) 2009 2014 ( abensania@yahoo.fr benchaa.oualid@univ-ghardaia.dzPrediction of the financial falter for somefoundationsoperating in the
private industrial in the state of Ghardaiaby
using discriminatory analysis during the period (2009-2014) Ben saniaAbderrahmane& Ben chaaOualid
University of Ghardaia; Algeria
Received:17 Jan 2017 Accepted: 03 May 2017 Published: 30 June 2017 1
: 2009 2014 100% . jel : O40 ,E24, C10 Abstract:
This article aims at studying prediction of the financial falter for some industrial foundations in the state of Ghardaia for the period between 2009 to 2014, by using a discriminatory analysis method .In order to answer the problematic of this paper, which focuses on the ability of the financial indicators to predict the falter of the industrial foundations.
The study included three industrial foundations, two faltering of foundations and one of them was healthy, that by trying to create a standard model for predicting the falter. The study showed that there are four out of eight financial indicators used in the study that have the ability to distinguish: Assets transferred to current liabilities, revenue to total assets, revenue to net capital, special fundus to non-current assets, while the study concluded that probability of discrimination the financial position through analytical reading of ratios was weak as the qualification quality of the model was very high 100%, through which it is possible to distinguish accurately between industrial foundations.
Key words: prediction , Financial falter, industrial foundations, Discriminat Analysis, Financial
indicators.
– - . - - - - - - - - - -
IMRAD 1
1.1 Beaver 1 - - - - 2.1 Altman 1977 Zeta 1969 1975 28 2 X1 / X2 / Z=
0.717x1+
0.847x2+
3.107x3+
0.420x4+
0.998x5X3 / X4 / X5 / Z 2.9 1.23 3.1 Kida 1980 Z 3 1 X X2 X3 X4 X5 Z Z 4.1 Althman &Mecough 4 X1 X2 X3 X4 X5 - Z 2,99 - Z 1,81 Z = 1.042x1+0.42x2- 0.461x3-0.463x4+0.271x5 Z
=
0.012x1+
0.014x2+
0.033x3+
0.006x4+
0.999x5- Z 1,81 2,99 5.1 Zavgren Christine Zavgren 5 X1 X2 X3 X4 X5 X6 X7 99 % 6 6.1 Sherrod 1987 6 7 X1 X2 X3 X4 X5 X6 . 8 01 Z Z ≥ 25 25≥ Z ≥ 20 20 ≥ Z ≥ 5 5 ≥ Z ≥ -5 Z ≤ -5 2016 376 Y=0.23883- 0.108x1-1.583x2-10.78X3+3.074X4+0.486x5-4.35x6+0.11x7 Z= 17x1+ 9x2+ 35x3+20x4 +1.2 x5+0.1 x6
2 1.2 2004 9 22 10 16 2000 2002 R3 R5 R19 R21 %91,9 869 % 869 % 2002 2001 2000 – – 2.1 2012 1 0 (SCF) 2003 2010
09 04 05 16 06 (X8) (X5) (X11) (X12) (X2) (X6) 917 % Z 0.05251 5.1620 Z 3.87998 2.3012 3.1
Sami ben djabeur
2011 1 1
Statut de la faillite en théorie financière: approches
théoriques et validations empiriques dans le contexte français
PLS PME 800 400 400 33 5925 % 94975 % 6050 % 9650 % Z= 1.455X2-0.411X5+0.013X6+5.637X8-0.316X12-20279
6050 % 98 % - - - (PLS) 1 . - P.O Oasis Plâtre (Spa) 180000000.00 - P.S les Pates du sersou
(Sarl) 200000000.00 - A.P Abras Pap industries
(Sarl) 500000.00 2 2009 2014
02 X1 X2 C1 C2 ROA ROE F1 F2 Analyses Discriminate 1 2 - - - - - - 1 3 1 4 - - - 3 1.3 P.O Oasis Plâtre
1.1.3 P.O 01 P.O Excel (X1) 2,8 3,8 2013 (X2) 0,005 2.1.3 P.O 02 P.O Excel (C1) 0,21 0,21 0,25 (C2) 0,6 0,7 X1 X2 C1 C2
3.1.3
P.O 2.1.3 03 P.O Excel (ROA) 0,005 0,01 (ROE) 0,01 002 4.1.3 P.O 04 P.O Excel (F1) 0,8 0,96 1 (F2) 0,4 2.3 P.S les Pates du sersou
1.2.3 P.S 05 P.S
Excel (X1) 2,20 (X2) 0,006 2013 2014 (P.O) P.S)( 2.2.3 P.S 06 P.S Excel (C1) 0,4 0,8 (C2) 2,9 13,2 25,0 - 3.2.3 P.S
07 P.S Excel (ROA) (-0,08) 0,05 (-0,1) 2014 2012 (ROE) 2009 0,30 0,1 0,14 4.2.3 P.S 08 P.S Excel (F1) (F2) (-0,4) (-0,2) 3.3 A.P
Abras Pap industries
1.3.3 A.P
