The detection of earnings manipulation: the three-phase cutting plane algorithm using mathematical programming

The primary goal of this study was to propose an algorithm using mathematical programming to detect earnings management practices. In order to evaluate the ability of this proposed algorithm, the traditional statistical models are used as a benchmark vis‐à‐vis their time series counterparts. As emer...

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Vydáno v:Journal of forecasting Ročník 29; číslo 5; s. 442 - 466
Hlavní autoři: Dikmen, Burcu, Küçükkocaoğlu, Güray
Médium: Journal Article
Jazyk:angličtina
Vydáno: Chichester, UK John Wiley & Sons, Ltd 01.08.2010
Wiley
Wiley Periodicals Inc
Témata:
Algorithms
Assets
cutting plane algorithm
Earnings
Earnings management
false financial statements
Financial information
Financial ratios
Financial statements
Forecasting techniques
Indexes
Industrial enterprises
Management
Manipulation
Manufacturing
Mathematical methods
mathematical model
Mathematical programming
Middle East
Motivation
Programming
Sales
Statistical analysis
Statistical models
Studies
Time series
Turkey
Working capital
Turkey
ISSN:0277-6693, 1099-131X
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Shrnutí:The primary goal of this study was to propose an algorithm using mathematical programming to detect earnings management practices. In order to evaluate the ability of this proposed algorithm, the traditional statistical models are used as a benchmark vis‐à‐vis their time series counterparts. As emerging techniques in the area of mathematical programming yield better results, application of suitable models is expected to result in highly performed forecasts. The motivation behind this paper is to develop an algorithm which will succeed in detecting companies that appeal to financial manipulation. The methodology is based on cutting plane formulation using mathematical programming. A sample of 126 Turkish manufacturing firms described over 10 financial ratios and indexes are used for detecting factors associated with false financial statements. The results indicate that the proposed three‐phase cutting plane algorithm outperforms the traditional statistical techniques which are widely used for false financial statement detections. Furthermore, the results indicate that the investigation of financial information can be helpful towards the identification of false financial statements and highlight the importance of financial ratios/indexes such as Days' Sales in Receivables Index (DSRI), Gross Margin Index (GMI), Working Capital Accruals to Total Assets (TATA) and Days to Inventory Index (DINV). Copyright © 2009 John Wiley & Sons, Ltd.
Bibliografie:istex:92E6D2A047D5B054AA9F1310275A182472DD3CF2
ark:/67375/WNG-NVDFR87Z-G
ArticleID:FOR1138
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ISSN:0277-6693
1099-131X
DOI:10.1002/for.1138