Firm Financial Distress Prediction With Statistical Methods: Prediction Accuracy Improvements Based on the Financial Data Restatements (CROSBI ID 614258)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Pervan, Ivica ; Pavić, Petra ; Pervan, Maja
engleski
Firm Financial Distress Prediction With Statistical Methods: Prediction Accuracy Improvements Based on the Financial Data Restatements
Firm failure phenomenon has been in the focus of academic research for many years. However, developed failure models entirely relay on original financial data and do not take into account potential data problems resulting from accounting manipulations. In this paper authors proposed the model for restatement of financial statements and tested it on the sample of 345 firms from Croatia. Empirical testing has shown that usage of restated financial data increases overall failure prediction accuracy by 5.3 percentage points. In the segment of non-distressed firms prediction accuracy was increased by 10.4 percentage points, while in the segment of distressed firms prediction accuracy was increased by 1.5 percentage points. Such findings indicate that accounting manipulations can affect failure prediction accuracy and that proposed model can be useful for prediction accuracy improvements.
financial distress prediction; accounting manipulations
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Podaci o prilogu
1134-1144.
2014.
objavljeno
Podaci o matičnoj publikaciji
8th International days of statistics and economics
978-80-87990-02-5
Podaci o skupu
8th International days of statistics and economics
predavanje
11.09.2014-13.09.2014
Prag, Češka Republika