Intelligent Systems in Accounting, Finance and Management最新文献_第7页

Remarks on a copula-based conditional value at risk for the portfolio problem 关于投资组合问题的一个基于copula的条件风险值的注记

Intelligent Systems in Accounting, Finance and Management Pub Date : 2023-08-07 DOI: 10.1002/isaf.1540

Andres Mauricio Molina Barreto, Naoyuki Ishimura

引用次数: 0

An efficient graph-based peer selection method for financial statements 一种高效的基于图的财务报表对等选择方法

Intelligent Systems in Accounting, Finance and Management Pub Date : 2023-07-05 DOI: 10.1002/isaf.1539

Sander Noels, Simon De Ridder, Sébastien Viaene, Tijl De Bie

引用次数: 0

Evaluating interpretable machine learning predictions for cryptocurrencies 评估加密货币的可解释机器学习预测

Intelligent Systems in Accounting, Finance and Management Pub Date : 2023-06-21 DOI: 10.1002/isaf.1538

Ahmad El Majzoub, Fethi A. Rabhi, Walayat Hussain

{"title":"Evaluating interpretable machine learning predictions for cryptocurrencies","authors":"Ahmad El Majzoub, Fethi A. Rabhi, Walayat Hussain","doi":"10.1002/isaf.1538","DOIUrl":"https://doi.org/10.1002/isaf.1538","url":null,"abstract":"<p>This study explores various machine learning and deep learning applications on financial data modelling, analysis and prediction processes. The main focus is to test the prediction accuracy of cryptocurrency hourly returns and to explore, analyse and showcase the various interpretability features of the ML models. The study considers the six most dominant cryptocurrencies in the market: Bitcoin, Ethereum, Binance Coin, Cardano, Ripple and Litecoin. The experimental settings explore the formation of the corresponding datasets from technical, fundamental and statistical analysis. The paper compares various existing and enhanced algorithms and explains their results, features and limitations. The algorithms include decision trees, random forests and ensemble methods, SVM, neural networks, single and multiple features N-BEATS, ARIMA and Google AutoML. From experimental results, we see that predicting cryptocurrency returns is possible. However, prediction algorithms may not generalise for different assets and markets over long periods. There is no clear winner that satisfies all requirements, and the main choice of algorithm will be tied to the user needs and provided resources.</p>","PeriodicalId":53473,"journal":{"name":"Intelligent Systems in Accounting, Finance and Management","volume":"30 3","pages":"137-149"},"PeriodicalIF":0.0,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/isaf.1538","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50153077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Neural networks for estimating Macro Asset Pricing model in football clubs 足球俱乐部宏观资产定价模型的神经网络估计

Intelligent Systems in Accounting, Finance and Management Pub Date : 2023-05-31 DOI: 10.1002/isaf.1532

David Alaminos, Ignacio Esteban, M. Belén Salas

{"title":"Neural networks for estimating Macro Asset Pricing model in football clubs","authors":"David Alaminos, Ignacio Esteban, M. Belén Salas","doi":"10.1002/isaf.1532","DOIUrl":"https://doi.org/10.1002/isaf.1532","url":null,"abstract":"<p>The recent crisis caused by COVID-19 directly affected consumption habits and the stability sof financial markets. In particular, the football industry has been hit hard by this pandemic and therefore has more volatile stock prices. Given this new scenario, further research is needed to accurately estimate the value of the shares of football clubs. In this paper, we estimate an asset pricing model in football clubs with different compositions of risk nature using non-linear techniques of artificial neural networks. Usually, asset pricing models have been estimated with linear methods such as ordinary least squares. Our results show a precision higher than 90% for all the estimated models, which far exceeds those shown by linear methods in the previous literature. We find that the residual represents about 40% of the variance of the price-dividend ratio. Long-term risks follow in importance, and above all, the habit component and its behaviour in the face of changes. The importance of the residual component exists due to a low correlation between the asset price and consumer behaviour, but to a much lesser extent than that shown in previous studies. The estimation carried out with artificial neural networks, both the Deep Learning methods and especially the Quantum Neural Network, opens up new possibilities to estimate more efficiently the pricing of financial assets in the football industry.</p>","PeriodicalId":53473,"journal":{"name":"Intelligent Systems in Accounting, Finance and Management","volume":"30 2","pages":"57-75"},"PeriodicalIF":0.0,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/isaf.1532","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50126628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Challenges of using RPA in auditing: A socio-technical systems approach 在审计中使用RPA的挑战：一种社会技术系统方法

Intelligent Systems in Accounting, Finance and Management Pub Date : 2023-05-25 DOI: 10.1002/isaf.1537

Laila Dahabiyeh, Omar Mowafi

引用次数: 0

An analysis of three chatbots: BlenderBot, ChatGPT and LaMDA 三个聊天机器人的分析：BlenderBot、ChatGPT和LaMDA

Intelligent Systems in Accounting, Finance and Management Pub Date : 2023-03-30 DOI: 10.1002/isaf.1531

Daniel E. O'Leary

引用次数: 8

Predicting base station return on investment in the telecommunications industry: Machine-learning approaches 预测基站在电信行业的投资回报率：机器学习方法

Intelligent Systems in Accounting, Finance and Management Pub Date : 2023-03-07 DOI: 10.1002/isaf.1530

Cihan Şahin

{"title":"Predicting base station return on investment in the telecommunications industry: Machine-learning approaches","authors":"Cihan Şahin","doi":"10.1002/isaf.1530","DOIUrl":"https://doi.org/10.1002/isaf.1530","url":null,"abstract":"<p>Investment in the right location ensures sustainable competition. In the telecommunication sector, the number of base stations (BSs) is one of the most significant investment parameters. When a potential BS is subject to be selected, practitioners will first consider investing in a BS where the return on investment (ROI) is highest. Therefore, the quantifiable objectives are distinctly defined, as it makes sense to choose maximizing features that raise per unit investment. This study provides a solution to evaluate the best BS installation alternative with machine-learning approaches as well as to estimate ROI value by changing the properties that affect the ROI value. For this purpose, the estimation performance of logistic regression, random forest, and XGBoost methods are compared and further strengthened by random forest hyperparameter optimization to provide the best performance. The model, with a success rate of 98.7% according to the \u0000<math>\u0000 <mi>F</mi></math>-score, showed that it was a robust algorithm. The three most essential features for the ROI value are determined to be voice traffic, data traffic, and frequency cost. These parameters enable a review of the prediction results of telecommunications managers and planning specialists responsible for BS investment.</p>","PeriodicalId":53473,"journal":{"name":"Intelligent Systems in Accounting, Finance and Management","volume":"30 1","pages":"29-40"},"PeriodicalIF":0.0,"publicationDate":"2023-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50124431","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

Using Google Trends to track the global interest in International Financial Reporting Standards: Evidence from big data 利用谷歌趋势追踪全球对《国际财务报告准则》的兴趣：来自大数据的证据

Intelligent Systems in Accounting, Finance and Management Pub Date : 2023-02-11 DOI: 10.1002/isaf.1529

Yuqian Zhang

引用次数: 1

Hedging role of stablecoins 稳定币的套期保值作用

Intelligent Systems in Accounting, Finance and Management Pub Date : 2023-02-01 DOI: 10.1002/isaf.1528

Yosuke Kakinuma

引用次数: 1

How the quality of initial coin offering white papers influences fundraising: Using security token offerings white papers as a benchmark 首次代币发行白皮书的质量如何影响筹款：以安全代币发行白皮书为基准

Intelligent Systems in Accounting, Finance and Management Pub Date : 2023-01-04 DOI: 10.1002/isaf.1527

Shih-Chu Chou, Zhe-An Li, Tawei Wang, Ju-Chun Yen

{"title":"How the quality of initial coin offering white papers influences fundraising: Using security token offerings white papers as a benchmark","authors":"Shih-Chu Chou, Zhe-An Li, Tawei Wang, Ju-Chun Yen","doi":"10.1002/isaf.1527","DOIUrl":"https://doi.org/10.1002/isaf.1527","url":null,"abstract":"<div>\u0000 \u0000 <p>In recent years, many initial coin offerings (ICOs) scams have been reported, attracting attention to this relatively new and unregulated ICO market, which lacks disclosure requirements and therefore suffers from intensifying problems of information asymmetry inherent in crowdfunding. As a prospectus-type document, an ICO white paper serves as a major means of voluntary disclosure practices adopted by ventures seeking external financing. Given the importance of an ICO white paper and the difficulty of assessing its quality, we propose to benchmark it against white paper content for security token offerings (STOs)—a more regulated ICO subset. Using the similarity of ICO white papers with STO white papers to proxy for disclosure quality, we document that the ICO campaigns that have white papers more similar to STO white papers are more likely to raise funding successfully. Our findings provide implications for policymakers, ICO fundraisers, and investors on the importance of white paper quality.</p>\u0000 </div>","PeriodicalId":53473,"journal":{"name":"Intelligent Systems in Accounting, Finance and Management","volume":"30 1","pages":"3-18"},"PeriodicalIF":0.0,"publicationDate":"2023-01-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50120081","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