market participants without immediately enhancing price discovery.","PeriodicalId":48380,"journal":{"name":"Journal of Financial and Quantitative Analysis","volume":"1 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140571238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Financing Payouts","authors":"Joan Farre-Mensa, Roni Michaely, Martin Schmalz","doi":"10.1017/s0022109024000231","DOIUrl":"https://doi.org/10.1017/s0022109024000231","url":null,"abstract":"<p>We find that 43% of firms that make payouts also raise capital during the same year, resulting in 31% of aggregate payouts being externally financed, primarily with debt. Most financed payouts cannot be explained by payout smoothing in response to volatile earnings or investment (rather, they are the result of firms persistently setting payouts above free cash flow). In fact, 25% of aggregate payouts could not have been paid without the firms simultaneously raising capital. Profitable firms with moderate growth use debt-financed payouts to jointly manage their leverage and cash, thus highlighting the close relationship between payout and capital structure decisions.</p>","PeriodicalId":48380,"journal":{"name":"Journal of Financial and Quantitative Analysis","volume":"74 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141866569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Consumption Growth Persistence and the Stock–Bond Correlation","authors":"Christopher S. Jones, Sungjune Pyun","doi":"10.1017/s002210902400019x","DOIUrl":"https://doi.org/10.1017/s002210902400019x","url":null,"abstract":"<p>We consider a model in which the correlation between shocks to consumption and to expected future consumption growth is nonzero and varies over time. We validate this assumption empirically using the model’s implication that time variation in consumption growth persistence (CGP) drives the correlation between stock and bond returns. Our model implies that the stock–bond correlation is also related to the predictive relation between bond yields and future stock returns. Finally, we provide suggestive evidence that asset price fluctuations are the primary driver of changes in CGP.</p>","PeriodicalId":48380,"journal":{"name":"Journal of Financial and Quantitative Analysis","volume":"22 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141866522","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evolution of Debt Financing Toward Less-Regulated Financial Intermediaries in the United States","authors":"Isil Erel, Eduard Inozemtsev","doi":"10.1017/s0022109024000206","DOIUrl":"https://doi.org/10.1017/s0022109024000206","url":null,"abstract":"<p>Nonbank lenders have been playing an increasing role in supplying debt, especially after the Great Recession. How important are the distortions in the greater regulation of banks that differentially limit risk-taking across alternative providers of credit? How might the growing role of nonbanks in credit markets affect financial stability? This selective review addresses these questions and discusses how banks and nonbanks helped provide liquidity to the nonfinancial sector during the COVID-19 pandemic shock. We argue that tighter bank regulation has created incentives for nonbanks to increase their participation in credit markets, a trend that creates concerns about financial stability.</p>","PeriodicalId":48380,"journal":{"name":"Journal of Financial and Quantitative Analysis","volume":"205 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141866568","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bank Competition and Information Production","authors":"Filippo De Marco, Silvio Petriconi","doi":"10.1017/s0022109024000152","DOIUrl":"https://doi.org/10.1017/s0022109024000152","url":null,"abstract":"<p>We show that bank competition diminishes banks’ incentives to produce information about prospective borrowers. We exploit the deregulation of U.S. interstate branching as a shock to competition and use borrowers’ stock returns after loan announcements to measure bank information production. Positive loan announcement returns are reduced in states that deregulate interstate branching, especially for opaque and bank-dependent firms and smaller banks that rely on soft information. Existing (i.e., inside) banks reduce information production more than new (i.e., outside) banks after deregulation, suggesting that they do so to deter borrower poaching. Furthermore, the probability of a covenant violation increases following deregulation.</p>","PeriodicalId":48380,"journal":{"name":"Journal of Financial and Quantitative Analysis","volume":"146 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-02-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140926195","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"How Does Labor Mobility Affect Corporate Leverage and Investment?","authors":"Ali Sanati","doi":"10.1017/s0022109024000115","DOIUrl":"https://doi.org/10.1017/s0022109024000115","url":null,"abstract":"<p>I develop a dynamic model to investigate how labor mobility impacts firms’ decisions. In the model, firms make investment and financing decisions, hire labor with different skill and mobility levels, and set wages through bargaining. The model predicts that, in response to an increase in labor mobility, high-skill firms operate with lower financial leverage, become less responsive to investment opportunities, and invest at lower rates, while low-skill firms remain unaffected. I confirm these predictions in the data using shocks to workers’ mobility across firms. The results are useful in understanding the effects of labor mobility changes driven by government policies or technological shocks, such as the rise of remote work.</p>","PeriodicalId":48380,"journal":{"name":"Journal of Financial and Quantitative Analysis","volume":"44 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140926154","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Book-to-Market, Mispricing, and the Cross Section of Corporate Bond Returns","authors":"Söhnke M. Bartram, Mark Grinblatt, Yoshio Nozawa","doi":"10.1017/s0022109024000048","DOIUrl":"https://doi.org/10.1017/s0022109024000048","url":null,"abstract":"<p>Corporate bonds’ book-to-market ratios predict returns computed from transaction prices. Senior bonds (even investment grade) with the 20% highest ratios outperform the 20% lowest by 3%–4% annually after non-parametrically controlling for numerous liquidity, default, microstructure, and priced-risk attributes: yield-to-maturity, bid–ask spread, duration/maturity, credit spread/rating, past returns, coupon, size, age, industry, and structural model equity hedges. Spreads for all-bond samples are larger. An efficient bond market would not exhibit the observed decay in the ratio’s predictive efficacy with implementation delays, small yield-to-maturity spreads, or similar-sized spreads across bonds with differing risks. A methodological innovation avoids liquidity filters and censorship that bias returns.</p>","PeriodicalId":48380,"journal":{"name":"Journal of Financial and Quantitative Analysis","volume":"49 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-02-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141866571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Factor Model Comparisons with Conditioning Information","authors":"Wayne E. Ferson, Andrew F. Siegel, Junbo L. Wang","doi":"10.1017/s002210902400005x","DOIUrl":"https://doi.org/10.1017/s002210902400005x","url":null,"abstract":"<p>We develop methods for testing factor models when the weights in portfolios of factors and test assets can vary with lagged information. We derive and evaluate consistent standard errors and finite sample bias adjustments for unconditional maximum squared Sharpe ratios and their differences. Bias adjustment using a second-order approximation performs well. We derive optimal zero-beta rates for models with dynamically trading portfolios. Factor models’ Sharpe ratios are larger but standard test asset portfolios’ maximum Sharpe ratios are larger still when there is dynamic trading. As a result, most of the popular factor models are rejected.</p>","PeriodicalId":48380,"journal":{"name":"Journal of Financial and Quantitative Analysis","volume":"39 1","pages":""},"PeriodicalIF":3.9,"publicationDate":"2024-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140926153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}