Finance Research Letters最新文献

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Labor market frictions for female workers and corporate innovation

IF 7.4 2区经济学 Q1 BUSINESS, FINANCE

Finance Research Letters

Pub Date : 2025-03-03 DOI: 10.1016/j.frl.2025.107093

Hyuksoon Lim

I investigate the impact of labor market frictions for female workers on corporate innovation. Following the adoption of state-level paid family leave acts, which exogenously facilitate labor market participation of female employees, firms headquartered in affected states show significant increases in their innovation relative to unaffected firms. This effect is stronger for firms more reliant on a skilled workforce, in less tight local labor markets, with lower female employment, and that have higher female turnover. These findings support my hypothesis that the adoption of paid family leave acts fosters corporate innovation by improving talent allocation through an expanded labor supply of female workers. Overall, my results imply that labor market frictions for working mothers inhibit corporate innovation.

引用次数: 0

Airline stock market reaction to CrowdStrike IT outage: An event study analysis

IF 7.4 2区经济学 Q1 BUSINESS, FINANCE

Finance Research Letters

Pub Date : 2025-03-03 DOI: 10.1016/j.frl.2025.107145

João Costa , Susana Cró , Nuno Moutinho , António Miguel Martins

This study investigates the short-term market effect of CrowdStrike IT outage in the airline industry. Using an event study methodology, we evidence that airline stocks respond significantly negatively to the technology disruption within two days before and after the event day. IT disruptions, by creating friction in daily operations, such as broken schedules, delayed or cancelled flights, negative externalities, and customer dissatisfaction, lead to loss of value for airlines. The results also show that the most affected airlines are those from main CrowdStrike customers countries (mainly non-Asian countries) and an irrelevance of the business model. Finally, the extent of the stock market's response to the CrowdStrike IT outage is influenced by other airline characteristics such as profitability, size, leverage, and cyber risk rating.

本研究探讨了 CrowdStrike IT 中断对航空业的短期市场影响。利用事件研究方法，我们证明航空公司股票在事件日前后两天内对技术中断做出了显著的负面反应。信息技术中断会给日常运营带来摩擦，如航班时刻表中断、航班延误或取消、负面外部效应和客户不满，从而导致航空公司的价值损失。研究结果还表明，受影响最大的航空公司来自 CrowdStrike 的主要客户国家（主要是非亚洲国家），而且商业模式与之无关。最后，股票市场对 CrowdStrike IT 故障的反应程度受到其他航空公司特征的影响，如盈利能力、规模、杠杆率和网络风险评级。

引用次数: 0

The integration of technology and finance and corporate innovation boundary

IF 7.4 2区经济学 Q1 BUSINESS, FINANCE

Finance Research Letters

Pub Date : 2025-03-03 DOI: 10.1016/j.frl.2025.107135

Jian Huang , Cheng Guo , Siyu Yan

This study investigates how integrated technology-finance initiatives influence corporate innovation, focusing on China's Pilot Policy Promoting the Integration of Technology and Finance (PPPITF) from 2010 to 2022. Analyzing over 19,000 firm-year observations, the research finds that PPPITF significantly boosts innovation productivity in pilot regions. Mediation analysis reveals that the policy mitigates financing constraints and accelerates digital transformation, fostering synergies that enhance organizational innovation capabilities. Through causal relationships validated by rigorous testing, the study highlights how integrated policy frameworks can overcome barriers to financial accessibility and technological development, offering valuable insights for policymakers aiming to stimulate innovation in emerging markets.

引用次数: 0

Macroeconomic factors, industrial enterprises, and debt default prediction: Based on the VAR-GRU model

IF 7.4 2区经济学 Q1 BUSINESS, FINANCE

Finance Research Letters

Pub Date : 2025-03-03 DOI: 10.1016/j.frl.2025.107122

Zhenqing Liu , Yi Luo , Mohan Duan

This study uses a dynamic factor model to construct predictive factors and applies a machine learning-based vector autoregressive model to predict the possibility of corporate bond defaults. The vector autoregressive (VAR) model mainly examines the dynamic interaction relationships among multiple variables, so as to explain the dynamic impacts of various economic shocks on economic variables. It mainly studies the relationships among endogenous variables. Endogenous variables are those variables that are involved in the model and determined within the model system. Exogenous variables, on the other hand, are variables determined by factors outside the model. The Gated Recurrent Unit (GRU), which is a type of Recurrent Neural Network (RNN), can address issues such as the inability of RNNs to have long-term memory and the gradients in backpropagation. It is relatively easy to train. According to data from March 2014 to November 2021, the relevant findings are twofold. 1) A regulatory-based stress test is a crucial tool for measuring the financial sector's resilience in response to challenging macroeconomic conditions. 2) Macroeconomic conditions that may seem unrealistic during economic booms are now often used by regulators as benchmarks for evaluating the losses and capital requirements for market and credit portfolios.

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引用次数: 0

AT-FinGPT: Financial risk prediction via an audio-text large language model

IF 7.4 2区经济学 Q1 BUSINESS, FINANCE

Finance Research Letters

Pub Date : 2025-03-03 DOI: 10.1016/j.frl.2025.106967

Yingnan Liu , Ningbo Bu , Zhiqiang Li , Yongmin Zhang , Zhenyu Zhao

Financial risk prediction is crucial for investment decision-making. Traditional machine learning methods are limited by their structures and parameter size, which hinders their generalizability and effectiveness. Large language models (LLMs), which are pretrained with very large dataset and many GPUs have recently shown promising improvements in financial risk prediction. Despite this progress, most existing financial LLMs mainly rely on textual data for training and prediction, overlooking audio data and limiting analysis to text summarization. However, natural language processing studies have shown that audio from CEOs’ quarterly earnings calls is crucial for financial risk prediction. In this work, we introduce an audio–text LLM named AT-FinGPT, which fuses financial audio data and summarization texts for financial risk prediction. The empirical experimental results show that AT-FinGPT is superior to most advanced methods. Through an ablation study, we demonstrate that different data sources can facilitate financial risk assessment and discuss the effectiveness of each part in the AT-FinGPT model.

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引用次数: 0

Crowdfunding business models through the lens of sustainable development: A taxonomy for backers and funders

IF 7.4 2区经济学 Q1 BUSINESS, FINANCE

Finance Research Letters

Pub Date : 2025-03-03 DOI: 10.1016/j.frl.2025.107084

Roberto Cerchione, Giuseppe Liccardo, Renato Passaro

Sustainable entrepreneurship has emerged as a key driver in addressing environmental and societal challenges through innovation. However, sustainable ventures often struggle to secure funding due to the perceived trade-off between financial returns and sustainability goals. This paper, through a systematic literature review, proposes a taxonomy of crowdfunding (CF) business models linking backers' motivations to the environmental, social and governance (ESG) dimensions of the projects. This taxonomy, highlighting the importance of aligning CF business model with the specific sustainable project objectives, offers entrepreneurs the opportunity to effectively support their innovative and sustainable ideas through a strategically appropriate approach.

引用次数: 0

The role of associated risk in predicting financial distress: A case study of listed agricultural companies in China

IF 7.4 2区经济学 Q1 BUSINESS, FINANCE

Finance Research Letters

Pub Date : 2025-03-02 DOI: 10.1016/j.frl.2025.107125

Wanjuan Zhang, Jing Wang

This study investigates the predictive capacity of associated risk for financial distress among listed agricultural companies in China. Seven models, including statistical, machine learning, and ensemble methods, are used to evaluate the contribution of associated risk information. Our findings show that incorporating associated risk significantly enhances model performance, reducing misclassification rates by 0.1 %-3.1 % for healthy companies and 10.8 %-40.6 % for distressed companies, with Random Forest achieving the highest accuracy (0.9523). By incorporating associated risk, the ability of models to identify financially distressed companies is improved. Effective risk identification reduces the accumulation and outbreak of systemic financial risks, providing valuable insights for banking regulatory agencies.

引用次数: 0

Impact of high-speed rail operation, ESG performance, and financial performance of listed tourism companies

IF 7.4 2区经济学 Q1 BUSINESS, FINANCE

Finance Research Letters

Pub Date : 2025-03-01 DOI: 10.1016/j.frl.2025.107071

Xintong Yan , Daibo Xiao , Hokai Chan , Guoxiong Zeng , Renxing Wei

This study examines the relationship between the opening of high-speed rail (HSR); environmental, social, and governance (ESG) performance, and the financial outcomes of publicly traded tourism companies using data from 2012 to 2022. Empirical analysis reveals that both the opening of HSR and high ESG performance positively impact the financial performance of these listed tourism entities. The efficacy of managerial processes acts as a moderating factor in the relationship between the opening of HSR services and the financial performance of listed tourism companies, with a differential impact on the financial success of state-controlled versus privately owned tourism enterprises.

引用次数: 0

The nonlinear impact of economic policy uncertainty on corporate green total factor productivity

IF 7.4 2区经济学 Q1 BUSINESS, FINANCE

Finance Research Letters

Pub Date : 2025-03-01 DOI: 10.1016/j.frl.2025.107045

Siqi Zou, Yang Long

This study investigates the nonlinear impact of economic policy uncertainty (EPU) on corporate green total factor productivity (GTFP), examining the moderating role of intelligent transformation (IT). Analyzing firm-level data from Chinese listed companies (2010–2022), we document an inverted U-shaped relationship between EPU and GTFP, where moderate uncertainty catalyzes environmental innovation while excessive uncertainty impedes it. IT significantly enhances firms' adaptive capacity, amplifying positive effects of manageable uncertainty while mitigating adverse impacts of high uncertainty. Heterogeneity analysis reveals distinct patterns across industry types, with high-tech and non-pollution-intensive sectors demonstrating greater resilience to policy volatility. These findings advance uncertainty management theory and provide actionable insights for environmental policy formulation.

引用次数: 0

The green premium in sustainable fintech: Cross-country evidence from crowdfunding

IF 7.4 2区经济学 Q1 BUSINESS, FINANCE

Finance Research Letters

Pub Date : 2025-02-28 DOI: 10.1016/j.frl.2025.107131

Xingyuan Yao

The integration of fintech and sustainable finance represents a significant evolution in financial practices. This study examines the "green premium" in crowdfunding, where sustainable projects receive excess funding. Leveraging a dataset of 13,458 projects from 167 countries and regions sourced from the Indiegogo platform, empirical analysis confirms the presence of a green premium, after controlling for various critical factors and conducting robustness checks. Notably, the magnitudes of the green premium exhibit variability across different regions and stages of development. Policymakers should consider introducing targeted financial incentives, fostering international cooperation, and promoting education to encourage broader participation and support sustainable development.

引用次数: 0

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