Trabajo final; Integrantes: Laura Leon, Carolina Bonilla y July Prada

library(readxl)
BIC <- read_excel("C:/Users/abonilla32/Desktop/ACCIONES FIN.xlsx", sheet = "BIC", col_names = FALSE)
View(BIC)

colnames(BIC)<- c("Date","Close","Open","High","Low","Vol","Change%")

library(readxl)
CHL <- read_excel("C:/Users/abonilla32/Desktop/ACCIONES FIN.xlsx", sheet = "CHL", col_names = FALSE)
View(CHL)

colnames(CHL)<- c("Date","Close","Open","High","Low","Vol","Change%")

library(readxl)
SIS <- read_excel("C:/Users/abonilla32/Desktop/ACCIONES FIN.xlsx", sheet = "SIS", col_names = FALSE)
View(SIS)

colnames(SIS)<- c("Date","Close","Open","High","Low","Vol","Change%")

library(readxl)
IMI <- read_excel("C:/Users/abonilla32/Desktop/ACCIONES FIN.xlsx", 
    sheet = "IMI", col_names = FALSE)
View(IMI)

colnames(IMI)<- c("Date","Close","Open","High","Low","Vol","Change%")

library(readxl)
    CCB <- read_excel("C:/Users/abonilla32/Desktop/ACCIONES FIN.xlsx", 
    sheet = "CCB", col_names = FALSE)
View(CCB)

colnames(CCB)<- c("Date","Close","Open","High","Low","Vol","Change%")


Datev <-as.Date(CHL$Date,Sys.timezone(location = TRUE), "%d%m$y")

CHLV <- matrix(CHL$Close)
SISV <-matrix(SIS$Close)
BICV<-matrix(BIC$Close)
IMIV<-matrix(IMI$Close)
CCBV<- matrix(CCB$Close)


CIERRES <- cbind.data.frame(Datev,CHLV,SISV,BICV,IMIV,CCBV)
colnames(CIERRE2)<- c("Date","CHL","SIS","BIC","IMI","CCB")
CIERRE1<-cbind.data.frame(Datev,CHLV,SISV)
CIERRE2<-cbind.data.frame(Datev,BICV,SISV,CCBV,IMIV,CHLV)
CIERRE3 <-cbind.data.frame(Datev,BICV,IMIV,CCBV)

CIERRES$Date <- as.matrix(CIERRE2[2:5])
row.names(CIERRE2)<- as.character(IMI$Date)

Normalidad

Pcierre<- as.timeSeries(CIERRE2)
Pcierre1 <- as.timeSeries(CIERRE1)
Pcierre2<- as.timeSeries(CIERRE3)
jarqueberaTest(Pcierre)

Title:
 Jarque - Bera Normalality Test

Test Results:
  STATISTIC:
    X-squared: 605.2956
  P VALUE:
    Asymptotic p Value: < 2.2e-16 

Description:
 Tue May 28 15:47:58 2019 by user: abonilla32

shapiroTest (as.vector(Pcierre1))

Title:
 Shapiro - Wilk Normality Test

Test Results:
  STATISTIC:
    W: 0.8284
  P VALUE:
    < 2.2e-16 

Description:
 Tue May 28 15:47:58 2019 by user: abonilla32

shapiroTest (as.vector(Pcierre2))

Title:
 Shapiro - Wilk Normality Test

Test Results:
  STATISTIC:
    W: 0.8998
  P VALUE:
    < 2.2e-16 

Description:
 Tue May 28 15:47:58 2019 by user: abonilla32

dagoTest(Pcierre)

Title:
 D'Agostino Normality Test

Test Results:
  STATISTIC:
    Z3  | Skewness: 11.1921
  P VALUE:
    Skewness Test: < 2.2e-16 

Description:
 Tue May 28 15:47:58 2019 by user: abonilla32

ksnormTest(Pcierre)

ties should not be present for the Kolmogorov-Smirnov testties should not be present for the Kolmogorov-Smirnov testties should not be present for the Kolmogorov-Smirnov test

Title:
 One-sample Kolmogorov-Smirnov test

Test Results:
  STATISTIC:
    D: 1
  P VALUE:
    Alternative Two-Sided: < 2.2e-16 
    Alternative      Less: < 2.2e-16 
    Alternative   Greater: 1 

Description:
 Tue May 28 15:47:58 2019 by user: abonilla32

boxPlot(Pcierre)

Este gráfico brinda información sobre la forma general de la curva: simetría, curtosis (curvas más “afinadas” o más “aplanadas”), el punto de la mediana, la distribución de las observaciones a ambos lados de los valores centrales y la presencia (y el/los valor/es) de valores atípicos. Para este caso especifico, los datos no son simetricos, excepto por CEMARGOS, que presenta simetria en su distribucion.

sampleMED(Pcierre)

  MED 
16200 

sampleIQR(Pcierre)

  IQR 
20540 

sampleSKEW(Pcierre)

     SKEW 
0.5481986 

sampleKURT(Pcierre)

    KURT 
0.680258 

qqnormPlot(Pcierre)

Vemos que los datos generados por la función rnorm presentan colas más cortas que lo esperable para una distribución t con 2 grados de libertad; es decir, la prueba presenta una normalidad en sus cuantiles.

RETORNOS

C <- subset(CIERRES,select = c(CHLV, SISV,BICV,CCBV,IMIV))
diff(as.matrix(log(C)), 1,1)

             CHLV          SISV          BICV         CCBV          IMIV
2     0.024044874  0.0079230748 -0.0156135129 -0.002525254  0.0014398851
3     0.013941245  0.0089787360  0.0005074854  0.010062978  0.0353393664
4     0.030416608 -0.0044792908 -0.0010152285  0.001250782  0.0041580101
5    -0.010384309  0.0072686929  0.0181182611  0.004987542  0.0000000000
6     0.016563526  0.0027816430  0.0197537287  0.003724399  0.0027624327
7    -0.002055499  0.0000000000  0.0265395552  0.001238390 -0.0069204428
8    -0.004123717  0.0110498362  0.0075901693  0.001236859  0.0069204428
9    -0.018770103  0.0000000000  0.0004724782  0.000000000  0.0055020772
10    0.010471300 -0.0027510334 -0.0023646263 -0.001236859  0.0013708021
11    0.038819992 -0.0082988028  0.0014194467 -0.003719781 -0.0137933221
12    0.001001502 -0.0061298604  0.0047169899  0.003719781 -0.0224728559
13    0.001000500 -0.0129397023 -0.0252574780  0.003705996 -0.0056980211
14    0.001998003 -0.0131093356 -0.0121390177 -0.003705996  0.0028530690
15   -0.007010544  0.0045792868 -0.0004886391 -0.004962789 -0.0129034048
16   -0.104802324  0.0253749166  0.0260506772  0.004962789  0.0171678036
17   -0.006718950  0.0083172090  0.0052244241  0.004938282  0.0070671672
18    0.017817843  0.0142546273  0.0089602109  0.001230769  0.0056179923
19    0.000000000 -0.0054585288  0.0070175727 -0.011131840 -0.0056179923
20    0.010977059 -0.0005474952  0.0023282898  0.006199648  0.0056179923
21    0.004357305 -0.0088009369 -0.0140517535 -0.011187189  0.0111421766
22   -0.010929071 -0.0099945307 -0.0243506899 -0.002503130  0.0041465160
23    0.003291281 -0.0011166947 -0.0141155909  0.003752350 -0.0041465160
24    0.014138354  0.0000000000 -0.0148150858 -0.007518832  0.0151205630
25    0.015005641  0.0105585866 -0.0120121564 -0.008844025  0.0054421903
26    0.021053409  0.0126340598  0.0169749458  0.000000000 -0.0150378774
27    0.000000000 -0.0176216013 -0.0154655115  0.000000000 -0.0069108775
28   -0.021053409 -0.0134230203  0.0040140546 -0.007643349  0.0055325176
29    0.010582109  0.0217218231  0.0237517351  0.015228721  0.0136988444
30   -0.004219416  0.0054945193 -0.0073619964 -0.005050516  0.0013596195
31    0.004219416  0.0179206534  0.0367546207  0.025001302  0.0081191244
32   -0.008456710 -0.0070213629 -0.0196601873  0.000000000  0.0173685061
33   -0.013896536 -0.0054347960 -0.0072904333 -0.012422520  0.0000000000
34   -0.009735069  0.0016335424 -0.0221957324 -0.025317808  0.0052840281
35   -0.021978907 -0.0070980369 -0.0100251466 -0.007722046 -0.0513626401
36    0.004434597 -0.0165749651  0.0045237574  0.020461072  0.0178698913
37    0.046469733 -0.0140254754 -0.0166881243 -0.002534856  0.0000000000
38   -0.013822655 -0.0113637587 -0.0268750025  0.002534856  0.0000000000
39   -0.012931215 -0.0045819095  0.0026157483 -0.007623925 -0.0123373738
40   -0.023039966 -0.0127095876 -0.0221879150 -0.014129972 -0.0138891122
41    0.020868412  0.0144302648  0.0169495583  0.011575692  0.0000000000
42    0.040474108  0.0045740503  0.0005250722  0.012706651 -0.0013995804
43    0.001043297 -0.0108977276 -0.0121469674  0.003780723 -0.0255333020
44    0.012435393  0.0040287824 -0.0112210635  0.013741628  0.0227282511
45    0.018367863  0.0034403704 -0.0026903433  0.006184312  0.0153313107
46    0.011060947  0.0017157568  0.0000000000  0.002463055  0.0096353120
47   -0.004008021  0.0022831060  0.0026903433  0.001229256  0.0013689256
48   -0.020284671  0.0203167259  0.0000000000 -0.018599420  0.0135871655
49   -0.039712637  0.0022321438 -0.0005374899 -0.021506205 -0.0108549234
50    0.023183335 -0.0162970733 -0.0102675855 -0.002560821 -0.0041011677
51    0.064538521 -0.0171432770 -0.0253038803  0.000000000  0.0068259651
52    0.055094654 -0.0057803629 -0.0083916576  0.000000000  0.0027173930
53    0.003690041  0.0138171456 -0.0084626739  0.001281230 -0.0081744324
54    0.032611586  0.0000000000 -0.0028368813  0.029024119  0.0095303649
55   -0.081678031  0.0005715919  0.0141046062  0.013588844 -0.0108992905
56   -0.037442797 -0.0028612323 -0.0056179923  0.000000000  0.0013689256
57   -0.036813973  0.0022896404 -0.0056497325 -0.001227747 -0.0013689256
58    0.008298803  0.0068376335  0.0062129542  0.007343974 -0.0096353120
59    0.018424267 -0.0119967163  0.0061745916  0.000000000 -0.0097290552
60   -0.008146685  0.0017226533  0.0027940784 -0.006116227  0.0055710450
61   -0.055715933  0.0102740630  0.0044543503  0.006116227 -0.0125787822
62    0.037139547  0.0219048354  0.0077476868  0.012121361  0.0028089906
63   -0.046916920  0.0000000000  0.0022026441  0.006006024  0.0000000000
64   -0.005473467 -0.0134230203 -0.0166393190 -0.008418570 -0.0127030643
65   -0.019956316 -0.0256643684 -0.0272125635  0.009615459  0.0169018108
66   -0.023797157 -0.0040521040 -0.0127242897 -0.034066555 -0.0154823641
67    0.048134641 -0.0104957232  0.0034863487 -0.003719781 -0.0142859572
68   -0.007679687  0.0110756014 -0.0075691773 -0.020075957 -0.0188821877
69   -0.030186753 -0.0058139699 -0.0005846244 -0.001268231 -0.0177519455
70    0.063757853 -0.0117303398  0.0029197101 -0.003814372  0.0059523985
71    0.010593319 -0.0124667688  0.0058139699 -0.019293203 -0.0104400650
72   -0.001054296 -0.0023923456 -0.0058139699 -0.026317308 -0.0350913198
73   -0.017021688 -0.0162997874  0.0069727185 -0.005347606  0.0015515907
74   -0.017316450 -0.0036585407 -0.0011587487 -0.043842638  0.0000000000
75   -0.022075952 -0.0048989688 -0.0029027597 -0.008438869 -0.0093458624
76   -0.041008024  0.0030646668 -0.0093458624 -0.002828856  0.0124418401
77   -0.047628049  0.0000000000  0.0005866823 -0.001417435  0.0000000000
78    0.060337637 -0.0055231807  0.0000000000  0.000000000 -0.0015467907
79   -0.016204058  0.0061349886  0.0046811086  0.004246291  0.0015467907
80   -0.110951117 -0.0129272345 -0.0076179683  0.002820876  0.0122889411
81   -0.022413595 -0.0006197707 -0.0017662648  0.000000000 -0.0138357319
82    0.005319161  0.0006197707 -0.0065031267 -0.002820876 -0.0140298482
83   -0.021448543  0.0006193868 -0.0282725598  0.002820876 -0.0031446567
84   -0.034462404 -0.0062112001 -0.0024434954  0.000000000 -0.0158733492
85   -0.001403509  0.0024891114 -0.0216391751  0.012596388  0.0063796070
86   -0.005633818  0.0037220887  0.0000000000 -0.012596388 -0.0176427992
87    0.044206093 -0.0055883412 -0.0189280099 -0.019915310  0.0032310206
88   -0.002706362  0.0018662525 -0.0063897981  0.002869442 -0.0162605209
89    0.002706362 -0.0056092388 -0.0096619109  0.004288784  0.0000000000
90   -0.055569851  0.0087119406 -0.0288923577  0.015570024  0.0000000000
91   -0.008608375 -0.0200257005  0.0308322225 -0.016997576 -0.0232182901
92    0.103918554  0.0050441469 -0.0175957619 -0.026050677  0.0232182901
93    0.030692946  0.0118788518  0.0278786288  0.026050677  0.0000000000
94   -0.030692946  0.0000000000  0.0164873741  0.000000000  0.0016380020
95   -0.013072082  0.0006213110 -0.0094787440  0.012775191 -0.0016380020
96    0.000000000  0.0043384016  0.0207358985 -0.015636424  0.0000000000
97    0.051293294  0.0165597160  0.0080520720  0.000000000  0.0000000000
98    0.036813973  0.0096853057  0.0146971415  0.002861232 -0.0082304991
99    0.006006024 -0.0170113458 -0.0036540845 -0.001429593  0.0244910200
100   0.021327823 -0.0006129329 -0.0061199701  0.001429593  0.0144117787
101   0.001171646  0.0048929761 -0.0049230869 -0.002861232  0.0110673066
102   0.003506725 -0.0042800432  0.0171258008 -0.002869442  0.0140517535
103  -0.001167542  0.0067175825  0.0233753526  0.005730675  0.0000000000
104   0.000000000 -0.0012180269 -0.0107207697  0.000000000  0.0000000000
105  -0.002339182 -0.0048869981  0.0000000000  0.000000000  0.0153849188
106  -0.033336420 -0.0110838573 -0.0359685222  0.000000000  0.0166544349
107   0.004830927  0.0000000000  0.0299624982  0.002853069 -0.0445200150
108  -0.036813973 -0.0049658699 -0.0006025912 -0.002853069 -0.0062992334
109   0.000000000 -0.0131539635  0.0036101122  0.000000000  0.0402531124
110   0.004987542  0.0242926926  0.0172674728  0.007117468  0.0372343831
111  -0.010000083 -0.0024645730 -0.0323963544  0.001417435 -0.0073367901
112   0.002509412  0.0024645730  0.0157293019  0.000000000  0.0131677104
113   0.002503130 -0.0018478601 -0.0006004203  0.000000000  0.0086831226
114   0.250758718 -0.0049443858 -0.0072333046 -0.001417435 -0.0086831226
115   0.103413095  0.0220597181  0.0102318076  0.012685160  0.0272418280
116  -0.019486888 -0.0060790461  0.0160383598 -0.012685160  0.0223785563
117   0.001787311 -0.0110362861 -0.0100681928 -0.007117468 -0.0167367924
118  -0.027150989 -0.0262351087 -0.0487901642  0.001427552  0.0139667075
119  -0.062461170 -0.0063492277 -0.0221178053 -0.001427552 -0.0083565946
120  -0.015748357  0.0050826031  0.0252379326 -0.012940511  0.0138891122
121  -0.018018506  0.0012666246  0.0031104224  0.012940511  0.0136988444
122   0.010050336  0.0000000000 -0.0062305498  0.000000000 -0.0136988444
123  -0.016129382 -0.0095390230 -0.0317486983 -0.001429593 -0.0152886925
124   0.028057953 -0.0032000027  0.0000000000  0.000000000  0.0027972046
125  -0.020969316 -0.0064308903 -0.0006453695  0.002857145 -0.0154823641
126   0.009040745  0.0128206884 -0.0288166632  0.001425517 -0.0142859572
127   0.011928571  0.0025445306 -0.0160753629 -0.007147993 -0.0336535050
128  -0.011928571  0.0163834793  0.0060585847  0.008571481  0.0044543503
129   0.048790164 -0.0075282664 -0.0074099362 -0.001423488  0.0320727199
130  -0.009569451  0.0012586534 -0.0067842865 -0.014347448  0.0014336920
131   0.013371737  0.0205422723  0.0215496555  0.014347448  0.0170458673
132   0.003787883  0.0225413138  0.0073017251  0.018349139 -0.0156142278
133  -0.013320844 -0.0090772182 -0.0006615945  0.009742596  0.0156142278
134   0.015209419  0.0036407807  0.0006615945  0.011019395  0.0056179923
135  -0.019048195  0.0054364374  0.0131407936  0.000000000  0.0055866067
136   0.005752652  0.0243987110  0.0206725708  0.013605652 -0.0182717662
137   0.013295542 -0.0035335726  0.0221317917 -0.013605652  0.0000000000
138   0.051481956 -0.0256960657 -0.0311235029  0.000000000  0.0042462909
139  -0.014440684  0.0096386288 -0.0051746558  0.013605652  0.0084388686
140   0.018018506  0.0101402599  0.0141663670 -0.013605652  0.0111421766
141   0.007117468  0.0000000000  0.0158582454 -0.009635312  0.0151205630
142  -0.036105005 -0.0179645550  0.0037688487  0.023240964  0.0067981227
143  -0.007380107  0.0072245949  0.0000000000  0.000000000  0.0027063616
144   0.003696862  0.0248828004  0.0081174345  0.039740329  0.0013504391
145  -0.003696862  0.0035046765  0.0043437859  0.000000000 -0.0027027043
146   0.000000000  0.0046538769 -0.0062112001  0.000000000 -0.0205065286
147   0.000000000  0.0011600929 -0.0081326692 -0.005208345  0.0068823396
148   0.000000000  0.0075079764 -0.0171052634  0.005208345  0.0000000000
149   0.027398974 -0.0262329237 -0.0057673982  0.000000000  0.0190223127
150  -0.009049836 -0.0112861311 -0.0103360093  0.002594035  0.0053691404
151   0.026907453 -0.0083983697  0.0218377336 -0.001296176 -0.0013395849
152   0.017544310  0.0089955629  0.0006351223 -0.003898640  0.0053476063
153  -0.030011078  0.0023852128 -0.0095694510  0.001301236  0.0263173083
154   0.030011078 -0.0023852128  0.0259426128 -0.022354646 -0.0602188600
155  -0.006980831  0.0323082432 -0.0132035870  0.021053409 -0.0055325176
156  -0.014109582  0.0000000000 -0.0249932907  0.002600782  0.0027700849
157  -0.017921627  0.0028860049 -0.0078176294 -0.009132484 -0.0111266795
158  -0.020092000 -0.0139294185 -0.0059035921 -0.003939598  0.0111266795
159  -0.022388995  0.0110434136  0.0032840752  0.005249356  0.0164612771
160   0.029741969 -0.0057971177  0.0233322315  0.009120584  0.0000000000
161   0.060409128 -0.0146415500 -0.0246445676  0.016720647 -0.0068259651
162   0.010291686 -0.0184583984  0.0220788189 -0.044335814  0.0013689256
163   0.010186845  0.0041979072  0.0146639542  0.013245227 -0.0054869822
164   0.013423020 -0.0017969457  0.0156989095  0.031090587  0.0109440217
165   0.047201601  0.0201787262  0.0129992545  0.059423420  0.0373875321
166   0.001588563  0.0318037791  0.0116173731  0.034262064  0.0245967093
167   0.000000000  0.0213972127  0.0096794464  0.024097552  0.0114432272
168   0.000000000  0.0027816430 -0.0006022283  0.022422464  0.0025252539
169   0.000000000  0.0000000000 -0.0084695001 -0.030390634  0.0087885060
170   0.004750603  0.0005554013  0.0072639545  0.028170877  0.0037429863
171  -0.037011465  0.0268435729  0.0167468029 -0.005571045  0.0000000000
172  -0.016529302 -0.0081411576 -0.0023752980  0.005571045  0.0000000000
173   0.059840000  0.0097614658 -0.0186023966  0.011049836 -0.0087555281
174   0.003134799 -0.0016203082 -0.0006058770  0.006571765  0.0050125418
175   0.044383719 -0.0027063616  0.0030257209  0.001091108  0.0062305498
176   0.025130665 -0.0081633106  0.0102195058 -0.001091108  0.0074257767
177   0.007272759 -0.0054794658  0.0107080143 -0.006571765 -0.0136563264
178  -0.008733680  0.0060257646 -0.0041506137 -0.001099505  0.0000000000
179   0.030239885 -0.0032822787 -0.0125562188 -0.004410150  0.0000000000
180   0.015482364  0.0070980369 -0.0036166405 -0.003320424  0.0000000000
181   0.005571045 -0.0065502418  0.0018099552 -0.006674107 -0.0012507819
182   0.006920443  0.0130578569 -0.0078669090  0.009994531 -0.0062774845
183   0.006872879  0.0026990570  0.0198502758  0.016438726  0.0075282664
184  -0.005494519 -0.0163047090  0.0065301508 -0.010929071  0.0012492194
185   0.032523192 -0.0110193952 -0.0017767254 -0.022223137  0.0012476608
186   0.026317308  0.0055248759  0.0082645098  0.033152207  0.0197537287
187  -0.006514681 -0.0105234978 -0.0262075750 -0.001087548 -0.0049019706
188  -0.033225648  0.0072122365  0.0244423494  0.001087548  0.0024539890
189  -0.013605652 -0.0022136146 -0.0226334855  0.000000000 -0.0049140148
190  -0.008253142  0.0278630426  0.0220443839  0.009735069  0.0098040001
191  -0.006930035 -0.0190378336  0.0023543272 -0.003234504 -0.0024420037
192   0.039541620 -0.0071645388  0.0000000000  0.008602204 -0.0061312271
193   0.015915455 -0.0022148403 -0.0094507496  0.010649728 -0.0111318404
194   0.025975486  0.0197591500  0.0257776429  0.012631747  0.0086687849
195  -0.005141400  0.0021715535  0.0028876717  0.005216496  0.0000000000
196  -0.009061551  0.0107875911 -0.0040450792  0.001040042  0.0012322860
197   0.016763771  0.0005363368  0.0074993141  0.005184045 -0.0024660925
198   0.021506205  0.0021424754  0.0022962123 -0.001034661 -0.0024721891
199   0.000000000 -0.0091373922  0.0108355779  0.001034661  0.0073983075
200   0.017370164 -0.0037868587 -0.0045480465  0.004127973 -0.0086366977
201  -0.006169051 -0.0010845988  0.0085106897 -0.001030397  0.0000000000
 [ reached getOption("max.print") -- omitted 1015 rows ]

GRAFFICAS #HISTOGRAMA#

RETOR <- as.matrix(C$CHLV,C$SISV,C$BICV,C$CCBV,C$IMIV)
RETOR

         [,1]
   [1,]  4520
   [2,]  4630
   [3,]  4695
   [4,]  4840
   [5,]  4790
   [6,]  4870
   [7,]  4860
   [8,]  4840
   [9,]  4750
  [10,]  4800
  [11,]  4990
  [12,]  4995
  [13,]  5000
  [14,]  5010
  [15,]  4975
  [16,]  4480
  [17,]  4450
  [18,]  4530
  [19,]  4530
  [20,]  4580
  [21,]  4600
  [22,]  4550
  [23,]  4565
  [24,]  4630
  [25,]  4700
  [26,]  4800
  [27,]  4800
  [28,]  4700
  [29,]  4750
  [30,]  4730
  [31,]  4750
  [32,]  4710
  [33,]  4645
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  [35,]  4500
  [36,]  4520
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  [38,]  4670
  [39,]  4610
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  [41,]  4600
  [42,]  4790
  [43,]  4795
  [44,]  4855
  [45,]  4945
  [46,]  5000
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  [53,]  5430
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  [55,]  5170
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  [58,]  4840
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  [65,]  4465
  [66,]  4360
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 [103,]  4280
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 [105,]  4270
 [106,]  4130
 [107,]  4150
 [108,]  4000
 [109,]  4000
 [110,]  4020
 [111,]  3980
 [112,]  3990
 [113,]  4000
 [114,]  5140
 [115,]  5700
 [116,]  5590
 [117,]  5600
 [118,]  5450
 [119,]  5120
 [120,]  5040
 [121,]  4950
 [122,]  5000
 [123,]  4920
 [124,]  5060
 [125,]  4955
 [126,]  5000
 [127,]  5060
 [128,]  5000
 [129,]  5250
 [130,]  5200
 [131,]  5270
 [132,]  5290
 [133,]  5220
 [134,]  5300
 [135,]  5200
 [136,]  5230
 [137,]  5300
 [138,]  5580
 [139,]  5500
 [140,]  5600
 [141,]  5640
 [142,]  5440
 [143,]  5400
 [144,]  5420
 [145,]  5400
 [146,]  5400
 [147,]  5400
 [148,]  5400
 [149,]  5550
 [150,]  5500
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 [152,]  5750
 [153,]  5580
 [154,]  5750
 [155,]  5710
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 [158,]  5420
 [159,]  5300
 [160,]  5460
 [161,]  5800
 [162,]  5860
 [163,]  5920
 [164,]  6000
 [165,]  6290
 [166,]  6300
 [167,]  6300
 [168,]  6300
 [169,]  6300
 [170,]  6330
 [171,]  6100
 [172,]  6000
 [173,]  6370
 [174,]  6390
 [175,]  6680
 [176,]  6850
 [177,]  6900
 [178,]  6840
 [179,]  7050
 [180,]  7160
 [181,]  7200
 [182,]  7250
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 [184,]  7260
 [185,]  7500
 [186,]  7700
 [187,]  7650
 [188,]  7400
 [189,]  7300
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 [201,]  8080
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 [204,]  8160
 [205,]  8000
 [206,]  8190
 [207,]  8160
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 [245,]  8750
 [246,]  8860
 [247,]  8620
 [248,]  8730
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 [254,]  9130
 [255,]  9240
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 [259,]  9500
 [260,]  9530
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 [264,]  9600
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 [267,]  9090
 [268,]  9090
 [269,]  9100
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 [273,]  8520
 [274,]  8360
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 [285,]  9660
 [286,]  9750
 [287,]  9400
 [288,]  9290
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 [290,]  9500
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 [292,] 10040
 [293,] 10060
 [294,] 10100
 [295,] 10040
 [296,] 10160
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 [298,]  9990
 [299,]  9990
 [300,] 10100
 [301,] 10200
 [302,] 10300
 [303,] 10520
 [304,] 10740
 [305,] 10760
 [306,] 10800
 [307,] 10980
 [308,] 11000
 [309,] 10920
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 [311,] 11100
 [312,] 11060
 [313,] 11080
 [314,] 11040
 [315,] 10940
 [316,] 10960
 [317,] 10880
 [318,] 10800
 [319,] 10800
 [320,] 10900
 [321,] 10920
 [322,] 10880
 [323,] 10800
 [324,] 11040
 [325,] 11060
 [326,] 10880
 [327,] 10800
 [328,] 10860
 [329,] 10960
 [330,] 11000
 [331,] 11000
 [332,] 10840
 [333,] 10780
 [334,] 10800
 [335,] 10800
 [336,] 10840
 [337,] 10840
 [338,] 10860
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 [340,] 10860
 [341,] 10660
 [342,] 10760
 [343,] 10800
 [344,] 10840
 [345,] 10860
 [346,] 11000
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 [348,] 10880
 [349,] 11000
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 [351,] 10960
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 [353,] 11240
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 [357,] 11100
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 [362,] 10880
 [363,] 10820
 [364,] 10880
 [365,] 10880
 [366,] 11000
 [367,] 10960
 [368,] 10780
 [369,] 11000
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 [372,] 11520
 [373,] 11500
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 [375,] 11400
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 [378,] 11520
 [379,] 11520
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 [381,] 11680
 [382,] 11800
 [383,] 11800
 [384,] 11620
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 [386,] 11840
 [387,] 11800
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 [389,] 11540
 [390,] 11500
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 [392,] 11400
 [393,] 11480
 [394,] 11580
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 [396,] 11720
 [397,] 11860
 [398,] 11840
 [399,] 11800
 [400,] 11720
 [401,] 11700
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 [403,] 11740
 [404,] 11700
 [405,] 11760
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 [411,] 11120
 [412,] 10940
 [413,] 10900
 [414,] 10900
 [415,] 10940
 [416,] 10900
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 [418,] 10880
 [419,] 10880
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 [421,] 10680
 [422,] 10660
 [423,] 10600
 [424,] 10600
 [425,] 10700
 [426,] 10700
 [427,] 10700
 [428,] 10740
 [429,] 10800
 [430,] 10800
 [431,] 10900
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 [433,] 10900
 [434,] 10680
 [435,] 10620
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 [440,] 11560
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 [443,] 11700
 [444,] 11640
 [445,] 11800
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 [447,] 11900
 [448,] 11920
 [449,] 11820
 [450,] 11700
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 [455,] 11600
 [456,] 11600
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 [459,] 11600
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 [464,] 11720
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 [684,] 12600
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 [690,] 12040
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 [693,] 12500
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 [703,] 12900
 [704,] 12720
 [705,] 12640
 [706,] 12600
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 [708,] 12800
 [709,] 12900
 [710,] 12840
 [711,] 12740
 [712,] 12700
 [713,] 12860
 [714,] 12980
 [715,] 13180
 [716,] 13480
 [717,] 13200
 [718,] 13280
 [719,] 13300
 [720,] 13120
 [721,] 12900
 [722,] 12960
 [723,] 13000
 [724,] 13000
 [725,] 13200
 [726,] 13200
 [727,] 13240
 [728,] 13600
 [729,] 13460
 [730,] 13500
 [731,] 12800
 [732,] 12980
 [733,] 12560
 [734,] 12600
 [735,] 13040
 [736,] 13060
 [737,] 12900
 [738,] 12720
 [739,] 12800
 [740,] 12900
 [741,] 13000
 [742,] 13200
 [743,] 13360
 [744,] 13200
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 [746,] 13040
 [747,] 13000
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 [750,] 13100
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 [756,] 13000
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 [777,] 10720
 [778,] 10700
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 [780,] 10380
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 [782,] 10100
 [783,]  9960
 [784,] 10000
 [785,] 10000
 [786,]  9990
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 [788,]  9830
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 [793,]  9560
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 [796,]  9350
 [797,]  9700
 [798,]  9700
 [799,] 10000
 [800,] 10020
 [801,] 10160
 [802,] 10100
 [803,] 10320
 [804,] 10060
 [805,] 10180
 [806,] 10240
 [807,] 10100
 [808,] 10300
 [809,] 10380
 [810,] 10180
 [811,] 10000
 [812,] 10300
 [813,] 10100
 [814,] 10400
 [815,] 10400
 [816,] 10440
 [817,] 10300
 [818,] 10200
 [819,] 10280
 [820,] 10280
 [821,] 10100
 [822,]  9800
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 [827,]  9350
 [828,]  9490
 [829,]  9500
 [830,]  9420
 [831,]  9300
 [832,]  8900
 [833,]  9000
 [834,]  9300
 [835,]  9370
 [836,]  9180
 [837,]  9050
 [838,]  8900
 [839,]  8990
 [840,]  8950
 [841,]  9150
 [842,]  9150
 [843,]  9150
 [844,]  9170
 [845,]  9100
 [846,]  9100
 [847,]  9090
 [848,]  9090
 [849,]  9100
 [850,]  9260
 [851,]  9320
 [852,]  9580
 [853,]  9900
 [854,]  9980
 [855,] 10140
 [856,] 10080
 [857,] 10480
 [858,] 10400
 [859,] 10080
 [860,] 10300
 [861,] 10560
 [862,] 10720
 [863,] 11280
 [864,] 11000
 [865,] 11320
 [866,] 11480
 [867,] 11500
 [868,] 11500
 [869,] 11500
 [870,] 11720
 [871,] 11680
 [872,] 11600
 [873,] 11900
 [874,] 11900
 [875,] 12180
 [876,] 12080
 [877,] 12300
 [878,] 12100
 [879,] 12200
 [880,] 12200
 [881,] 12200
 [882,] 12200
 [883,] 12500
 [884,] 12700
 [885,] 12840
 [886,] 12480
 [887,] 12680
 [888,] 12080
 [889,] 11600
 [890,] 11700
 [891,] 11420
 [892,] 11500
 [893,] 11560
 [894,] 11500
 [895,] 11500
 [896,] 11600
 [897,] 11740
 [898,] 11760
 [899,] 11700
 [900,] 11820
 [901,] 11220
 [902,] 11080
 [903,] 10940
 [904,] 10500
 [905,] 11000
 [906,] 11480
 [907,] 11580
 [908,] 11500
 [909,] 11820
 [910,] 11800
 [911,] 11600
 [912,] 11600
 [913,] 11700
 [914,] 11840
 [915,] 12120
 [916,] 12280
 [917,] 12500
 [918,] 12640
 [919,] 12500
 [920,] 12580
 [921,] 12500
 [922,] 12600
 [923,] 12700
 [924,] 12700
 [925,] 12540
 [926,] 12400
 [927,] 12800
 [928,] 12820
 [929,] 12980
 [930,] 12980
 [931,] 12880
 [932,] 12800
 [933,] 12660
 [934,] 12720
 [935,] 12700
 [936,] 12520
 [937,] 12700
 [938,] 12820
 [939,] 12620
 [940,] 12760
 [941,] 12860
 [942,] 12660
 [943,] 12520
 [944,] 12520
 [945,] 12260
 [946,] 12100
 [947,] 12280
 [948,] 12100
 [949,] 12520
 [950,] 12780
 [951,] 12960
 [952,] 12920
 [953,] 13000
 [954,] 13000
 [955,] 12920
 [956,] 12860
 [957,] 12700
 [958,] 12560
 [959,] 12500
 [960,] 12660
 [961,] 12600
 [962,] 12600
 [963,] 12860
 [964,] 12840
 [965,] 12960
 [966,] 12840
 [967,] 13100
 [968,] 12700
 [969,] 12760
 [970,] 12560
 [971,] 13000
 [972,] 13240
 [973,] 13140
 [974,] 13000
 [975,] 13000
 [976,] 12500
 [977,] 12600
 [978,] 13300
 [979,] 13520
 [980,] 13600
 [981,] 13540
 [982,] 13800
 [983,] 13460
 [984,] 13600
 [985,] 13600
 [986,] 13420
 [987,] 13800
 [988,] 13940
 [989,] 14000
 [990,] 14000
 [991,] 14200
 [992,] 14200
 [993,] 14000
 [994,] 13800
 [995,] 13900
 [996,] 13580
 [997,] 13400
 [998,] 13500
 [999,] 13540
[1000,] 13500
 [ reached getOption("max.print") -- omitted 216 rows ]

hist(RETOR)

SERIE DE TIEMPO

data(package="xts")
str(CIERRE2)

'data.frame':   1216 obs. of  6 variables:
 $ Datev: Date, format: "2019-05-07" "2019-05-06" ...
 $ BICV : num  40020 39400 39420 39380 40100 ...
 $ SISV : num  35200 35480 35800 35640 35900 ...
 $ CCBV : num  7930 7910 7990 8000 8040 8070 8080 8090 8090 8080 ...
 $ IMIV : num  13880 13900 14400 14460 14460 ...
 $ CHLV : num  4520 4630 4695 4840 4790 ...

is.matrix(CIERRE2)

[1] FALSE

colnames(CIERRE2)

[1] "Datev" "BICV"  "SISV"  "CCBV"  "IMIV"  "CHLV" 

head(rownames(CIERRE2))

[1] "2019-05-08" "2019-05-07" "2019-05-06" "2019-05-03" "2019-05-02" "2019-04-30"

print(head(CIERRE2,calendar=TRUE))

str(CIERRE2)

'data.frame':   1216 obs. of  6 variables:
 $ Datev: Date, format: "2019-05-07" "2019-05-06" ...
 $ BICV : num  40020 39400 39420 39380 40100 ...
 $ SISV : num  35200 35480 35800 35640 35900 ...
 $ CCBV : num  7930 7910 7990 8000 8040 8070 8080 8090 8090 8080 ...
 $ IMIV : num  13880 13900 14400 14460 14460 ...
 $ CHLV : num  4520 4630 4695 4840 4790 ...

plot.ts(CIERRE2)

Cemex (CLH):Se puede observar que presenta tendencia a la baja, lo que significa, que los precios de su accion son cada vez mas bajos. Grupo SURA (SIS): En este caso, la grafica presenta irregularidad en el tiempo, en algunos dias tiene picos muy altos, pero asi mismo tambien va cayendo. Bancolombia (BIC):La serie es ciclica, puesto que tiene momentos de crecimiento y auge. Almacenes Exito (IMI):Los precios de la accion han ido aumentando con el paso del tiempo, es decir; tiene una tendencia a la alza. Cemargos (CCB): En este grafico se puede observar tendencia a la alza.

El paquete timeSeries #chl#

smts <- as.timeSeries(CIERRES$Date)
head(smts)

      BICV  SISV CCBV  IMIV
[1,] 40020 35200 7930 13880
[2,] 39400 35480 7910 13900
[3,] 39420 35800 7990 14400
[4,] 39380 35640 8000 14460
[5,] 40100 35900 8040 14460
[6,] 40900 36000 8070 14500

plot(smts, at="chic")

plot(smts, at="pretty", minor.ticks="day")
title(main = "Titulo", xlab = "Fecha")

plot(smts, at="pretty", minor.ticks="week",cex.axis=0.75,yax.flip=TRUE)

plot(smts, at="pretty", minor.ticks="week",cex.axis=0.75,yax.flip=TRUE,type=c("l","p","h","l"))

Usando el paquete dygraphs

dygraph(CIERRE2) %>%
dyRangeSelector() 

El paquete highcharter

suppressPackageStartupMessages(library(highcharter))
highchart(type = "stock") %>%
  hc_add_series(CIERRES$Date, type = "line",color="green")

highchart(type = "stock") %>%
  hc_add_series(CIERRES$Date, type = "column",color="green")

highchart(type = "stock") %>%
  hc_add_series(CIERRES$Date, type = "scatter",color="green") %>%
  hc_title(text= "Retornos ")

hchart(as.vector(CIERRES$Date[,1]), color="purple")

hchart(density(as.vector(CIERRES$Date[,1])),type="area", name="cierres")

El paquete quantmod

suppressPackageStartupMessages(library(quantmod))
CCB1<- subset(CCB, select = c(Date, Close, Open, High, Low))
  
  CCB2 <- as.matrix( CCB1 [2:5])
  
  head(CCB2)

     Close Open High  Low
[1,]  7930 7950 7950 7920
[2,]  7910 7990 7990 7910
[3,]  7990 8000 8020 7900
[4,]  8000 8090 8090 8000
[5,]  8040 8090 8090 8040
[6,]  8070 8080 8090 8060

  
  rownames(CCB2) <- as.character( CCB1$Date)
  CCB2 <- as.xts (CCB2)
  
  is.OHLC(CCB2)

[1] TRUE

  
  has.Cl(CCB2)

[1] TRUE

  
  has.Vo(CCB2)

[1] FALSE

  
  head(Cl(CCB2))

           Close
2014-05-09 11140
2014-05-12 11380
2014-05-13 11280
2014-05-14 11180
2014-05-15 11100
2014-05-16 11160

  
  chartSeries(CCB2, theme = "white")

Durante el 2014 se obtuvo un pico alto en el mes de mayo. Sin embargo, hubo un descenso en los cierres para inicios de 2015 con un comportamiento irregular. Para el periodo 2016-2017 se tuvo un desempeño estable sin alteracion alguna. Finalmente, se presenta un decrecimiento en los cierres, es decir; caida en sus precios.