Using fuzzy c-means clustering algorithm in financial health scoring
Author:
Pinar OKAN GOKTEN, Furkan BASER, Soner GOKTEN
JEL:
G30, M49
DOI:
10.20869/AUDITF/2017/147/385
Keywords:
Accounting numbers, financial analysis,
financial classification, Fuzzy c-means (FCM) clustering
algorithm
Abstract:
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.
Abstract(212KB)
Article(634KB)