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Log-Modulus for Knowledge Discovery in Databases of Financial Reports

Authors:
Duarte Trigueiros
Carolina Sam

Keywords: Type of Information Mining; Knowledge Extraction; Accounting Fraud Mining

Abstract:
An alternative is proposed to the use of ratios in financial predictive modelling. Such alternative, the “log-modulus”, overcomes limitations, which have hitherto thwarted most of the previous attempts to predict financial attributes from data. Moreover, the use of log-modulus opens-up the prospect of performing Knowledge Discovery in Databases (KDD) of financial reports. Using controlled experiments, the paper shows that models using log-modulus are accurate, robust and balanced in cases where ratios fail to deliver feasible results. The paper also provides a theoretical basis supporting the observed ability of log-modulus to allow knowledge discovery of financial statements.

Pages: 26 to 31

Copyright: Copyright (c) IARIA, 2016

Publication date: May 22, 2016

Published in: conference

ISSN: 2326-9332

ISBN: 978-1-61208-477-0

Location: Valencia, Spain

Dates: from May 22, 2016 to May 26, 2016