The European Journal of Finance最新文献

{"title":"The role of board age diversity in the performance of publicly listed Fintech entities","authors":"Paraskevi Katsiampa, Paul B. McGuinness, Hanxiong Zhang","doi":"10.1080/1351847x.2023.2287066","DOIUrl":"https://doi.org/10.1080/1351847x.2023.2287066","url":null,"abstract":"The present study addresses the important demographic of director age in relation to the performance of the constituent firms of Fintech-focused Exchange Traded Funds (ETFs). While private Fintech ...","PeriodicalId":22468,"journal":{"name":"The European Journal of Finance","volume":"128 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139065476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The influence of cultural norms on international equity allocation","authors":"Alexandru Todea, Cristina Harin","doi":"10.1080/1351847x.2023.2291124","DOIUrl":"https://doi.org/10.1080/1351847x.2023.2291124","url":null,"abstract":"We investigate the effect of cultural tightness-looseness on foreign bias in international equity allocation using data for 29 home investor countries and 37 destination countries for the period 20...","PeriodicalId":22468,"journal":{"name":"The European Journal of Finance","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138816630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bond default risk transmission through a common underwriter: evidence from China","authors":"Chunqiang Zhang, Tingyuan Zhu, Xi Gao, Kam C. Chan, Xiaojun Chen","doi":"10.1080/1351847x.2023.2290058","DOIUrl":"https://doi.org/10.1080/1351847x.2023.2290058","url":null,"abstract":"","PeriodicalId":22468,"journal":{"name":"The European Journal of Finance","volume":"29 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139005077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Crash risk connectedness in commodity markets","authors":"Najaf Iqbal, Muhammad Abubakr Naeem, Sitara Karim, Muhammad Haseeb","doi":"10.1080/1351847x.2023.2287673","DOIUrl":"https://doi.org/10.1080/1351847x.2023.2287673","url":null,"abstract":"In contrast to the extant literature on returns, volumes, and volatility spillovers, we examine the crash risk connectedness of 13 commodity markets in the energy, metal, and agricultural sectors, ...","PeriodicalId":22468,"journal":{"name":"The European Journal of Finance","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138687324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cryptocurrency research: future directions","authors":"Andrew Urquhart, Larisa Yarovaya","doi":"10.1080/1351847x.2023.2284186","DOIUrl":"https://doi.org/10.1080/1351847x.2023.2284186","url":null,"abstract":"Since Bitcoin was first proposed in late 2008 and went live in 2009, hundreds of research papers have been published trying to understand the behaviour of cryptocurrencies and their impact on finan...","PeriodicalId":22468,"journal":{"name":"The European Journal of Finance","volume":"51 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138687564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How does institutional investor preference influence corporate green innovation in China?","authors":"Zhongfei Chen, Wenbin Zuo, Guanxia Xie","doi":"10.1080/1351847x.2023.2285338","DOIUrl":"https://doi.org/10.1080/1351847x.2023.2285338","url":null,"abstract":"","PeriodicalId":22468,"journal":{"name":"The European Journal of Finance","volume":"17 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139212825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigation of the effect of global EPU spillovers on country-level stock market idiosyncratic volatility","authors":"Mustafa O. Caglayan, Yuting Gong, Wenjun Xue","doi":"10.1080/1351847x.2023.2279141","DOIUrl":"https://doi.org/10.1080/1351847x.2023.2279141","url":null,"abstract":"ABSTRACTUsing the multivariate quantile model, this paper develops a global economic policy uncertainty (EPU) spillover measure for each country and investigates the spillover effects on the country-level stock market idiosyncratic volatility across a sample of 23 economies. The regression results show that global EPU spillovers have a positive and significant effect on the country-level stock market idiosyncratic volatility. We find that the effect of developed-market-generated EPU spillovers on the country-level stock market idiosyncratic risk is noticeably larger compared to the effect of emerging-market-generated EPU spillovers. Furthermore, the significant and positive effect of the EPU spillovers on the country-level stock market idiosyncratic volatility continues when we utilize various economic, financial, and political risk factors as controls, as well as when we use alternative measures of stock market idiosyncratic volatility as the dependent variable in our regression analyses.KEYWORDS: EPU spilloverscountry-level stock market idiosyncratic volatilitymultivariate quantile modelinternational asset pricingJEL CLASSIFICATIONS: C10F30G12G15 AcknowledgementsWe gratefully acknowledge the financial support from the National Natural Science Foundation of China (grant number 71971133), the National Social Science Foundation of China (grant number 21BGL270) and the Shanghai Science and Technology Committee (grant number 23692111400)Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 The GDP weights utilized in this analysis are from quarterly GDP data and time-varying over the sample period. Specifically, we collect the real GDP data of our sample countries from the IMF’s World Economic Outlook Database on a quarterly basis, and the GDP weights utilized in this calculation are adjusted on a quarterly basis.2 In our analyses we use the first difference of the EPUs in our regression models since the original EPUs are not stationary and do not meet the requirement of the multivariate quantile model (see White, Kim, and Manganelli Citation2015). In addition, when we look at the distribution of the change in EPUs across 23 countries (see Figure B1 in Online Appendix B), we find that the kurtosis is 7.0546, which is evidence of heavy tails in the distribution. Furthermore, the Jarque–Bera test confirms that the change in EPU is not normally distributed. These findings support the necessity to use the multivariate quantile model in analyzing global EPU spillovers.3 For each country i and the other N-1 countries, in each rolling procedure, 36 monthly observations are used for different quantiles. As a robustness check, we have also utilized the 48- and 60-month rolling windows and obtained results similar to the ones generated from a 36-month rolling window approach. These results using the 48- and 60-month rolling window regressions are available upon request and suggest that our results are not dependent on the ","PeriodicalId":22468,"journal":{"name":"The European Journal of Finance","volume":"14 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134957136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Internationalization and zero leverage","authors":"Eleni Chatzivgeri, Panagiotis Dontis-Charitos, Sheeja Sivaprasad, Jonathan Williams","doi":"10.1080/1351847x.2023.2277273","DOIUrl":"https://doi.org/10.1080/1351847x.2023.2277273","url":null,"abstract":"Despite growing attention on the role of internationalization in capital structure and the increasing adoption of zero-leverage policies by multinationals (MNC), no study examines the effect of internationalization on zero leverage. Using data from the United Kingdom (UK), we present the first empirical evidence of a positive and significant relationship that increases in the level of internationalization both statistically and economically. We find that the motivation for zero leverage differs between MNC and domestic firms (DOM). Whilst the major driving factor for MNC is the maintenance of financial flexibility, financial constraints motivate DOM.","PeriodicalId":22468,"journal":{"name":"The European Journal of Finance","volume":"29 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134957430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Measuring the differentiation and decentralization of managers' risk attention and their impacts","authors":"Ling Zhou, Zongrun Wang, Jianxin Wang","doi":"10.1080/1351847x.2023.2277285","DOIUrl":"https://doi.org/10.1080/1351847x.2023.2277285","url":null,"abstract":"AbstractManagers' attention to different risk factors conveys important information to investors. This paper examines the association between managers' risk attention allocation schemes and the performance of firms across different sectors. We innovatively use the text mining approach to measure the differentiation and decentralization of risk attention from textual risk disclosures reported in 65,878 10-K statements. The results show significant sector heterogeneity in managers' attention to different risk topics. For the consumer goods sector, managers with differentiated and decentralized topics can improve the company's profitability and solvency. In contrast, managers in the financial and healthcare sectors need to maintain topic attention concentration. In addition, we find that managers' attention to product approval, system security, and business impact has gradually increased over time to adapt to the internet economic environment.Keywords: Risk factorstopic attentiontext mining10-K statementssector heterogeneity Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 SEC (2010). Form 10-K instructions. www.sec.gov/about/forms/form10-k.pdf.Additional informationFundingThis study was supported by the National Natural Science Foundation of China [Nos. 72091515]. Notes on contributorsLing ZhouLing Zhou, Ph.D., postdoctoral fellow at Central South University, mainly focuses on causal inference, policy analysis, and text analysis.Zongrun WangZongrun Wang, Professor of Central South University, the head of major and key projects of the National Natural Science Foundation of China, the head of the Applied Economics discipline at Central South University. have long been committed to researching risk management technologies and methods in the field of data analysis and management science, with a particular focus on risk measurement, integration, and decision-making theories and methods, actively carry out academic research and practical work on financial engineering and risk management technology methods.Jianxin WangJianxin Wang is an Associate Professor at Central South University. He received his PhD in Economics from George Mason University and his PhD in Management Science and Engineering from Central South University. His research interests include behavioral economics, experimental economics, and behavioral finance, with a special focus on behavioral economics of alcohol intoxication. He has published in PNAS, Journal of Corporate Finance, Experimental Economics, Journal of Economic Behavior & Organization and Economics Letters.","PeriodicalId":22468,"journal":{"name":"The European Journal of Finance","volume":" 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135291252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interpretable image-based deep learning for price trend prediction in ETF markets","authors":"Ruixun Zhang, Chaoyi Zhao, Guanglian Lin","doi":"10.1080/1351847x.2023.2275567","DOIUrl":"https://doi.org/10.1080/1351847x.2023.2275567","url":null,"abstract":"AbstractImage-based deep learning models excel at extracting spatial information from images but their potential in financial applications has not been fully explored. Here we propose the channel and spatial attention convolutional neural network (CS-ACNN) for price trend prediction. It utilizes the attention mechanisms to focus on specific areas of input images that are the most relevant for prices. Using exchange-traded funds (ETF) data from three different markets, we show that CS-ACNN – using images constructed from financial time series – achieves on-par and, in some cases, superior performances compared to models that use time series data only. This holds true for both model classification metrics and investment profitability, and the out-of-sample Sharpe ratios range from 1.57 to 3.03 after accounting for transaction costs. The model learns visual patterns that are consistent with traditional technical analysis, providing an economic rationale for learned patterns and allowing investors to interpret the model.Keywords: Price trend predictionconvolutional neural network (CNN)attentionimageinterpretabilityJEL Classifications: C45G11G12G15 AcknowledgmentsWe thank Xiuli Shao for very helpful comments and discussion.Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 Specific neural network architectures in this literature include the fully-connected neural networks (Gu, Kelly, and Xiu Citation2020), autoencoders (Gu, Kelly, and Xiu Citation2021), and sequence models (Cong et al. Citation2021a, Citation2021b).2 Jiang, Kelly, and Xiu (Citation2022), a primary example in this literature, focus on learning price patterns from candlestick charts for future price trends, while our framework is able to extract information from both candlestick charts and, more broadly, any images constructed from financial time series.3 We use Python's mpl_finance module, and adopt the convention in China to represent positive trends with red and negative trends with green.4 In particular, they are defined by whether the closing price is higher than the opening price of the day.5 See, for example, Borgefors (Citation1986) and Fang et al. (Citation2021).6 Se(p′) goes to ±∞ when p is very close to 0 or 1. In practice, we clip Se(p) to be between 0 and 1.7 To feed the data into the convolutional neural network, these images are resized and cropped to 112×64 pixels.8 This is referred to as the Gramian Summation Angular Field (GASF) by Wang and Oates (Citation2015). If we define an inner product as ⟨x,y⟩=xy−1−x2⋅1−y2, the image G in Equation (Equation11(11) G=[cos⁡(ϕ1+ϕ1)⋯cos⁡(ϕ1+ϕT)cos⁡(ϕ2+ϕ1)⋯cos⁡(ϕ2+ϕT)⋮⋱⋮cos⁡(ϕT+ϕ1)⋯cos⁡(ϕT+ϕT)]=X~⋅X~′−I−X~2⋅I−X~2′,(11) ) constitute a quasi-Gramian matrix under this inner product.9 The number of filters in VggNet (the number of output channels after convolution) starts from 64 and increases exponentially after each max-pooling operation. The convolution mode of VggNet is ‘same’, meaning that the ","PeriodicalId":22468,"journal":{"name":"The European Journal of Finance","volume":"29 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135271032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}