Using fuzzy c-means clustering algorithm in financial health scoring

Classification of firms according to their financial health is currently one of the major problems in the literature. To our knowledge, as a first attempt, we suggest using fuzzy c-means clustering algorithm to produce single and sensitive financial health scores especially for shortterm investment...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Audit financiar (Bucharest, Romania ) Ročník 15; číslo 147; s. 385 - 394
Hlavní autoři:	GOKTEN, Pinar OKAN, BASER, Furkan, GOKTEN, Soner
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Chamber of Financial Auditors of Romania 01.08.2017
Témata:	Accounting numbers financial analysis financial classification Fuzzy c-means (FCM) clustering algorithm
ISSN:	1583-5812, 1844-8801, 1844-8801
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Popis
Shrnutí:	Classification of firms according to their financial health is currently one of the major problems in the literature. To our knowledge, as a first attempt, we suggest using fuzzy c-means clustering algorithm to produce single and sensitive financial health scores especially for shortterm investment decisions by using recently announced accounting numbers. Accordingly, we show the calculation of fuzzy financial health scores step by step by benefit from Piotroski’s criteria of liquidity/solvency, operating efficiency and profitability for the firms taken as a sample. The results of correlation analysis indicate that calculated scores are coherent with short-term price formations in terms of investors’ behavior and so fuzzy c-means clustering algorithm could be used to sort firm in a more sensitive perspective.
ISSN:	1583-5812 1844-8801 1844-8801
DOI:	10.20869/AUDITF/2017/147/385