Pub Date : 2025-04-22DOI: 10.1016/j.frl.2025.107381
Sascha Tobias Wengerek, André Uhde, Benjamin Hippert
This study analyzes the impact of tariff imposition announcements on the stock prices of 1,194 U.S. companies during the first Trump administration, using a unique sample of 4,624 announcements made by or against the U.S. between January 2018 and August 2019. We find that tariff announcements lead to negative (cumulative) average abnormal stock returns. These negative wealth effects occur regardless of whether the Trump administration imposes safeguard tariffs to protect domestic industries or foreign countries announce retaliatory tariffs. Moreover, the adverse impact is primarily driven by announcements involving China, with variations linked to sector-specific, tariff, trade, and firm characteristics.
{"title":"Share price reactions to tariff imposition announcements during the first Trump administration","authors":"Sascha Tobias Wengerek, André Uhde, Benjamin Hippert","doi":"10.1016/j.frl.2025.107381","DOIUrl":"10.1016/j.frl.2025.107381","url":null,"abstract":"<div><div>This study analyzes the impact of tariff imposition announcements on the stock prices of 1,194 U.S. companies during the first Trump administration, using a unique sample of 4,624 announcements made by or against the U.S. between January 2018 and August 2019. We find that tariff announcements lead to negative (cumulative) average abnormal stock returns. These negative wealth effects occur regardless of whether the Trump administration imposes safeguard tariffs to protect domestic industries or foreign countries announce retaliatory tariffs. Moreover, the adverse impact is primarily driven by announcements involving China, with variations linked to sector-specific, tariff, trade, and firm characteristics.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"80 ","pages":"Article 107381"},"PeriodicalIF":7.4,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143870548","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}
Pub Date : 2025-04-22DOI: 10.1016/j.frl.2025.107462
Ruoyu Fan , Ziming Ren
This study examines the connection between CEOs’ inside debt holdings and corporate ESG performance. Using a sample of publicly listed Chinese firms from 2013 to 2023, we provide strong evidence that inside debt positively influences corporate ESG performance, though this effect is diminished by the presence of large shareholders. Our analysis also shows that CEO inside debt improves ESG performance by lowering debt financing costs and enhancing the quality of financial reporting. These findings remain consistent across various sensitivity and endogeneity tests. Overall, this research makes a meaningful contribution to the rapidly expanding literature on inside debt and ESG.
{"title":"Effects of CEO inside debt on corporate ESG behavior: role of major shareholders","authors":"Ruoyu Fan , Ziming Ren","doi":"10.1016/j.frl.2025.107462","DOIUrl":"10.1016/j.frl.2025.107462","url":null,"abstract":"<div><div>This study examines the connection between CEOs’ inside debt holdings and corporate ESG performance. Using a sample of publicly listed Chinese firms from 2013 to 2023, we provide strong evidence that inside debt positively influences corporate ESG performance, though this effect is diminished by the presence of large shareholders. Our analysis also shows that CEO inside debt improves ESG performance by lowering debt financing costs and enhancing the quality of financial reporting. These findings remain consistent across various sensitivity and endogeneity tests. Overall, this research makes a meaningful contribution to the rapidly expanding literature on inside debt and ESG.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"81 ","pages":"Article 107462"},"PeriodicalIF":7.4,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868216","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}
Pub Date : 2025-04-22DOI: 10.1016/j.frl.2025.107464
Jin Yuan , Liwei Jin , Feng Lan
We study a Black–Litterman and multi-factor (BL-MF) fusion model that integrates equilibrium expected returns and investor views information from the Black–Litterman framework with the return-factor correlation information captured in the multi-factor model. The optimal estimator derived from our model improves accuracy in estimating expected returns and covariance matrix. We build optimal portfolios using our BL-MF model and benchmarks, adhering to both standard and criteria tailored for capturing tail risk with non-normal return distributions. Out-of-sample tests show our BL-MF portfolios outperform various benchmarks, and robustness checks validate this performance advantage, regardless of changes in sub-period, estimation window length or data frequency.
{"title":"A BL-MF fusion model for portfolio optimization: Incorporating the Black–Litterman solution into multi-factor model","authors":"Jin Yuan , Liwei Jin , Feng Lan","doi":"10.1016/j.frl.2025.107464","DOIUrl":"10.1016/j.frl.2025.107464","url":null,"abstract":"<div><div>We study a Black–Litterman and multi-factor (BL-MF) fusion model that integrates equilibrium expected returns and investor views information from the Black–Litterman framework with the return-factor correlation information captured in the multi-factor model. The optimal estimator derived from our model improves accuracy in estimating expected returns and covariance matrix. We build optimal portfolios using our BL-MF model and benchmarks, adhering to both standard and criteria tailored for capturing tail risk with non-normal return distributions. Out-of-sample tests show our BL-MF portfolios outperform various benchmarks, and robustness checks validate this performance advantage, regardless of changes in sub-period, estimation window length or data frequency.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"80 ","pages":"Article 107464"},"PeriodicalIF":7.4,"publicationDate":"2025-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143870549","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}
Pub Date : 2025-04-21DOI: 10.1016/j.frl.2025.107384
Masayasu Kanno
This study examines whether ESG performance contributes to default risk mitigation in firms issuing securities that comprise an ESG-ETF. This study estimates logistic regression models for the panel data. The model-free results show that the credit risk had reduced for eight ESG-ETFs, but not for eleven. In contrast, the model analysis results indicate that in 17 of 21 ESG-ETFs, ESG performance most effectively mitigates the deterioration of the creditworthiness of ESG-ETF’s constituent firms. This study provides an effective credit risk analysis methodology for selecting an ESG-ETF that comprises firms with better creditworthiness for investors and regulators.
{"title":"ESG-ETFs and the constituent firms’ default risk mitigation","authors":"Masayasu Kanno","doi":"10.1016/j.frl.2025.107384","DOIUrl":"10.1016/j.frl.2025.107384","url":null,"abstract":"<div><div>This study examines whether ESG performance contributes to default risk mitigation in firms issuing securities that comprise an ESG-ETF. This study estimates logistic regression models for the panel data. The model-free results show that the credit risk had reduced for eight ESG-ETFs, but not for eleven. In contrast, the model analysis results indicate that in 17 of 21 ESG-ETFs, ESG performance most effectively mitigates the deterioration of the creditworthiness of ESG-ETF’s constituent firms. This study provides an effective credit risk analysis methodology for selecting an ESG-ETF that comprises firms with better creditworthiness for investors and regulators.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"81 ","pages":"Article 107384"},"PeriodicalIF":7.4,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143874727","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}
Pub Date : 2025-04-21DOI: 10.1016/j.frl.2025.107458
Nan Jia , Hongli Zhang , Weigang Ma
This study examines the impact of local government debt on rural green economy transition through panel data analysis. The results show that there is an inverted U-shaped non-linear relationship between local government debt and rural green economy transition, with debt facilitating the transition at low rural development levels but negatively affecting it at high development levels. The level of rural development is an important threshold variable that influences the mechanism of action of debt. Rural capital allocation plays a mediating role at low levels of development, but the mediating effect is not significant at high levels of development. It is suggested that local governments should reasonably control the scale of debt according to the stage of rural development, optimise the allocation of funds, improve the efficiency of investment, and formulate fiscal policies in a phased manner, so as to promote the sustainable development of rural green economy.
{"title":"The impact of local government debt on rural green transformation","authors":"Nan Jia , Hongli Zhang , Weigang Ma","doi":"10.1016/j.frl.2025.107458","DOIUrl":"10.1016/j.frl.2025.107458","url":null,"abstract":"<div><div>This study examines the impact of local government debt on rural green economy transition through panel data analysis. The results show that there is an inverted U-shaped non-linear relationship between local government debt and rural green economy transition, with debt facilitating the transition at low rural development levels but negatively affecting it at high development levels. The level of rural development is an important threshold variable that influences the mechanism of action of debt. Rural capital allocation plays a mediating role at low levels of development, but the mediating effect is not significant at high levels of development. It is suggested that local governments should reasonably control the scale of debt according to the stage of rural development, optimise the allocation of funds, improve the efficiency of investment, and formulate fiscal policies in a phased manner, so as to promote the sustainable development of rural green economy.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"81 ","pages":"Article 107458"},"PeriodicalIF":7.4,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868214","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}
Pub Date : 2025-04-21DOI: 10.1016/j.frl.2025.107460
WenXue Zhang , Yuhao Tian , Zeyu Zhu
Based on data from non-financial listed companies in the Shanghai and Shenzhen A-share markets from 2010 to 2023, this paper systematically explores the impact of corporate excess cash holdings on stock price crash risk and its underlying mechanisms. The study finds a significant positive correlation between corporate excess cash and stock price crash risk, suggesting that excess cash may increase stock price volatility by exacerbating agency problems. Further analysis reveals that economic policy uncertainty plays a moderating role in this process: when uncertainty rises, it suppresses the aggravating effect of excess cash on stock price crash risk, highlighting the partial offsetting effect of precautionary demand on agency problems. Heterogeneity analysis shows that CEO duality significantly weakens the positive relationship between excess cash and stock price crash risk, indicating that improvements in internal governance structures can mitigate agency conflicts.
{"title":"Corporate excess cash, economic policy uncertainty and stock price crash risk","authors":"WenXue Zhang , Yuhao Tian , Zeyu Zhu","doi":"10.1016/j.frl.2025.107460","DOIUrl":"10.1016/j.frl.2025.107460","url":null,"abstract":"<div><div>Based on data from non-financial listed companies in the Shanghai and Shenzhen A-share markets from 2010 to 2023, this paper systematically explores the impact of corporate excess cash holdings on stock price crash risk and its underlying mechanisms. The study finds a significant positive correlation between corporate excess cash and stock price crash risk, suggesting that excess cash may increase stock price volatility by exacerbating agency problems. Further analysis reveals that economic policy uncertainty plays a moderating role in this process: when uncertainty rises, it suppresses the aggravating effect of excess cash on stock price crash risk, highlighting the partial offsetting effect of precautionary demand on agency problems. Heterogeneity analysis shows that CEO duality significantly weakens the positive relationship between excess cash and stock price crash risk, indicating that improvements in internal governance structures can mitigate agency conflicts.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"81 ","pages":"Article 107460"},"PeriodicalIF":7.4,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143868215","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}
Pub Date : 2025-04-21DOI: 10.1016/j.frl.2025.107401
David E. Bloom , Klaus Prettner , Jamel Saadaoui , Mario Veruete
How will ChatGPT and other forms of artificial intelligence (AI) affect the skill premium? To address this question, we propose a nested constant elasticity of substitution production function that distinguishes among three types of capital: traditional physical capital (machines, assembly lines), industrial robots, and AI. Following the literature, we assume that industrial robots predominantly substitute for low-skill workers, whereas AI mainly helps to perform the tasks of high-skill workers. We show that AI reduces the skill premium as long as it is more substitutable for high-skill workers than low-skill workers are for high-skill workers.
{"title":"Artificial intelligence and the skill premium","authors":"David E. Bloom , Klaus Prettner , Jamel Saadaoui , Mario Veruete","doi":"10.1016/j.frl.2025.107401","DOIUrl":"10.1016/j.frl.2025.107401","url":null,"abstract":"<div><div>How will ChatGPT and other forms of artificial intelligence (AI) affect the skill premium? To address this question, we propose a nested constant elasticity of substitution production function that distinguishes among three types of capital: traditional physical capital (machines, assembly lines), industrial robots, and AI. Following the literature, we assume that industrial robots predominantly substitute for low-skill workers, whereas AI mainly helps to perform the tasks of high-skill workers. We show that AI reduces the skill premium as long as it is more substitutable for high-skill workers than low-skill workers are for high-skill workers.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"81 ","pages":"Article 107401"},"PeriodicalIF":7.4,"publicationDate":"2025-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143874731","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}
Pub Date : 2025-04-19DOI: 10.1016/j.frl.2025.107454
Zhen Xi, Yichen Zhang, Jing Zhao
This paper investigates whether and why firms follow their customers and suppliers to adopt digital transformation (DT) strategies. Through textual analysis of quarterly conference calls, we find that firms adopt DT strategies following their suppliers and customers, indicating digital transformation cascades along the supply chain. Moreover, the DT alignment is stronger when focal firms face greater monitoring from “digital enthusiast” analysts and stronger digital transformation pressure from their industry peers. Additionally, long-term partners, firms from industries with advanced DT, and those centrally positioned within the supply chain network create a stronger ripple along the supply chain.
{"title":"Digital strategy ripples: Understanding the digital transformation cascade along the supply chain","authors":"Zhen Xi, Yichen Zhang, Jing Zhao","doi":"10.1016/j.frl.2025.107454","DOIUrl":"10.1016/j.frl.2025.107454","url":null,"abstract":"<div><div>This paper investigates whether and why firms follow their customers and suppliers to adopt digital transformation (DT) strategies. Through textual analysis of quarterly conference calls, we find that firms adopt DT strategies following their suppliers and customers, indicating digital transformation cascades along the supply chain. Moreover, the DT alignment is stronger when focal firms face greater monitoring from “digital enthusiast” analysts and stronger digital transformation pressure from their industry peers. Additionally, long-term partners, firms from industries with advanced DT, and those centrally positioned within the supply chain network create a stronger ripple along the supply chain.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"80 ","pages":"Article 107454"},"PeriodicalIF":7.4,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143870550","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}
Pub Date : 2025-04-19DOI: 10.1016/j.frl.2025.107447
Xing Yang
DeepSeek’s recent breakthrough has intensified the debate over global AI competition. Using real-time data from Yahoo Finance, I find strong evidence that U.S. AI firms respond positively to the release of the DeepSeek R1 model, contradicting media concerns that disruptive AI competition harms firm value. A heterogeneity analysis reveals that firms with fewer resources experience stronger initial gains but underperform their more resource-rich counterparts over longer event windows. Additionally, GPU providers faced negative market reactions, suggesting that cost-efficient AI models may reduce reliance on large-scale GPU infrastructure. This research provides timely insights into the evolving impact of AI competition on firm valuation and industry dynamics.
{"title":"AI competition and firm value: Evidence from DeepSeek’s disruption","authors":"Xing Yang","doi":"10.1016/j.frl.2025.107447","DOIUrl":"10.1016/j.frl.2025.107447","url":null,"abstract":"<div><div>DeepSeek’s recent breakthrough has intensified the debate over global AI competition. Using real-time data from Yahoo Finance, I find strong evidence that U.S. AI firms respond positively to the release of the DeepSeek R1 model, contradicting media concerns that disruptive AI competition harms firm value. A heterogeneity analysis reveals that firms with fewer resources experience stronger initial gains but underperform their more resource-rich counterparts over longer event windows. Additionally, GPU providers faced negative market reactions, suggesting that cost-efficient AI models may reduce reliance on large-scale GPU infrastructure. This research provides timely insights into the evolving impact of AI competition on firm valuation and industry dynamics.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"80 ","pages":"Article 107447"},"PeriodicalIF":7.4,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143864191","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}
Pub Date : 2025-04-19DOI: 10.1016/j.frl.2025.107378
Shuzhen Yang , Wenqing Zhang
The stochastic volatility inspired (SVI) model is widely used to fit the implied variance smile. Currently, most optimization algorithms for SVI models are strongly dependent on the input starting point. In this study, we develop an efficient iterative algorithm for the SVI model based on a fixed-point least-squares optimizer, further presenting the convergence results for this novel iterative algorithm under certain condition. The experimental evaluation results of our approach using market data demonstrate the advantages of the proposed fixed-point iterative algorithm over the Quasi-explicit SVI method.
{"title":"Fixed-point iterative algorithm for SVI model","authors":"Shuzhen Yang , Wenqing Zhang","doi":"10.1016/j.frl.2025.107378","DOIUrl":"10.1016/j.frl.2025.107378","url":null,"abstract":"<div><div>The stochastic volatility inspired (SVI) model is widely used to fit the implied variance smile. Currently, most optimization algorithms for SVI models are strongly dependent on the input starting point. In this study, we develop an efficient iterative algorithm for the SVI model based on a fixed-point least-squares optimizer, further presenting the convergence results for this novel iterative algorithm under certain condition. The experimental evaluation results of our approach using market data demonstrate the advantages of the proposed fixed-point iterative algorithm over the Quasi-explicit SVI method.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"80 ","pages":"Article 107378"},"PeriodicalIF":7.4,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143860505","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}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号