Erroneous Erratum to Accounting Fraud Article
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Yang Bao & Bin Ke & Bin Li & Y. Julia Yu & Jie Zhang, 2020. "Detecting Accounting Fraud in Publicly Traded U.S. Firms Using a Machine Learning Approach," Journal of Accounting Research, Wiley Blackwell, vol. 58(1), pages 199-235, March.
- Stephen Walker, 2021. "Critique of an Article on Machine Learning in the Detection of Accounting Fraud," Econ Journal Watch, Econ Journal Watch, vol. 18(1), pages 1-61–70, March.
- Yang Bao & Bin Ke & Bin Li & Y. Julia Yu & Jie Zhang, 2021. "A Response to "Critique of an Article on Machine Learning in the Detection of Accounting Fraud"," Econ Journal Watch, Econ Journal Watch, vol. 18(1), pages 1-71–78, March.
- Stephen Walker, 2021. "Rejoinder to the Critique of an Article on Machine Learning in the Detection of Accounting Fraud," Econ Journal Watch, Econ Journal Watch, vol. 18(2), pages 230–234-2, September.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Md Jahidur Rahman & Hongtao Zhu, 2023. "Predicting accounting fraud using imbalanced ensemble learning classifiers – evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(3), pages 3455-3486, September.
- Yang Bao & Bin Ke & Bin Li & Y. Julia Yu & Jie Zhang, 2021. "A Response to "Critique of an Article on Machine Learning in the Detection of Accounting Fraud"," Econ Journal Watch, Econ Journal Watch, vol. 18(1), pages 1-71–78, March.
- Xiaowei Chen & Cong Zhai, 2023. "Bagging or boosting? Empirical evidence from financial statement fraud detection," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(5), pages 5093-5142, December.
- Adebayo Oshingbesan & Eniola Ajiboye & Peruth Kamashazi & Timothy Mbaka, 2022. "Model-Free Reinforcement Learning for Asset Allocation," Papers 2209.10458, arXiv.org.
- Zhang, Chanyuan (Abigail) & Cho, Soohyun & Vasarhelyi, Miklos, 2022. "Explainable Artificial Intelligence (XAI) in auditing," International Journal of Accounting Information Systems, Elsevier, vol. 46(C).
- Xin Xu & Feng Xiong & Zhe An, 2023. "Using Machine Learning to Predict Corporate Fraud: Evidence Based on the GONE Framework," Journal of Business Ethics, Springer, vol. 186(1), pages 137-158, August.
- Yunchuan Sun & Xiaoping Zeng & Ying Xu & Hong Yue & Xipu Yu, 2024. "An intelligent detecting model for financial frauds in Chinese A‐share market," Economics and Politics, Wiley Blackwell, vol. 36(2), pages 1110-1136, July.
- Zhou, Ying & Li, Haoran & Xiao, Zhi & Qiu, Jing, 2023. "A user-centered explainable artificial intelligence approach for financial fraud detection," Finance Research Letters, Elsevier, vol. 58(PA).
- Luigi Rombi, 2024. "Handbook of accounting, accountability and governance edited by Garry D. Carnegie and Christopher J. Napier," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 28(3), pages 943-955, September.
- Colak, Gonul & Fu, Mengchuan & Hasan, Iftekhar, 2022. "On modeling IPO failure risk," Economic Modelling, Elsevier, vol. 109(C).
- Nerissa C. Brown & Richard M. Crowley & W. Brooke Elliott, 2020. "What Are You Saying? Using topic to Detect Financial Misreporting," Journal of Accounting Research, Wiley Blackwell, vol. 58(1), pages 237-291, March.
- Li, Guowen & Wang, Shuai & Feng, Yuyao, 2024. "Making differences work: Financial fraud detection based on multi-subject perceptions," Emerging Markets Review, Elsevier, vol. 60(C).
- Paul Geertsema & Helen Lu, 2023. "Relative Valuation with Machine Learning," Journal of Accounting Research, Wiley Blackwell, vol. 61(1), pages 329-376, March.
- Mika Ylinen & Mikko Ranta, 2024. "Employer ratings in social media and firm performance: Evidence from an explainable machine learning approach," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(1), pages 247-276, March.
- Gao, Wei & Ju, Ming & Yang, Tongyang, 2023. "Severe weather and peer-to-peer farmers’ loan default predictions: Evidence from machine learning analysis," Finance Research Letters, Elsevier, vol. 58(PA).
- Jun, So Young & Kim, Dong Sung & Jung, Suk Yoon & Jun, Sang Gyung & Kim, Jong Woo, 2022. "Stock investment strategy combining earnings power index and machine learning," International Journal of Accounting Information Systems, Elsevier, vol. 47(C).
- Vitali, Sonia & Giuliani, Marco, 2024. "Emerging digital technologies and auditing firms: Opportunities and challenges," International Journal of Accounting Information Systems, Elsevier, vol. 53(C).
- Achakzai, Muhammad Atif Khan & Peng, Juan, 2023. "Detecting financial statement fraud using dynamic ensemble machine learning," International Review of Financial Analysis, Elsevier, vol. 89(C).
- Booker, Adam & Chiu, Victoria & Groff, Nathan & Richardson, Vernon J., 2024. "AIS research opportunities utilizing Machine Learning: From a Meta-Theory of accounting literature," International Journal of Accounting Information Systems, Elsevier, vol. 52(C).
- Achakzai, Muhammad Atif Khan & Juan, Peng, 2022. "Using machine learning Meta-Classifiers to detect financial frauds," Finance Research Letters, Elsevier, vol. 48(C).
More about this item
Keywords
Machine learning; serial fraud;JEL classification:
- C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
- M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ejw:journl:v:19:y:2022:i:2:p:190-203. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Jason Briggeman (email available below). General contact details of provider: https://edirc.repec.org/data/edgmuus.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.