Neveen Ahmed , Barbara Abou Tanos , Omar Farooq , Mohammed Bouaddi
{"title":"Economic policy uncertainty and active management: Evidence from SRI funds","authors":"Neveen Ahmed , Barbara Abou Tanos , Omar Farooq , Mohammed Bouaddi","doi":"10.1016/j.frl.2025.107339","DOIUrl":"10.1016/j.frl.2025.107339","url":null,"abstract":"<div><div>This study explores the impact of economic policy uncertainty (EPU) on the relationship between active management and the performance of socially responsible mutual funds. Using data on U.S. socially responsible funds, we show that active management is more valuable in periods characterized by high EPU. The findings are robust across different fund characteristics, active management metrics, EPU proxies, and fund performance measures. Our results are further validated using multiple estimation techniques. Additionally, funds that are younger, smaller, with higher expenses, lower turnover, and slower growth are more likely to benefit from active management as economic policy uncertainty increases.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"79 ","pages":"Article 107339"},"PeriodicalIF":7.4,"publicationDate":"2025-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143759642","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":"Can payday loan bans and financial literacy benefit consumers?","authors":"Eric McKee, Oscar Solis, Wei Zhang","doi":"10.1016/j.frl.2025.107326","DOIUrl":"10.1016/j.frl.2025.107326","url":null,"abstract":"<div><div>By exploiting variation in the payday loan availability induced by state-level regulation changes, we investigate the impact of payday loan bans on consumers’ credit outcomes and financial welfare. We find that consumers in states with new bans significantly reduced the usage of payday loans and alternative financial services (AFS) and experienced a lower likelihood of difficulty in paying bills and mortgages relative to those in other states. Furthermore, both the credit and welfare effects are stronger for consumers with lower levels of financial literacy. These individuals experienced greater reductions in payday loan and AFS usage, as well as economic hardship. In contrast, high-literacy consumers used payday loans less in the first place and derived fewer benefits from the bans. Our results highlight the important role of financial literacy in mitigating the adverse effects of payday loans.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"79 ","pages":"Article 107326"},"PeriodicalIF":7.4,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143759527","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":"The effect of financial advisor reputation on mergers and acquisitions performance","authors":"Yinhui Hao, Yan Zhou","doi":"10.1016/j.frl.2025.107281","DOIUrl":"10.1016/j.frl.2025.107281","url":null,"abstract":"<div><div>This study investigates the relationship between the reputation of financial advisors and the performance of mergers and acquisitions (M&A) among China's A-share listed companies over the 2012–2022 period. Our analysis of a sample of M&A and restructuring events reveals a significant positive association between the reputation of financial advisors and the success of M&A deals. Importantly, this positive relationship is found to be attenuated in cases involving shell listings. Additionally, we find that a higher degree of marketization enhances the positive impact of financial advisor reputation on M&A performance.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"79 ","pages":"Article 107281"},"PeriodicalIF":7.4,"publicationDate":"2025-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748664","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":"Green finance and micro-zone level carbon emissions","authors":"Peng Lu , Ziwei Wang , Yibo Liu","doi":"10.1016/j.frl.2025.107262","DOIUrl":"10.1016/j.frl.2025.107262","url":null,"abstract":"<div><div>We examine the impact of green finance on carbon emissions across urban, suburban, and rural zones via the geographic information system. We investigate that green finance only reduces carbon emissions in urban centers, with its effect varying across degrees of urbanization classifications (DUCs). Considering residual correlation among DUCs, we reveal that green finance facilitates transferring carbon emissions from urban to suburban zones. With the spatial weight matrix for emissions and the IV-GMM approach, we demonstrate that carbon emissions display spatial spillover effects within a city. Green finance may contribute to the relocation of emissions from urban centers to suburban zones.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"79 ","pages":"Article 107262"},"PeriodicalIF":7.4,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738808","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":"Shortages and machine-learning forecasting of oil returns volatility: 1900–2024","authors":"Onur Polat , Dhanashree Somani , Rangan Gupta , Sayar Karmakar","doi":"10.1016/j.frl.2025.107334","DOIUrl":"10.1016/j.frl.2025.107334","url":null,"abstract":"<div><div>The objective of this paper is to forecast the volatility of the West Texas Intermediate (WTI) oil returns over the monthly period of January 1900 to June 2024 by utilizing the information content of newspapers articles-based indexes shortages for the United States (US). We measure volatility as the inter-quantile range by fitting a Bayesian time-varying parameter quantile regression (TVP-QR) on oil returns. The TVP-QR is also used to estimate skewness, kurtosis, lower- and upper-tail risks, and we control for them in our forecasting model along with leverage. Based on the Lasso estimator to control for overparameterization, we find that the model with moments outperform the benchmark autoregressive model involving 12 lags of volatility. More importantly, the performance of the moments-based model improves further when we incorporate the aggregate metric of shortages and its sub-indexes, particularly those related to the industry and labor sectors. These findings carry significant implications for investors.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"79 ","pages":"Article 107334"},"PeriodicalIF":7.4,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The resilient power of CSR: Sustained risk reduction despite widespread ESG adoption","authors":"Jorge Merladet, Sara Lumbreras, Andrés Ramos","doi":"10.1016/j.frl.2025.107240","DOIUrl":"10.1016/j.frl.2025.107240","url":null,"abstract":"<div><div>This paper explores the role of CSR in risk mitigation within an increasingly ESG-focused environment. Using monthly data from 2016 to 2023, we employ several risk measures representing systematic, idiosyncratic and downside risks. Through comprehensive panel regression analysis, we reveal robust risk reduction effects across model specifications, contrasting with the mixed profitability outcomes reported in the literature. Notably, the risk mitigation effect is broad-based and intensifies as ESG adoption becomes widespread, challenging prevailing assumptions of diminishing impact. These results have significant implications for firm valuation and investor decision making.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"79 ","pages":"Article 107240"},"PeriodicalIF":7.4,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
F. Cesarone , A. Di Paolo , M. Bufalo , G. Orlando
{"title":"A benchmark-asset principal component factorization for index tracking on large investment universes","authors":"F. Cesarone , A. Di Paolo , M. Bufalo , G. Orlando","doi":"10.1016/j.frl.2025.107244","DOIUrl":"10.1016/j.frl.2025.107244","url":null,"abstract":"<div><div>This paper proposes an innovative methodology based on a benchmark-asset principal component factorization to determine a tracking portfolio that replicates the performance of a benchmark by investing in a subset of assets of a large investment universe. Our approach exploits the spectral decomposition of each benchmark-asset covariance matrix to formulate the tracking error, which is minimized by analyzing its eigenvalues. We present an in-depth comparison of several competing strategies on real-world data in terms of out-of-sample performance and computational efficiency. The empirical analysis highlights that our approach shows index tracking abilities similar to the optimization-based portfolio selection model but with lower turnover and faster running times of about four orders of magnitude. Furthermore, small replicating portfolios obtained by our method also provide investment performance comparable to the difficult-to-beat equally weighted portfolio.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"79 ","pages":"Article 107244"},"PeriodicalIF":7.4,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"How do enterprise big data applications mitigate asset mispricing?","authors":"Xiaolan Lin, Li Wang","doi":"10.1016/j.frl.2025.107256","DOIUrl":"10.1016/j.frl.2025.107256","url":null,"abstract":"<div><div>This paper examines the impact of enterprise big data applications on asset mispricing using data from 2011 to 2023. The findings reveal that big data applications play a crucial role in mitigating asset mispricing by strengthening internal control mechanisms and reducing information asymmetry. By leveraging big data, enterprises can enhance financial transparency and accuracy, leading to more informed investment decisions and a lower likelihood of asset mispricing. This study highlights the significance of big data in fostering a fairer and more efficient capital market.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"79 ","pages":"Article 107256"},"PeriodicalIF":7.4,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143714636","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}
Miaomiao Chui , Yinglong Zheng , Tao Peng , Dinghao Shi
{"title":"Impact of environmental regulation intensity and digital economy on regional environmental penalties","authors":"Miaomiao Chui , Yinglong Zheng , Tao Peng , Dinghao Shi","doi":"10.1016/j.frl.2025.107276","DOIUrl":"10.1016/j.frl.2025.107276","url":null,"abstract":"<div><div>By selecting data related to environmental protection and digital economy in 31 provinces and municipalities in China from 2010 to 2022 as the research sample, this study explores the interplay among environmental regulation intensity, digital economy, and regional environmental penalties. Findings indicate that increasingly stringent environmental regulations decrease regional environmental penalties. Furthermore, the advancement of digital financial inclusion as digital economy's indicator reveals its moderating effect on the relationship between environmental regulations and regional penalties, exhibiting variations across distinct regions. The extent of technological innovation has a similar effect on the relationship between environmental regulations and regional penalties, with notable differences across regions.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"79 ","pages":"Article 107276"},"PeriodicalIF":7.4,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143748625","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":"Supply network centrality and ESG performance: A resource dependence perspective","authors":"Siying Quan , Peng Cheng , Jia Zhai","doi":"10.1016/j.frl.2025.107322","DOIUrl":"10.1016/j.frl.2025.107322","url":null,"abstract":"<div><div>In this study, we examine the relationship between a firm's social capital measured by its centrality in the supply network and its environmental, social, and governance (ESG) performance. Using data from China's A-share firms, we apply resource dependence theory and show a negative correlation between in-degree centrality and ESG performance. Specifically, firms with greater social capital from suppliers tend to allocate fewer resources for enhancing ESG performance, especially when facing financial constraints or low investor protection, or if state-owned enterprises. This study enriches the ESG literature by integrating network-based variables and provides valuable insights into sustainable performance within supply networks.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"79 ","pages":"Article 107322"},"PeriodicalIF":7.4,"publicationDate":"2025-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143738807","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}