Nana Chai, Mohammad Zoynul Abedin, Xiaoling Wang, Baofeng Shi
{"title":"Growth potential of machine learning in credit risk predicting of farmers in the industry 4.0 era","authors":"Nana Chai, Mohammad Zoynul Abedin, Xiaoling Wang, Baofeng Shi","doi":"10.1002/ijfe.3010","DOIUrl":"https://doi.org/10.1002/ijfe.3010","url":null,"abstract":"This paper aims to design a model framework for farmer credit risk assessment based on machine learning. It reduces the degree of credit risk misjudgement caused by the weak correlation between evaluation indicators and default status and imbalanced data. Based on the empirical analysis of 8624 farmers' data from a commercial bank in China, the average rank of the OPSO‐GINI‐FS model designed from the feature dimension is 1.29, which is higher than that of the OPSO‐GINI‐IS model designed from the indicator dimension (1.57). This means that our model has a higher default risk identification ability than the traditional one. And the META‐SAMPLER method of processing imbalanced data is also promising. Moreover, we found the machine learning designed in this paper has a higher ability to identify farmers' loan default than the traditional econometric methods. These findings establish the potential of machine learning in credit risk identification from a micro perspective.","PeriodicalId":501193,"journal":{"name":"International Journal of Finance and Economics","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141189992","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":"A note on the determinants of non‐fungible tokens returns","authors":"Theodore Panagiotidis, Georgios Papapanagiotou","doi":"10.1002/ijfe.3008","DOIUrl":"https://doi.org/10.1002/ijfe.3008","url":null,"abstract":"We aim to identify the determinants of non‐fungible tokens non‐fungible tokens (NFTs) returns. The 10 most popular NFTs based on their price, trading volume, and market capitalisation are examined. Twenty‐three potential drivers of the returns of each NFT are considered. We employ a Bayesian LASSO model which takes into account stochastic volatility and leverage effect. The results indicate that NFTs returns are primarily driven by volatility and ethereum returns. We find a weak connection between NFTs returns and conventional assets, such as stock, oil, and gold markets.","PeriodicalId":501193,"journal":{"name":"International Journal of Finance and Economics","volume":"47 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141189811","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}
Tiago F. A. Matos, João C. A. Teixeira, Tiago M. Dutra
{"title":"The role of market discipline and macroprudential policies in achieving bank stability","authors":"Tiago F. A. Matos, João C. A. Teixeira, Tiago M. Dutra","doi":"10.1002/ijfe.3005","DOIUrl":"https://doi.org/10.1002/ijfe.3005","url":null,"abstract":"This study examines whether forcing banks to hold subordinated debt and enforcing market discipline could enhance the effectiveness of capital macroprudential policies in reducing banks' risk and contribute to bank stability. Using the system generalised method of moments and based on a sample of 322 banks across 18 countries during the period 2006–2020, we find that a higher level of subordinated debt leads banks to avoid moral‐hazard behaviours and engage in risk shifting when adapting to a tighter macroprudential framework, which in turn leads to a greater effectiveness of these policies. Furthermore, as robustness tests, we show that this effect is stronger in advanced economies and in the United States of America. These results also stand using a different proxy for banks' risk.","PeriodicalId":501193,"journal":{"name":"International Journal of Finance and Economics","volume":"13 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141189991","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}
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