Journal of Applied Finance & Banking最新文献

Economic Analysis of Judicial Conciliation in Brazilian Financial Institutions 巴西金融机构司法调解的经济分析

Journal of Applied Finance & Banking Pub Date : 2024-07-12 DOI: 10.47260/jafb/1446

Anna Cláudia De Vasconcelos, M. Tessmann, Humberto Nunes Alencar

引用次数: 0

Bank Customer Churn Prediction Using Machine Learning Framework 利用机器学习框架预测银行客户流失率

Journal of Applied Finance & Banking Pub Date : 2024-06-04 DOI: 10.47260/jafb/1445

Rasha Ashraf

{"title":"Bank Customer Churn Prediction Using Machine Learning Framework","authors":"Rasha Ashraf","doi":"10.47260/jafb/1445","DOIUrl":"https://doi.org/10.47260/jafb/1445","url":null,"abstract":"Abstract\u0000\u0000Using real customer data from a large community bank in the South of the US, this paper analyzes the customer churn prediction problem by constructing and comparing ten machine learning classification models with five sample techniques. Our results show that Random Forest, XG Boost, AdaBoost, and Bagging Meta classifiers dominate others in terms of overall accuracy, F-score, and AUC curve for the test observations. For the four classifiers, the overall accuracy ranges from 87% to 96% across five different sampling methods explored, while the AUC values range between 0.9 to 0.93. Considering overall accuracy and F-Score, AdaBoost with original and MTDF sampling technique dominates others; however, considering the AUC measure, XG Boost and Random Forest perform similarly to AdaBoost, which slightly dominate Bagging Meta across all sampling techniques; although the performance measures for these four classifiers are comparable across all sampling techniques. The paper further presents important features of customer churn behavior as predicted by the model. The diagnostic analysis also provides an insightful comparison between churned and non-churned customers.\u0000\u0000JEL classification numbers: C0, C5, C8, G21.\u0000Keywords: Machine learning, Big data, Sampling techniques, Customer churn, Customer retention, Financial services, Community bank.","PeriodicalId":330012,"journal":{"name":"Journal of Applied Finance & Banking","volume":"6 17","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141267234","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}

引用次数: 0

Carbon Disclosure and Information Asymmetry 碳信息披露与信息不对称

Journal of Applied Finance & Banking Pub Date : 2024-05-21 DOI: 10.47260/jafb/1444

Kuei Chiu Lee

引用次数: 0

Exploring Calendar Effects in Bitcoin Returns: An Analysis of Market Efficiency 探索比特币回报的日历效应：市场效率分析

Journal of Applied Finance & Banking Pub Date : 2024-05-15 DOI: 10.47260/jafb/1443

Chen-Han Liu

引用次数: 0

Measuring Financial Stability in Curaçao and Sint Maarten 衡量库拉索岛和圣马丁岛的金融稳定性

Journal of Applied Finance & Banking Pub Date : 2024-05-06 DOI: 10.47260/jafb/1442

Gavin Ooft, Monique-Thijn Baank

{"title":"Measuring Financial Stability in Curaçao and Sint Maarten","authors":"Gavin Ooft, Monique-Thijn Baank","doi":"10.47260/jafb/1442","DOIUrl":"https://doi.org/10.47260/jafb/1442","url":null,"abstract":"Abstract\u0000\u0000Assessing the solidity of the financial system may be cumbersome since there is no single comprehensive indicator to measure financial stability. This paper presents two aggregate measures that can be deployed as early warning measures of financial stability for the monetary union of Curaçao and Sint Maarten, mainly focusing on the banking sector. As this sector comprises most of the monetary union's assets, the constructed measures are mainly focused on this sector. Following financial stability literature, we apply empirical normalization and aggregation to construct an Aggregate Financial Stability Index (AFSI) and a Banking Stability Index (BSI). These indices have been gaining popularity among central banks to assess financial stability on top of conventional measures such as Financial Soundness Indicators (FSIs) and credit cycles. The AFSI comprises banking-sector indicators, macro-financial developments, and international trends, while the BSI captures dimensions of banks' financial soundness. We benchmark the AFSI and the BSI to the period of deteriorating macro-financial conditions induced by the coronavirus crisis, and the development in the indices was as expected. Based on the robustness analyses conducted, we deem the constructed indices plausible for measuring and tracking financial stability within the monetary union of Curaçao and Sint Maarten.\u0000\u0000JEL classification numbers: C20, C45, E58, F15, G21.\u0000Keywords: Early warning indicators, Financial stability, Financial soundness indicators.","PeriodicalId":330012,"journal":{"name":"Journal of Applied Finance & Banking","volume":"13 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141007166","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}

引用次数: 0

The Impact of ESG on Corporate Financing Decisions Before and After Covid-19: Evidence from Taiwan Covid-19前后ESG对企业融资决策的影响：来自台湾的证据

Journal of Applied Finance & Banking Pub Date : 2024-04-25 DOI: 10.47260/jafb/1441

Ji-Ying Fang, Wen-Sheng Wang

引用次数: 0

Investigating the Impact of Financial Reporting for Cryptocurrencies on Company Value 调查加密货币财务报告对公司价值的影响

Journal of Applied Finance & Banking Pub Date : 2024-04-10 DOI: 10.47260/jafb/1436

Kuo-Shing Chen

{"title":"Investigating the Impact of Financial Reporting for Cryptocurrencies on Company Value","authors":"Kuo-Shing Chen","doi":"10.47260/jafb/1436","DOIUrl":"https://doi.org/10.47260/jafb/1436","url":null,"abstract":"Abstract\u0000\u0000This research focuses on investigating the impact of cryptocurrency accounting reports on company value (measured by financial performance) before and during the COVID 19 epidemic. Analyzing publicly listed companies’ data in firms’ 10-K filings, we find that there is no significant relation with the company’s profits while a company holds cryptocurrency positions. Although the issue of cryptocurrency accounting is an emerging topic, prior literature is mostly focused on cryptocurrency investment and is a rare investigation coping with the accounting treatment of crypto-assets. This paper seeks to contribute to the knowledge of fresh issues surrounding the accounting practices and standards tied to cryptocurrency for the company’s holding of crypto-assets. Taken together, the observed findings obtained from the test of the second hypothesis show that there is no significant relationship with the company’s stock returns while a company holds cryptocurrency positions. This result can be interpreted to determine whether the general investors take a more positive or negative attitude towards companies involved in cryptocurrency holding. Crucially, research findings unveil that cryptocurrency holdings have a significant impact on a company's liabilities. Our empirical evidence could be beneficial to public authorities and firms in decision- making situations related to cryptocurrency holdings of companies.\u0000\u0000JEL classification numbers: G10, G18, M14, M41.\u0000Keywords: Cryptocurrency accounting reports, Crypto-asset holdings, Firm value.","PeriodicalId":330012,"journal":{"name":"Journal of Applied Finance & Banking","volume":"225 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140720042","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}

引用次数: 0

Sentiment-Driven Exchange Rate Forecasting: Integrating Twitter Analysis with Economic Indicators 情绪驱动的汇率预测：将推特分析与经济指标相结合

Journal of Applied Finance & Banking Pub Date : 2024-04-05 DOI: 10.47260/jafb/1434

Kazım Berk Küçüklerli, Veysel Ulusoy

{"title":"Sentiment-Driven Exchange Rate Forecasting: Integrating Twitter Analysis with Economic Indicators","authors":"Kazım Berk Küçüklerli, Veysel Ulusoy","doi":"10.47260/jafb/1434","DOIUrl":"https://doi.org/10.47260/jafb/1434","url":null,"abstract":"Abstract\u0000\u0000This study focuses on predicting the USD/TL exchange rate by integrating sentiment analysis from Twitter with traditional economic indicators. With the dynamic nature of global finance, accurate exchange rate forecasting is crucial for financial planning and risk management. While economic indicators have traditionally been used for this purpose, the increasing influence of public sentiment, particularly on digital platforms like Twitter, has prompted the exploration of sentiment analysis as a complementary tool. Our research aims to evaluate the effectiveness of combining sentiment analysis with economic indicators in predicting the USD/TL exchange rate. We employ machine learning techniques, including LSTM Neural Network, xgboost, and RNN, to analyze Twitter data containing keywords related to the Turkish economy alongside TL/USD exchange rate data. Our findings demonstrate that integrating sentiment analysis from Twitter enhances the predictive accuracy of exchange rate movements. This study contributes to the evolving landscape of financial forecasting by highlighting the significance of sentiment analysis in exchange rate prediction and providing insights into its potential applications in financial decision-making processes.\u0000\u0000JEL classification numbers: C53, F31, E60.\u0000Keywords: Twitter narratives, LSTM, XGBoost, RNN, USD/TL FX rate, Narrative economics.","PeriodicalId":330012,"journal":{"name":"Journal of Applied Finance & Banking","volume":"53 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140736503","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}

引用次数: 0

Fed’s Dual Mandate: Maximum Employment and Price Stability 美联储的双重使命：最大限度的就业和价格稳定

Journal of Applied Finance & Banking Pub Date : 2024-04-04 DOI: 10.47260/jafb/1433

Ioannis N. Kallianiotis

引用次数: 0

The Causality between Analysts’ Recommendations and Corporate M&As 分析师建议与企业并购之间的因果关系

Journal of Applied Finance & Banking Pub Date : 2024-04-03 DOI: 10.47260/jafb/1432

Ching-Chih Wu, Tung-Hsiao Yang

{"title":"The Causality between Analysts’ Recommendations and Corporate M&As","authors":"Ching-Chih Wu, Tung-Hsiao Yang","doi":"10.47260/jafb/1432","DOIUrl":"https://doi.org/10.47260/jafb/1432","url":null,"abstract":"Abstract\u0000\u0000This study examines the role of analysts' recommendations in mergers and acquisitions (M&As), focusing on their impact on payment methods and acquirers' long-term performance. The findings reveal that acquirers with strong buy or buy recommendations are more likely to use 100% stock payment, consistent with the overvaluation hypothesis. Conversely, those with strong sell or sell recommendations tend to prefer cash payment. Notably, acquirers with higher recommendation scores exhibit better long-term market performance. This finding suggests that analysts' recommendations before M&A announcements do not fully incorporate the deal's potential impact on long-term value creation. Moreover, acquirers with buy recommendations experience significantly lower long-term returns, highlighting the disconnect between analysts' recommendations and long-term performance. These findings contribute to understanding the information content and limitations of analysts' recommendations in the M&A context.\u0000\u0000JEL classification numbers: G34, G24, G14.\u0000Keywords: Mergers and acquisitions, Analysts' recommendations, Payment methods, Information quality, Overvaluation hypothesis.","PeriodicalId":330012,"journal":{"name":"Journal of Applied Finance & Banking","volume":"65 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140746859","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}

引用次数: 0

Journal of Applied Finance &amp; Banking最新文献

Journal of Applied Finance & Banking最新文献