Pub Date : 2026-01-30DOI: 10.1016/j.frl.2026.109590
Nutao Yu, Cao Peng, Kejin Chen
This paper takes listed companies on the Shanghai and Shenzhen Chinese A-share markets from year 2011 to 2022 as the research sample, quantifies government attention to new quality productive forces through the frequency of related terms in local government work reports, and examines its impact effect and mechanism on the labor income share within the jurisdiction. The study finds that the increase in government attention to new quality productive forces significantly raises the labor income share of enterprises, and this conclusion remains valid after a series of robustness tests. Mechanism testing reveals that government attention to new quality productive forces enhances the labor income share by promoting increased corporate R&D investment and human capital adjustments. Heterogeneity analysis finds that the promotion effect is more pronounced for enterprises that are non-state-owned, in the manufacturing sector, or located in high marketization regions. The conclusions of this paper can provide certain policy implications for the government to develop new quality productive forces and increase the labor income share of enterprises to some extent.
{"title":"How does government attention to new quality productive forces affect corporate labor income share?","authors":"Nutao Yu, Cao Peng, Kejin Chen","doi":"10.1016/j.frl.2026.109590","DOIUrl":"10.1016/j.frl.2026.109590","url":null,"abstract":"<div><div>This paper takes listed companies on the Shanghai and Shenzhen Chinese A-share markets from year 2011 to 2022 as the research sample, quantifies government attention to new quality productive forces through the frequency of related terms in local government work reports, and examines its impact effect and mechanism on the labor income share within the jurisdiction. The study finds that the increase in government attention to new quality productive forces significantly raises the labor income share of enterprises, and this conclusion remains valid after a series of robustness tests. Mechanism testing reveals that government attention to new quality productive forces enhances the labor income share by promoting increased corporate R&D investment and human capital adjustments. Heterogeneity analysis finds that the promotion effect is more pronounced for enterprises that are non-state-owned, in the manufacturing sector, or located in high marketization regions. The conclusions of this paper can provide certain policy implications for the government to develop new quality productive forces and increase the labor income share of enterprises to some extent.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"92 ","pages":"Article 109590"},"PeriodicalIF":6.9,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089524","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 : 2026-01-30DOI: 10.1016/j.frl.2026.109594
Dong Chen
Using data spanning 2011–2021 from a sample of Chinese A-share-listed firms, this study examines how digital leadership influences the efficiency of corporate labor investment. Notably, digital leadership enhances labor investment efficiency, and this relationship operates through two complementary mechanisms: improved strategic agility and enhanced information transparency. Contextual variations in findings show strong effects in non-state-owned enterprises (SOEs) and eastern regions with better developed digital infrastructures, offer valuable insights for enterprises optimizing human resource allocation through digital transformation, and provide policy implications for balanced regional digital development.
{"title":"How does digital leadership influence the efficiency of corporate labor investment?","authors":"Dong Chen","doi":"10.1016/j.frl.2026.109594","DOIUrl":"10.1016/j.frl.2026.109594","url":null,"abstract":"<div><div>Using data spanning 2011–2021 from a sample of Chinese A-share-listed firms, this study examines how digital leadership influences the efficiency of corporate labor investment. Notably, digital leadership enhances labor investment efficiency, and this relationship operates through two complementary mechanisms: improved strategic agility and enhanced information transparency. Contextual variations in findings show strong effects in non-state-owned enterprises (SOEs) and eastern regions with better developed digital infrastructures, offer valuable insights for enterprises optimizing human resource allocation through digital transformation, and provide policy implications for balanced regional digital development.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"92 ","pages":"Article 109594"},"PeriodicalIF":6.9,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089525","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 : 2026-01-30DOI: 10.1016/j.frl.2026.109593
Hong Chen , Yuheng Meng , Lifu Liu , Minrui Du
This paper uses data on Chinese A-share private listed companies from 2007 to 2023 to examine how state-owned capital participation in “reverse mixed-ownership reform” affects excess goodwill, from both the perspective of “articulated rules” and “unarticulated rules.” The empirical results show that state-owned capital participation significantly curbs excess goodwill in private enterprises, and this finding remains robust after a series of endogeneity and robustness checks. Mechanism tests suggest that the effect operates mainly through strengthened governance and information channels. Further analysis indicates that the inhibitory effect is more pronounced when industrial state-owned capital participates, and state-owned capital participation also significantly alleviates the risk of subsequent goodwill impairment. This paper develops a theoretical framework linking state-owned capital participation to excess goodwill in private enterprises, sheds light on the institutional logic underlying China’s “mixed-ownership reform,” and tells a Chinese story of complementary advantages among heterogeneous shareholders.
{"title":"How does state-owned capital participation suppress excess goodwill in private enterprises?","authors":"Hong Chen , Yuheng Meng , Lifu Liu , Minrui Du","doi":"10.1016/j.frl.2026.109593","DOIUrl":"10.1016/j.frl.2026.109593","url":null,"abstract":"<div><div>This paper uses data on Chinese A-share private listed companies from 2007 to 2023 to examine how state-owned capital participation in “reverse mixed-ownership reform” affects excess goodwill, from both the perspective of “articulated rules” and “unarticulated rules.” The empirical results show that state-owned capital participation significantly curbs excess goodwill in private enterprises, and this finding remains robust after a series of endogeneity and robustness checks. Mechanism tests suggest that the effect operates mainly through strengthened governance and information channels. Further analysis indicates that the inhibitory effect is more pronounced when industrial state-owned capital participates, and state-owned capital participation also significantly alleviates the risk of subsequent goodwill impairment. This paper develops a theoretical framework linking state-owned capital participation to excess goodwill in private enterprises, sheds light on the institutional logic underlying China’s “mixed-ownership reform,” and tells a Chinese story of complementary advantages among heterogeneous shareholders.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"92 ","pages":"Article 109593"},"PeriodicalIF":6.9,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089528","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 : 2026-01-30DOI: 10.1016/j.frl.2026.109579
Huiling Huang , Yixiang Tian
Green bond pricing is distorted by unpriced positive externalities, leading to suboptimal investment. To correct this market failure, we develop an integrated framework that incorporates green reputation, carbon quota trading, and subsidies to internalize these externalities. We quantify operational boundaries for these policy instruments, establishing a prioritized market-led, trading-regulated, subsidy-supported intervention sequence. Numerical results reveal a clear hierarchy: for low-cost projects, reputation mechanisms are sufficient for effective pricing. For projects with moderate costs, carbon quota trading becomes the dominant mechanism, while subsidies provide essential support for the highest-cost projects. This suggests that effective pricing depends on a targeted approach, leveraging different market and policy instruments according to the cost structure.
{"title":"Pricing Green Bonds Under Externalities: How do market signals and government intervention affect project emission reduction and bond pricing?","authors":"Huiling Huang , Yixiang Tian","doi":"10.1016/j.frl.2026.109579","DOIUrl":"10.1016/j.frl.2026.109579","url":null,"abstract":"<div><div>Green bond pricing is distorted by unpriced positive externalities, leading to suboptimal investment. To correct this market failure, we develop an integrated framework that incorporates green reputation, carbon quota trading, and subsidies to internalize these externalities. We quantify operational boundaries for these policy instruments, establishing a prioritized market-led, trading-regulated, subsidy-supported intervention sequence. Numerical results reveal a clear hierarchy: for low-cost projects, reputation mechanisms are sufficient for effective pricing. For projects with moderate costs, carbon quota trading becomes the dominant mechanism, while subsidies provide essential support for the highest-cost projects. This suggests that effective pricing depends on a targeted approach, leveraging different market and policy instruments according to the cost structure.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"92 ","pages":"Article 109579"},"PeriodicalIF":6.9,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146075702","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 : 2026-01-30DOI: 10.1016/j.frl.2026.109592
Yaodan Hu, Sirui Chen, Wen Zheng, Zhen Zhu
This study investigates whether local executives help curb corporate "Greenwashing" using a sample of China’s non-financial A-share listed firms over 2008–2022. Results indicate that firms led by local executives are significantly less likely to engage in greenwashing. This relationship holds under multiple robustness checks. Mechanism analysis reveals that the curbing effect is driven by executives' hometown identity, reputational pressure, and long-term decision-making. The results highlight the importance of informal-governance via executive regional ties in promoting credible environmental disclosure and reducing opportunistic environmental claims.
{"title":"Can local executives effectively curb corporate \"greenwashing\" ?","authors":"Yaodan Hu, Sirui Chen, Wen Zheng, Zhen Zhu","doi":"10.1016/j.frl.2026.109592","DOIUrl":"10.1016/j.frl.2026.109592","url":null,"abstract":"<div><div>This study investigates whether local executives help curb corporate \"Greenwashing\" using a sample of China’s non-financial A-share listed firms over 2008–2022. Results indicate that firms led by local executives are significantly less likely to engage in greenwashing. This relationship holds under multiple robustness checks. Mechanism analysis reveals that the curbing effect is driven by executives' hometown identity, reputational pressure, and long-term decision-making. The results highlight the importance of informal-governance via executive regional ties in promoting credible environmental disclosure and reducing opportunistic environmental claims.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"92 ","pages":"Article 109592"},"PeriodicalIF":6.9,"publicationDate":"2026-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146089526","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 : 2026-01-29DOI: 10.1016/j.frl.2026.109589
Haohua Liu, Qiang Pan
This study investigated the impact of digital finance on the supply chain resilience of manufacturing firms. The results indicate that digital finance significantly improves the supply chain resilience of manufacturing firms. Mechanistically, digital finance enhances the supply chain resilience of manufacturing firms through three channels: alleviating financing constraints, promoting digital transformation of firms, and boosting innovation capacity. Heterogeneity analysis suggests that this resilience-enhancing effect is more pronounced for large firms, firms with high financial risk, and firms in regions with improved digital infrastructure. The findings of this paper offer valuable insights into the relationship between digital finance and supply chain resilience, holding critical implications for both policymakers and corporate managers to formulate resilience strategies.
{"title":"Digital finance and supply chain resilience of manufacturing firms","authors":"Haohua Liu, Qiang Pan","doi":"10.1016/j.frl.2026.109589","DOIUrl":"10.1016/j.frl.2026.109589","url":null,"abstract":"<div><div>This study investigated the impact of digital finance on the supply chain resilience of manufacturing firms. The results indicate that digital finance significantly improves the supply chain resilience of manufacturing firms. Mechanistically, digital finance enhances the supply chain resilience of manufacturing firms through three channels: alleviating financing constraints, promoting digital transformation of firms, and boosting innovation capacity. Heterogeneity analysis suggests that this resilience-enhancing effect is more pronounced for large firms, firms with high financial risk, and firms in regions with improved digital infrastructure. The findings of this paper offer valuable insights into the relationship between digital finance and supply chain resilience, holding critical implications for both policymakers and corporate managers to formulate resilience strategies.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"92 ","pages":"Article 109589"},"PeriodicalIF":6.9,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071785","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 : 2026-01-29DOI: 10.1016/j.frl.2026.109588
An Thi Thuy Duong
This paper examines whether high ESG portfolios offer superior downside protection compared to low-ESG portfolios and the market conditions under which this advantage holds. Using annual ESG scores and daily U.S. stock returns (2018–2023), high- and low-ESG indices are constructed, and factor-neutral residual portfolios are derived after adjusting for Fama–French risk factors. A three-state Markov regime-switching model (MRSM) identifies low-, high-, and crash-volatility regimes, complemented by downside, Value-at-Risk (VaR), Conditional Value-at-Risk (CVaR), and Incremental CVaR (ICVaR) analyses. The results show that ESG integration enhances resilience but not returns: high-ESG portfolios display lower volatility and milder losses than low-ESG portfolios in non-crash regimes, while this advantage vanishes in crashes. Factor-neutral analysis attributes this resilience to reduced idiosyncratic risk rather than factor exposure. Downside and tail-risk measures further indicate that low-ESG portfolios amplify tail-risk. These results are robust to the battery of tests.
{"title":"ESG as a conditional risk buffer: Idiosyncratic volatility and tail losses across market regimes","authors":"An Thi Thuy Duong","doi":"10.1016/j.frl.2026.109588","DOIUrl":"10.1016/j.frl.2026.109588","url":null,"abstract":"<div><div>This paper examines whether high ESG portfolios offer superior downside protection compared to low-ESG portfolios and the market conditions under which this advantage holds. Using annual ESG scores and daily U.S. stock returns (2018–2023), high- and low-ESG indices are constructed, and factor-neutral residual portfolios are derived after adjusting for Fama–French risk factors. A three-state Markov regime-switching model (MRSM) identifies low-, high-, and crash-volatility regimes, complemented by downside, Value-at-Risk (VaR), Conditional Value-at-Risk (CVaR), and Incremental CVaR (ICVaR) analyses. The results show that ESG integration enhances resilience but not returns: high-ESG portfolios display lower volatility and milder losses than low-ESG portfolios in non-crash regimes, while this advantage vanishes in crashes. Factor-neutral analysis attributes this resilience to reduced idiosyncratic risk rather than factor exposure. Downside and tail-risk measures further indicate that low-ESG portfolios amplify tail-risk. These results are robust to the battery of tests.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"92 ","pages":"Article 109588"},"PeriodicalIF":6.9,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071787","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 : 2026-01-29DOI: 10.1016/j.frl.2026.109585
Jun Young Byun, Yosep Na, Jae Wook Song
This study investigates whether visual information embedded in stock charts contains economically meaningful signals for asset pricing. Using deep learning models trained on candlestick images, we construct predictive factors via convolutional neural networks (CNN) and vision transformers (ViT). The models generate monthly probabilities of future returns, transformed into double-sorted, value-weighted portfolios, and evaluated within a high-dimensional asset pricing framework. Employing the double-selection LASSO, we assess whether these image-driven factors contribute incremental pricing power beyond 161 established risk factors. The ViT-derived factor exhibits robust and statistically significant stochastic discount factor loadings, indicating that it captures a novel priced dimension of risk associated with visual market heuristics and trend saliency. It consistently delivers positive and economically meaningful return spreads across firm sizes, with superior Sharpe and Sortino ratios relative to standard benchmarks. In contrast, the CNN-based factor shows weaker performance, particularly among large-cap stocks, suggesting limited economic relevance despite statistical significance. Factor selection patterns reveal that ViT signals are linked to multiple economic channels (low-risk, profitability, and financing), while CNN signals primarily align with quality and safety characteristics. Overall, the results demonstrate that advanced deep learning can extract interpretable, orthogonal source of priced risk from chart images, enriching the empirical asset pricing landscape and highlighting the potential of computer vision as a tool for understanding market dynamics.
{"title":"From vision to value: Stock chart image-driven factors and their pricing power","authors":"Jun Young Byun, Yosep Na, Jae Wook Song","doi":"10.1016/j.frl.2026.109585","DOIUrl":"10.1016/j.frl.2026.109585","url":null,"abstract":"<div><div>This study investigates whether visual information embedded in stock charts contains economically meaningful signals for asset pricing. Using deep learning models trained on candlestick images, we construct predictive factors via convolutional neural networks (CNN) and vision transformers (ViT). The models generate monthly probabilities of future returns, transformed into double-sorted, value-weighted portfolios, and evaluated within a high-dimensional asset pricing framework. Employing the double-selection LASSO, we assess whether these image-driven factors contribute incremental pricing power beyond 161 established risk factors. The ViT-derived factor exhibits robust and statistically significant stochastic discount factor loadings, indicating that it captures a novel priced dimension of risk associated with visual market heuristics and trend saliency. It consistently delivers positive and economically meaningful return spreads across firm sizes, with superior Sharpe and Sortino ratios relative to standard benchmarks. In contrast, the CNN-based factor shows weaker performance, particularly among large-cap stocks, suggesting limited economic relevance despite statistical significance. Factor selection patterns reveal that ViT signals are linked to multiple economic channels (low-risk, profitability, and financing), while CNN signals primarily align with quality and safety characteristics. Overall, the results demonstrate that advanced deep learning can extract interpretable, orthogonal source of priced risk from chart images, enriching the empirical asset pricing landscape and highlighting the potential of computer vision as a tool for understanding market dynamics.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"92 ","pages":"Article 109585"},"PeriodicalIF":6.9,"publicationDate":"2026-01-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071788","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 : 2026-01-28DOI: 10.1016/j.frl.2026.109564
Omar Blanco-Arroyo , Vicente Esteve , María A. Prats
This study investigates the co-explosivity between Spain’s nominal house price index and the housing credit-to-GDP ratio over the period 1971–2024, with particular emphasis on the housing bubble years from 1998 to 2008. Applying the framework proposed by Chen et al. (2017), the analysis reveals an asymmetric relationship: house prices exhibit a stronger sensitivity to credit expansion than credit does to price increases, underscoring the disproportionate influence of credit on housing market dynamics. During the 1998–2008 bubble phase, the relationship becomes more symmetric, suggesting a feedback loop in which relaxed lending standards fueled housing demand, while rising prices reinforced further credit growth. This period is characterized by tighter coupling between the two variables, stronger co-movement, and faster correction dynamics—indicative of speculative lending behavior. The findings highlight the importance of monitoring credit conditions to better understand and manage housing market volatility.
{"title":"Co-moving systems with explosive regressors and time-varying volatility: Evidence from the Spanish housing market","authors":"Omar Blanco-Arroyo , Vicente Esteve , María A. Prats","doi":"10.1016/j.frl.2026.109564","DOIUrl":"10.1016/j.frl.2026.109564","url":null,"abstract":"<div><div>This study investigates the co-explosivity between Spain’s nominal house price index and the housing credit-to-GDP ratio over the period 1971–2024, with particular emphasis on the housing bubble years from 1998 to 2008. Applying the framework proposed by <span><span>Chen et al. (2017)</span></span>, the analysis reveals an asymmetric relationship: house prices exhibit a stronger sensitivity to credit expansion than credit does to price increases, underscoring the disproportionate influence of credit on housing market dynamics. During the 1998–2008 bubble phase, the relationship becomes more symmetric, suggesting a feedback loop in which relaxed lending standards fueled housing demand, while rising prices reinforced further credit growth. This period is characterized by tighter coupling between the two variables, stronger co-movement, and faster correction dynamics—indicative of speculative lending behavior. The findings highlight the importance of monitoring credit conditions to better understand and manage housing market volatility.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"92 ","pages":"Article 109564"},"PeriodicalIF":6.9,"publicationDate":"2026-01-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071790","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 : 2026-01-27DOI: 10.1016/j.frl.2026.109584
Elisa Giaretta, Francesco Zen
Artificial intelligence (AI) startups play a crucial role in technological and economic development, yet their financing mechanisms remain underexplored. This study examines the funding of AI startups, analyzing a dataset of 9,000 Italian innovative startups, including 588 AI-focused ventures. Results indicate that AI startups present better financial conditions than their peers, specifically greater liquidity ratio, solvency ratio, current ratio and interest coverage. Further analyses highlight the factors that may influence investment decisions, such as skilled employees, R&D intensity and a management team characterized by a greater presence of young people and a lower presence of women and foreigners.
{"title":"Artificial Intelligence startups and financial conditions: Evidence from Italy","authors":"Elisa Giaretta, Francesco Zen","doi":"10.1016/j.frl.2026.109584","DOIUrl":"10.1016/j.frl.2026.109584","url":null,"abstract":"<div><div>Artificial intelligence (AI) startups play a crucial role in technological and economic development, yet their financing mechanisms remain underexplored. This study examines the funding of AI startups, analyzing a dataset of 9,000 Italian innovative startups, including 588 AI-focused ventures. Results indicate that AI startups present better financial conditions than their peers, specifically greater liquidity ratio, solvency ratio, current ratio and interest coverage. Further analyses highlight the factors that may influence investment decisions, such as skilled employees, R&D intensity and a management team characterized by a greater presence of young people and a lower presence of women and foreigners.</div></div>","PeriodicalId":12167,"journal":{"name":"Finance Research Letters","volume":"92 ","pages":"Article 109584"},"PeriodicalIF":6.9,"publicationDate":"2026-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071484","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