Global Finance Journal最新文献_第6页

Do clean energy stocks diversify the risk of FinTech stocks? Connectedness and portfolio implications 清洁能源股是否能分散金融科技股的风险？关联性和投资组合的影响

IF 5.5 2区经济学

Global Finance Journal Pub Date : 2024-07-19 DOI: 10.1016/j.gfj.2024.101019

Irene Henriques, Perry Sadorsky

{"title":"Do clean energy stocks diversify the risk of FinTech stocks? Connectedness and portfolio implications","authors":"Irene Henriques, Perry Sadorsky","doi":"10.1016/j.gfj.2024.101019","DOIUrl":"10.1016/j.gfj.2024.101019","url":null,"abstract":"<div><p>The FinTech sector is growing rapidly, prompting a need to explore effective investment diversification strategies for stocks in this sector. The existing literature has identified the benefits of using clean energy stocks to diversify stock portfolios and the purpose of this research is to estimate how useful clean energy stocks are for diversifying an investment in FinTech stocks. This study uses a QVAR model to estimate the dynamic return connectedness between FinTech stocks and clean energy stocks for the period September 2016 to April 2024. Total connectedness is time varying and is higher in the tails than at the median. The onset of the COVID-19 pandemic had a large but short-term impact on connectedness. Under normal market conditions, systemic risk increases by 3.5% per year. FinTech is a net transmitter of shocks to nuclear energy but is mostly unaffected by shocks from wind, solar, and nuclear energy stocks illustrating the diversification benefits of these sub-sectors. Portfolio analysis shows that adding solar, wind, and nuclear energy to a portfolio with FinTech can produce higher risk adjusted returns and lower drawdown than an investment solely in FinTech stocks. These results are robust across various portfolio rebalancing frequencies (daily, weekly, monthly). For example, a minimum connectedness portfolio rebalanced daily has an average annual return of 11% and a Sharpe ratio of 0.37. These values are higher than their respective values for an investment solely in FinTech stocks (5.4%, 0.11). Thus, clean energy stocks do provide diversification benefits for investments in FinTech stocks.</p></div>","PeriodicalId":46907,"journal":{"name":"Global Finance Journal","volume":"62 ","pages":"Article 101019"},"PeriodicalIF":5.5,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141728801","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}

引用次数: 0

Digital transformation and corporate risk taking: Evidence from China 数字化转型与企业风险承担：来自中国的证据

IF 5.5 2区经济学

Global Finance Journal Pub Date : 2024-07-19 DOI: 10.1016/j.gfj.2024.101012

Hui Wu, Yu Wang

引用次数: 0

Research on safe-haven currencies under global uncertainty —A new perception based on the East Asian market 全球不确定性下的避险货币研究--基于东亚市场的新认识

IF 5.5 2区经济学

Global Finance Journal Pub Date : 2024-07-17 DOI: 10.1016/j.gfj.2024.101013

Changrong Lu , Fandi Yu , Jiaxiang Li , Shilong Li

{"title":"Research on safe-haven currencies under global uncertainty —A new perception based on the East Asian market","authors":"Changrong Lu , Fandi Yu , Jiaxiang Li , Shilong Li","doi":"10.1016/j.gfj.2024.101013","DOIUrl":"10.1016/j.gfj.2024.101013","url":null,"abstract":"<div><p>The backdrop of this research is the high global uncertainty that has amplified the demand for safe-haven assets, particularly in the East Asian market. This paper redefines the concept of a “safe-haven” currency to align with contemporary geopolitical and trade policy uncertainties, diverging from the traditional volatility index (VIX) risk measure. We investigate the risk aversion properties of East Asian currencies under these nonmarket risks using dynamic heterogeneous panel data analysis and robustness checks with double machine learning. Empirical results reveal that no East Asian currency qualifies as a safe haven under geopolitical risk and trade policy uncertainty. However, the Japanese yen (JPY) maintains its status under the VIX indicator. This study highlights the insufficiency of traditional safe havens like the JPY and underscores the importance of considering nonmarket risks, challenging the effectiveness of traditional investment strategies amid modern geopolitical and policy uncertainties. The findings suggest that investors should prioritize nonmarket risks and call for reform in the global monetary system to enhance currency resilience. The novel methodological approach to evaluating safe-haven currencies addresses the need for diversified currency portfolios to mitigate nonmarket risks.</p></div>","PeriodicalId":46907,"journal":{"name":"Global Finance Journal","volume":"62 ","pages":"Article 101013"},"PeriodicalIF":5.5,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141773204","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}

引用次数: 0

Tail risk network analysis of Asian banks 亚洲银行尾部风险网络分析

IF 5.5 2区经济学

Global Finance Journal Pub Date : 2024-07-15 DOI: 10.1016/j.gfj.2024.101017

Thach N. Pham, Robert Powell, Deepa Bannigidadmath

引用次数: 0

Unveiling interconnectedness and risk spillover among cryptocurrencies and other asset classes 揭示加密货币和其他资产类别之间的相互关联性和风险溢出效应

IF 5.5 2区经济学

Global Finance Journal Pub Date : 2024-07-14 DOI: 10.1016/j.gfj.2024.101018

Shivani Narayan, Dilip Kumar

{"title":"Unveiling interconnectedness and risk spillover among cryptocurrencies and other asset classes","authors":"Shivani Narayan, Dilip Kumar","doi":"10.1016/j.gfj.2024.101018","DOIUrl":"10.1016/j.gfj.2024.101018","url":null,"abstract":"<div><p>The study investigates the interconnectedness and risk spillover among a diverse range of financial assets, including thirty-three cryptocurrencies, thirteen sectoral indices, six exchange rates, four precious metals, and six energy commodities. Using diverse methodologies, including partial correlation network, dynamic causality index, Granger causality network, cross-quantilogram and Bayesian graphical VAR model, the findings reveal intriguing insights, such as cryptocurrencies exhibiting a negative relation with other asset classes, minimal interconnectedness during the COVID-19 pandemic, and their vulnerability to shocks. Moreover, there is a stronger dependence structure from energy commodities and exchange rates to other classes, while moderate temporal dependencies exist between cryptocurrencies and other assets. These results emphasize the need for understanding and managing risks in the cryptocurrency market and highlight the interconnected nature of financial markets. The interconnectedness among various asset classes is mainly driven by variables representing market and economic sentiment, uncertainty and business confidence.</p></div>","PeriodicalId":46907,"journal":{"name":"Global Finance Journal","volume":"62 ","pages":"Article 101018"},"PeriodicalIF":5.5,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141623341","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}

引用次数: 0

Deep reinforcement learning for portfolio selection 用于投资组合选择的深度强化学习

IF 5.5 2区经济学

Global Finance Journal Pub Date : 2024-07-14 DOI: 10.1016/j.gfj.2024.101016

Yifu Jiang , Jose Olmo , Majed Atwi

{"title":"Deep reinforcement learning for portfolio selection","authors":"Yifu Jiang , Jose Olmo , Majed Atwi","doi":"10.1016/j.gfj.2024.101016","DOIUrl":"10.1016/j.gfj.2024.101016","url":null,"abstract":"<div><p>This study proposes an advanced model-free deep reinforcement learning (DRL) framework to construct optimal portfolio strategies in dynamic, complex, and large-dimensional financial markets. Investors' risk aversion and transaction cost constraints are embedded in an extended Markowitz's mean-variance reward function by employing a twin-delayed deep deterministic policy gradient (TD3) algorithm. This study designs a DRL-TD3-based risk and transaction cost-sensitive portfolio that combines advanced exploration strategies and dynamic policy updates. The proposed portfolio method effectively addresses the challenges posed by high-dimensional state and action spaces in complex financial markets. This methodology provides two optimal portfolios by flexibly controlling transaction and risk costs with (i) the constituents of the Dow Jones Industrial Average and (ii) the constituents of the S&P100 index. Results demonstrate a strong portfolio performance of the proposed DRL portfolio compared to those of several competitors from the traditional and DRL literatures.</p></div>","PeriodicalId":46907,"journal":{"name":"Global Finance Journal","volume":"62 ","pages":"Article 101016"},"PeriodicalIF":5.5,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1044028324000887/pdfft?md5=1e104ca35ccd1fee383f1ec3c00e3882&pid=1-s2.0-S1044028324000887-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141630819","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}

引用次数: 0

Impact of environmental, social, and governance rating disagreement on real earnings management in Chinese listed companies 环境、社会和治理评级分歧对中国上市公司实际收益管理的影响

IF 5.5 2区经济学

Global Finance Journal Pub Date : 2024-07-14 DOI: 10.1016/j.gfj.2024.101015

Ge Li , Yuxiang Cheng

{"title":"Impact of environmental, social, and governance rating disagreement on real earnings management in Chinese listed companies","authors":"Ge Li , Yuxiang Cheng","doi":"10.1016/j.gfj.2024.101015","DOIUrl":"10.1016/j.gfj.2024.101015","url":null,"abstract":"<div><p>This study examines the impact of environmental, social, and governance (ESG) rating disagreement on real earnings management in Chinese companies. Using ESG ratings from Huazheng, Wind, SynTao Green Finance, and Bloomberg, we find that increased disagreements in ESG rating lead to higher real earnings management in the current period and over the next 1 to 2 years. This effect is driven by external attention, compensation incentives, and reputational pressure. Furthermore, companies with a financial management background and younger management show a stronger correlation. Specifically, ESG rating disagreement has a significant impact on the manipulation of discretionary expenses and production costs but not on operating cash flows. Additionally, high ESG-rated companies tend to manage their earnings through discretionary expenses when rating disagreements arise. Overall, this study reveals the potential incentive mechanisms for such companies, providing theoretical support for understanding the factors influencing real earnings management. It also suggests that regulators and investors should fully consider the impact of ESG rating disagreement when assessing company performance.</p></div>","PeriodicalId":46907,"journal":{"name":"Global Finance Journal","volume":"62 ","pages":"Article 101015"},"PeriodicalIF":5.5,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141716942","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}

引用次数: 0

Impact of Fintech on labor allocation efficiency in firms: Empirical evidence from China 金融科技对企业劳动分配效率的影响：来自中国的经验证据

IF 5.5 2区经济学

Global Finance Journal Pub Date : 2024-07-10 DOI: 10.1016/j.gfj.2024.101011

James Ang , Zhenli Yan , Tusheng Xiao , Chun Yuan , Jingfang Wang

引用次数: 0

The effect of digital economy and environmental regulation on green total factor productivity: Evidence from China 数字经济和环境监管对绿色全要素生产率的影响：来自中国的证据

IF 5.5 2区经济学

Global Finance Journal Pub Date : 2024-07-10 DOI: 10.1016/j.gfj.2024.101010

Yonghui Lian, Haoran Dong, Hong Cao

引用次数: 0

Does social capital matter in underwriter's fees? 社会资本对承销商的费用有影响吗？