Detecting Falsified Financial Statements Using a Hybrid SM-UTADIS Approach: Empirical Analysis of Listed Traditional Chinese Medicine Companies in China

Ruicheng Yang and Qi Jiang

Discrete Dynamics in Nature and Society, 2020, vol. 2020, 1-15

Abstract:

By combining the similarity matching (SM) method with the utilities additives discriminates (UTADIS) method, we propose a hybrid SM-UTADIS approach to detect falsified financial statements (FFS) of listed companies. To evaluate the performance of this hybrid approach, we conduct experiments using the annual financial ratios of listed traditional Chinese medicine (TCM) companies in China. There are three stages in the detection procedure. First, we use the cosine similarity matching method to select matched companies for each considered company, derive the deviation data of each considered company as a sample dataset to capture the intrinsic law of the financial data, and further divide these into training and testing datasets for the next two stages. Second, we put the training dataset into the UTADIS to train the SM-UTADIS model. Finally, we use the trained SM-UTADIS model to classify the testing dataset and evaluate the performance of the proposed method. Furthermore, we use other approaches, such as single UTADIS and logistic and SM-logistic regression models, to detect FFS. By comparing these results to those of the hybrid SM-UTADIS approach, we find that the proposed hybrid approach greatly improves the accuracy of FFS detection.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/DDNS/2020/8865489.pdf (application/pdf)
http://downloads.hindawi.com/journals/DDNS/2020/8865489.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:jnddns:8865489

DOI: 10.1155/2020/8865489

Access Statistics for this article

More articles in Discrete Dynamics in Nature and Society from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().