Annexes
Cours de société :ALLIANCE
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Colonne1
2016-04-04
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Colonne2
505
|
dividende
|
Colonne4
-1.94%
|
|
2016-05-02
|
500
|
|
-0.99%
|
|
2016-06-01
|
500
|
35
|
7.00%
|
|
2016-07-04
|
475
|
|
-5.00%
|
|
2016-08-01
|
465
|
|
-2.11%
|
|
2016-09-05
|
465
|
|
0.00%
|
|
2016-10-04
|
465
|
|
0.00%
|
|
2016-11-03
|
470
|
|
1.08%
|
|
2016-12-05
|
465
|
|
-1.06%
|
|
2017-01-02
|
465
|
|
0.00%
|
|
2017-02-01
|
465
|
|
0.00%
|
|
2017-03-01
|
465
|
|
0.00%
|
|
2017-04-03
|
450
|
|
-3.23%
|
|
2017-05-02
|
445
|
|
-1.11%
|
|
2017-06-05
|
445
|
45
|
10.11%
|
|
2017-07-03
|
400
|
|
-10.11%
|
|
2017-08-02
|
420
|
|
5.00%
|
|
2017-09-04
|
420
|
|
0.00%
|
|
2017-10-02
|
420
|
|
0.00%
|
|
2017-11-02
|
420
|
|
0.00%
|
|
2017-12-04
|
420
|
|
0.00%
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|
2018-01-02
|
420
|
|
0.00%
|
|
2018-02-05
|
420
|
|
0.00%
|
|
2018-03-05
|
420
|
|
0.00%
|
|
2018-04-02
|
425
|
|
1.19%
|
|
2018-05-03
|
425
|
|
0.00%
|
|
2018-06-04
|
430
|
|
1.18%
|
|
2018-07-02
|
430
|
45
|
10.47%
|
|
2018-08-01
|
395
|
|
-8.14%
|
|
2018-09-03
|
410
|
|
3.80%
|
|
2018-10-02
|
420
|
|
2.44%
|
|
2018-11-04
|
420
|
|
0.00%
|
|
2018-12-02
|
426
|
|
1.43%
|
|
2019-01-02
|
427
|
|
0.23%
|
|
2019-02-03
|
429
|
|
0.47%
|
|
2019-03-03
|
449
|
|
4.66%
|
|
2019-04-02
|
431
|
|
-4.01%
|
|
rendement
|
|
|
0.08%
|
|
variance
|
|
|
0.17%
|
|
ecart type
|
|
|
4.14%
|
103
En utilisant les instruction de R : Les
cours:
>rouiba=c(365,375,375,375,370,360,380,380,375,370,360,355,355,345,315,315,300,390,370,370,350,350,335,3
35,335,330,325,325,325,325,325,325,320,300,300,300,300,300,300,300,295,295,295,295,295,295,295,266,266,
240,240,235)
>time_series=ts(rouiba,start = 2015,end = 2019,frequency=12)
>plot(time_series)
>time_series = ts(biopharm,
start=2016,end=2019,frequency=12) >plot(time_series , main= `biopharm
`,xlab= `year', ylab='cours')
biopharm
2016 2017 2018 2019
Time
Test de dickey-fuller surdzindex :
>library(urca)
>r=diff(log(dzindex))
>x=ur.df(r,type='trend',lag=1);summary(x)
############################################### # Augmented
Dickey-Fuller Test Unit Root Test #
###############################################
Test regression trend
Call:
lm(formula = z.diff ~ z.lag.1 + 1 + tt + z.diff.lag)
Residuals:
Min 1Q Median 3Q Max
-0.068868 -0.019320 -0.004815 0.010043 0.136536
Coefficients:
Estimate Std. Error t value Pr(>|t|)
|
(Intercept) 2.449e-03
|
9.864e-03
|
0.248 0.805
|
|
|
|
|
z.lag.1 -9.712e-01
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2.107e-01
|
-4.610 3.21e-05 ***
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|
|
|
|
tt 4.274e-05
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3.272e-04
|
0.131 0.897
|
|
|
|
|
z.diff.lag -5.160e-02
|
1.466e-01
|
-0.352 0.726
|
|
|
|
|
Signif. codes: 0 `***'
|
0.001 `**'
|
0.01 `*' 0.05 `.' 0.1
|
`
|
'
|
1
|
Residual standard error: 0.03334 on 46 degrees of freedom
Multiple R-squared: 0.515, Adjusted R-squared: 0.4834
104
F-statistic: 16.28 on 3 and 46 DF, p-value: 2.381e-07 Value of
test-statistic is: -4.6102 7.0895 10.6341
|
Critical values for test statistics:
1pct 5pct 10pct
|
|
tau3
|
-4.04 -3.45
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-3.15
|
|
phi2
|
6.50
|
4.88
|
4.16
|
|
phi3
|
8.73
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6.49
|
5.47
|
Test de dickey-fuller sur ROUIBA :
>rouiba=c(365,375,375,375,370,360,380,380,375,370,360,355,355,345,315,315,3
00,390,370,370,350,350,335,335,335,330,325,325,325,325,325,325,320,300,300,
300,300,300,300,300,295,295,295,295,295,295,295,266,266,240,240,235)
>r=diff(log(rouiba))
>x=ur.df(r,type='trend',lag=1);summary(x)
############################################### # Augmented
Dickey-Fuller Test Unit Root Test #
###############################################
Test regression trend
Call:
lm(formula = z.diff ~ z.lag.1 + 1 + tt + z.diff.lag)
Residuals:
Min 1Q Median 3Q Max
-0.092416 -0.015044 -0.000449 0.015047 0.257674
Coefficients:
Estimate Std. Error t value Pr(>|t|)
|
(Intercept) 0.0006850
|
0.0145024
|
0.047 0.963
|
|
|
|
|
z.lag.1 -1.1186352
|
0.2343856
|
-4.773 1.95e-05 ***
|
|
|
|
|
tt -0.0004370
|
0.0005008
|
-0.873 0.387
|
|
|
|
|
z.diff.lag -0.1067734
|
0.1480586
|
-0.721 0.475
|
|
|
|
|
Signif. codes: 0 `***'
|
0.001 `**'
|
0.01 `*' 0.05 `.' 0.1
|
`
|
'
|
1
|
Residual standard error: 0.04844 on 45 degrees of freedom
Multiple R-squared: 0.6304, Adjusted R-squared: 0.6058 F-statistic: 25.59 on 3
and 45 DF, p-value: 8.206e-10
Value of test-statistic is: -4.7726 7.6036 11.3987
|
Critical values for test statistics:
1pct 5pct 10pct
|
|
tau3
|
-4.04 -3.45
|
-3.15
|
|
phi2
|
6.50
|
4.88
|
4.16
|
|
phi3
|
8.73
|
6.49
|
5.47
|
Test de dickey-fuller sur SAIDAL:
>SAIDAL=c(560,560,560,560,570,575,585,605,580,635,640,660,640,640,640,635,6
40,640,640,640,600,600,600,600,600,600,640,635,665,665,665,665,660,660,660,
660,660,640,620,620,620,620,620,580,580,605,605,635,635,635,610,609)
r=diff(log(SAI))
>x=ur.df(r,type='trend',lag=1);summary(x)
############################################### # Augmented
Dickey-Fuller Test Unit Root Test #
105
############################################### Test regression
trend
Call:
lm(formula = z.diff ~ z.lag.1 + 1 + tt + z.diff.lag)
Residuals:
Min 1Q Median 3Q Max
-0.068347 -0.007393 -0.000309 0.007837 0.072081
Coefficients:
Estimate Std. Error t value Pr(>|t|)
|
(Intercept) 0.0100816
|
0.0084123
|
1.198 0.237019
|
|
|
|
|
z.lag.1 -0.9566756
|
0.2242311
|
-4.266 0.000101 ***
|
|
|
|
|
tt -0.0003302
|
0.0002823
|
-1.170 0.248285
|
|
|
|
|
z.diff.lag -0.1701993
|
0.1493245
|
-1.140 0.260402
|
|
|
|
|
Signif. codes: 0 `***'
|
0.001 `**'
|
0.01 `*' 0.05 `.' 0.1
|
`
|
'
|
1
|
Residual standard error: 0.02734 on 45 degrees of freedom
Multiple R-squared: 0.5882, Adjusted R-squared: 0.5607 F-statistic: 21.42 on 3
and 45 DF, p-value: 9.084e-09
Value of test-statistic is: -4.2665 6.1067 9.1494
|
Critical values for test statistics:
1pct 5pct 10pct
|
|
tau3
|
-4.04 -3.45
|
-3.15
|
|
phi2
|
6.50
|
4.88
|
4.16
|
|
phi3
|
8.73
|
6.49
|
5.47
|
prevision de la serie NC-ROUIBA
>sarima.for(r,n.ahead=12,p=1,d=0,q=1)
$pred
Time Series:
Start = 52
End = 63
|
Frequency = 1
|
|
|
|
|
|
[1]
|
0.003725608
|
-0.018144936
|
-0.001074932
|
-0.014398105
|
-0.003999341
|
[6]
|
-0.012115598
|
-0.005780842
|
-0.010725132
|
-0.006866104
|
-0.009878083
|
[11]
|
-0.007527227
|
-0.009362075
|
|
|
|
|
$se
Time Series: Start = 52 End = 63
Frequency = 1
|
|
|
|
|
|
[1]
|
0.04563118
|
0.04648744
|
0.04700142
|
0.04731179
|
0.04749987
|
0.04761408
|
[7]
|
|
0.04768352
|
0.04772577
|
0.04775150
|
0.04776716
|
0.04777670
|
0.04778251
|
|
>library(quantmod) >getSymbols("AMZN", from =
"2000-01-01", to = "2019-01-01", src = "yahoo",
adjust = TRUE)
106
GOOGLE >getSymbols("GOOG", from = "1980-12-01", to =
"2018-12-31", src = "yahoo",
adjust = TRUE) >plot(Cl(GOOG))
FACEBOOK
1 ) Importer les données : >Library (quantmod)
>getSymbols("FB", from = "2012-05-01", to = "2018-12-31", src = "yahoo",
>plot(Cl(FB))
107
NC4-ROUIRAI
SPA
|
ETATS FINANCIERS 31.12.2918
|
~a
|
COMPTE DE RESULTATS PERIODE DU 01.01.2018 AU
31.12.2018
CHIFFRES EXPRIMES EN DINARS
|
NOTE
|
31.12.2018
|
31.12.2017
|
|
Chiffre d'affaires
|
6.1
|
5 936 615 369
|
5 659 391 237
|
|
Variation stocks produits finis et en-cours
|
6.2
|
( 164 687 788)
|
260 096 158
|
|
Production immobilisée
|
|
|
|
|
Subventions d'exploitation
|
|
|
|
|
PRODUCTION DE L'EXERCICE
|
|
5 771 927 581
|
5 919 487 396
|
|
Achats consommés
|
6.3
|
(3 618 612 603)
|
(3 607 011 260)
|
|
Services extérieurs et autres consommations
|
6.4
|
( 926 986 537)
|
(1 129 603 933)
|
|
CONSOMMATION DE L'EXERCICE
|
|
(4 545 599 140)
|
(4 736 615 193)
|
|
VALEUR AJOUTEE D'EXPLOITATION
|
|
1 226 328 441
|
1 182 872 203
|
|
Charges de personnel
|
6.5
|
( 711 630 826)
|
( 722 931 844)
|
|
Impôts taxes et versements assimilés
|
6.6
|
(50 733 316)
|
(54 753 822)
|
|
EXCEDENT BRUT D'EXPLOITATION
|
|
463 964 299
|
405 186 536
|
|
Autres produits opérationnels
|
6.7
|
89 892 128
|
47 099 948
|
|
Autres charges opérationnelles
|
6.8
|
( 127 735 114)
|
( 138 477 963)
|
|
Dotations aux amortissements et aux provisions
|
6.9
|
(534682928)
|
(744037721)
|
|
Reprise sur pertes de valeur et provisions
|
|
49 028 820
|
3 247 456
|
|
RESULTAT OPERATIONNEL
|
|
( 59 532 796)
|
( 426 981 745)
|
|
Produits financiers
|
6.10
|
21 728 182
|
15 082 804
|
|
Charges financières
|
6.11
|
( 290 470 023)
|
( 375 831 347)
|
|
RESULTAT FINANCER
|
|
( 268 741 841)
|
( 360 748 543)
|
|
|
|
|
|
RESULTAT ORDINAIRE AVANT IMPÔTS
|
|
( 328 274 637)
|
( 787 730 288)
|
|
Impôts exigibles sur résultat ordinaires
Impôts différés sur résultats ordinaires
Total des produits des activistes ordinaires
|
5
|
985
|
53 238 671
815 381
|
6
|
070
|
85
120 037
037 641
|
|
Total des charges des activités
ordinaires
|
(6
|
260
|
851
|
347)
|
(6
|
772
|
647
|
891)
|
|
|
|
|
|
|
|
|
|
|
RESULTAT NET DES ACTIVITES ORDINAIRES
|
(
|
275
|
035
|
966)
|
(
|
702
|
610
|
250)
|
|
|
|
|
|
|
|
|
|
|
RESULTAT NET DE L'EXERCICE
|
(
|
275
|
035
|
966)
|
(
|
702
|
610
|
250)
|
108
109
|
|
