timeseries nhóm
Nguyen Thi Kim Anh
2024-04-09
library(lmtest)## Loading required package: zoo## Warning: package 'zoo' was built under R version 4.3.2##
## Attaching package: 'zoo'## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numericlibrary(ggplot2)## Warning: package 'ggplot2' was built under R version 4.3.2library(tseries)## Registered S3 method overwritten by 'quantmod':
## method from
## as.zoo.data.frame zoolibrary(car)## Warning: package 'car' was built under R version 4.3.2## Loading required package: carDatalibrary(forecast)
library(TTR)
library(Metrics)## Warning: package 'Metrics' was built under R version 4.3.2##
## Attaching package: 'Metrics'## The following object is masked from 'package:forecast':
##
## accuracylibrary(tsutils)## Warning: package 'tsutils' was built under R version 4.3.2library(urca)## Warning: package 'urca' was built under R version 4.3.3library(forecast)
library(vars)## Warning: package 'vars' was built under R version 4.3.3## Loading required package: MASS## Loading required package: strucchange## Warning: package 'strucchange' was built under R version 4.3.3## Loading required package: sandwich#input
library(readxl)## Warning: package 'readxl' was built under R version 4.3.2ts_price<-read_excel("~/Kim(1)/Kim NEU/HK6 NEU/Phân tích chuỗi tg và dự báo/group.xlsx")
attach(ts_price)
save(ts_price, file = "group")
ts(ts_price,start=c(1,1),frequency=1)## Time Series:
## Start = 1
## End = 498
## Frequency = 1
## BTP CHP DRL
## 1 13.006187 18.46135 54.04355
## 2 12.864815 18.46135 54.45927
## 3 12.723444 18.22003 54.45927
## 4 12.723444 18.17981 54.04355
## 5 13.218244 18.22003 54.29298
## 6 13.076873 17.85804 54.29298
## 7 12.511386 17.93848 55.29070
## 8 12.476043 17.89826 55.29070
## 9 12.476043 17.77760 54.87499
## 10 12.970844 17.53627 54.87499
## 11 12.228643 17.61671 54.04355
## 12 12.157957 17.69716 54.04355
## 13 12.157957 17.93848 54.04355
## 14 12.970844 18.01892 54.04355
## 15 12.334672 17.53627 54.04355
## 16 12.652758 17.77760 54.04355
## 17 12.476043 17.69716 54.04355
## 18 12.476043 17.69716 54.12669
## 19 13.041530 17.69716 56.95358
## 20 13.218244 17.69716 54.87499
## 21 13.041530 17.69716 54.45927
## 22 13.041530 17.53627 54.04355
## 23 13.041530 17.97870 54.20983
## 24 13.041530 17.93848 54.20983
## 25 13.006187 17.85804 54.87499
## 26 13.076873 17.85804 53.62783
## 27 13.359616 17.73738 56.53786
## 28 13.430301 18.09936 56.53786
## 29 13.430301 18.09936 56.53786
## 30 13.500987 17.89826 54.04355
## 31 13.430301 17.77760 54.04355
## 32 13.359616 17.81782 54.04355
## 33 13.076873 17.81782 54.87499
## 34 12.723444 17.81782 54.87499
## 35 12.758786 17.81782 54.87499
## 36 12.864815 17.85804 54.29298
## 37 12.935501 17.97870 54.45927
## 38 12.935501 17.81782 54.79184
## 39 12.794129 17.85804 54.70870
## 40 12.935501 17.93848 55.70642
## 41 13.006187 17.77760 55.70642
## 42 12.723444 17.81782 56.53786
## 43 12.652758 17.85804 54.04355
## 44 12.476043 17.85804 57.70188
## 45 12.794129 17.93848 55.70642
## 46 12.476043 17.93848 56.45472
## 47 12.511386 18.05914 56.45472
## 48 12.723444 18.01892 56.37158
## 49 12.511386 18.09936 56.37158
## 50 12.546729 18.09936 56.37158
## 51 12.970844 18.13958 57.36930
## 52 12.794129 18.22003 57.36930
## 53 13.006187 18.22003 57.36930
## 54 12.935501 18.26025 56.53786
## 55 12.794129 18.46135 56.45472
## 56 12.900158 18.30047 56.45472
## 57 12.794129 18.26025 56.37158
## 58 12.794129 18.50157 55.04127
## 59 12.794129 18.86356 55.04127
## 60 13.147558 19.22555 55.70642
## 61 13.041530 19.26577 56.53786
## 62 13.006187 19.18533 56.53786
## 63 13.041530 19.14510 56.53786
## 64 13.006187 19.10488 56.53786
## 65 13.041530 18.90378 55.78957
## 66 12.970844 18.62223 54.04355
## 67 12.970844 18.50157 56.53786
## 68 12.864815 18.90378 54.04355
## 69 13.253587 18.34069 57.28616
## 70 13.359616 18.17981 57.36930
## 71 12.864815 18.30047 57.36930
## 72 12.723444 18.30047 57.36930
## 73 13.076873 18.30047 56.53786
## 74 12.652758 18.17981 55.29070
## 75 12.652758 18.17981 56.53786
## 76 13.041530 18.17981 57.36930
## 77 12.794129 18.58201 57.28616
## 78 13.006187 18.66246 56.53786
## 79 12.652758 19.14510 55.70642
## 80 12.864815 19.10488 58.20074
## 81 13.041530 20.11040 58.17754
## 82 12.370015 20.11040 58.17754
## 83 12.370015 20.51261 58.43534
## 84 12.370015 20.91482 57.40413
## 85 12.087271 20.83438 57.57600
## 86 11.309728 20.32206 54.99797
## 87 11.345070 20.49283 54.99797
## 88 11.945900 20.49283 54.99797
## 89 11.945900 20.83438 57.49006
## 90 11.945900 20.74899 55.85731
## 91 11.804528 20.74899 55.94325
## 92 11.945900 20.49283 55.85731
## 93 11.592471 20.23667 56.71666
## 94 11.875214 20.36475 57.57600
## 95 12.688101 20.40744 57.57600
## 96 12.370015 20.27936 58.43534
## 97 12.299329 20.49283 58.43534
## 98 12.228643 21.51747 57.57600
## 99 12.228643 21.17593 57.57600
## 100 12.228643 21.17593 57.57600
## 101 12.511386 20.40744 57.57600
## 102 12.299329 20.66361 55.25577
## 103 12.652758 21.51747 55.25577
## 104 12.688101 21.60286 55.85731
## 105 12.511386 21.51747 55.85731
## 106 12.652758 20.87707 55.77138
## 107 12.688101 20.74899 55.42764
## 108 12.193300 20.74899 55.85731
## 109 12.582072 20.66361 55.68544
## 110 12.511386 21.26131 55.68544
## 111 12.334672 21.26131 55.85731
## 112 11.945900 21.34670 55.85731
## 113 11.945900 21.09054 55.85731
## 114 11.769185 20.15128 58.34941
## 115 11.804528 20.15128 56.71666
## 116 11.981243 20.49283 56.71666
## 117 11.981243 20.70630 56.71666
## 118 11.839871 20.49283 54.99797
## 119 11.804528 20.66361 51.30279
## 120 11.804528 20.06590 53.27928
## 121 11.910557 20.10859 51.56060
## 122 11.733842 20.10859 51.56060
## 123 11.733842 20.10859 54.48236
## 124 11.733842 20.10859 54.48236
## 125 11.875214 19.59627 54.39643
## 126 11.945900 19.25472 54.39643
## 127 11.981243 18.78510 55.85731
## 128 11.981243 19.38280 55.85731
## 129 11.663157 19.38280 55.85731
## 130 11.663157 19.55358 54.13863
## 131 11.698499 19.72435 54.56830
## 132 11.910557 19.76704 54.56830
## 133 11.981243 19.72435 54.56830
## 134 12.016586 19.89512 57.74787
## 135 11.981243 20.10859 57.74787
## 136 11.981243 20.06590 55.85731
## 137 11.663157 20.06590 57.57600
## 138 11.839871 20.15128 58.34941
## 139 11.839871 20.10859 56.20105
## 140 11.839871 20.23667 58.43534
## 141 11.733842 20.06590 58.43534
## 142 11.733842 20.15128 58.43534
## 143 11.804528 20.15128 55.85731
## 144 11.804528 20.15128 55.85731
## 145 12.016586 20.23667 55.85731
## 146 12.051928 20.32206 55.42764
## 147 11.804528 20.40744 58.26347
## 148 11.981243 20.62091 55.51358
## 149 11.945900 21.34670 55.08390
## 150 12.016586 21.17593 55.08390
## 151 11.945900 21.09054 57.57600
## 152 11.945900 21.26131 57.49006
## 153 11.945900 21.34670 58.00567
## 154 11.945900 21.09054 58.00567
## 155 12.016586 21.09054 57.57600
## 156 12.016586 20.91977 57.57600
## 157 12.016586 20.66361 58.09161
## 158 12.016586 20.91977 60.11295
## 159 12.016586 20.87707 57.30065
## 160 12.794129 20.74899 57.74007
## 161 12.758786 20.62091 57.56430
## 162 12.652758 20.62091 57.74007
## 163 12.405357 20.74899 59.93718
## 164 12.723444 20.66361 60.46448
## 165 12.794129 20.83438 60.64025
## 166 12.794129 20.83438 60.20083
## 167 12.440700 20.74899 59.32199
## 168 12.476043 20.74899 59.76141
## 169 12.511386 21.85902 60.64025
## 170 12.511386 22.58481 60.64025
## 171 12.511386 22.37134 58.17949
## 172 12.440700 22.20057 59.76141
## 173 12.440700 22.20057 63.89198
## 174 12.511386 22.88366 63.89198
## 175 12.617415 22.88366 61.95852
## 176 12.405357 22.88366 62.39794
## 177 12.582072 22.84097 62.39794
## 178 12.582072 22.71289 61.51910
## 179 12.652758 22.54211 61.51910
## 180 12.582072 22.49942 59.84929
## 181 12.582072 22.45673 59.84929
## 182 12.370015 21.68825 59.93718
## 183 12.370015 21.38939 61.07968
## 184 12.370015 21.38939 60.11295
## 185 12.299329 20.83438 61.51910
## 186 12.087271 20.87707 61.51910
## 187 12.087271 21.94441 61.51910
## 188 11.274385 21.47478 60.20083
## 189 12.054619 21.34670 60.20083
## 190 12.483748 21.38939 60.20083
## 191 12.093631 21.38939 60.20083
## 192 12.093631 21.38939 60.20083
## 193 11.937584 21.64555 60.20083
## 194 11.937584 21.43209 60.20083
## 195 11.898572 21.77363 60.72814
## 196 11.820549 21.77363 60.81602
## 197 11.391420 21.56017 60.55237
## 198 11.898572 21.43209 60.55237
## 199 11.898572 21.26131 60.55237
## 200 11.391420 20.74899 59.32199
## 201 11.235373 20.91977 58.88256
## 202 11.040314 21.13323 59.49776
## 203 11.235373 21.30401 59.14622
## 204 11.703514 21.34670 59.14622
## 205 11.157350 21.21862 59.14622
## 206 11.469443 21.68825 58.00372
## 207 11.313396 21.34670 58.88256
## 208 11.625490 21.30401 58.79468
## 209 11.235373 21.13323 58.79468
## 210 11.079326 20.87707 57.82795
## 211 11.664502 20.91977 57.82795
## 212 11.157350 20.79169 55.45507
## 213 11.157350 20.06590 57.91584
## 214 11.079326 20.06590 56.68545
## 215 10.923279 19.98051 58.00372
## 216 10.299092 19.29742 58.00372
## 217 10.689209 18.99856 58.88256
## 218 10.455139 18.78510 58.61891
## 219 11.157350 19.08395 59.58564
## 220 11.196361 19.12664 59.76141
## 221 10.689209 19.12664 59.49776
## 222 10.299092 19.08395 58.70680
## 223 9.674904 19.12664 60.02506
## 224 9.869963 19.46819 59.76141
## 225 10.299092 20.06590 60.64025
## 226 10.377115 19.80974 61.51910
## 227 10.299092 19.80974 61.51910
## 228 10.455139 19.98051 61.95852
## 229 10.377115 19.89512 62.31006
## 230 10.533162 20.23667 61.87064
## 231 10.533162 20.10859 61.95852
## 232 10.455139 20.60343 61.69487
## 233 10.494150 20.33352 61.60698
## 234 10.455139 20.46848 61.60698
## 235 10.260080 20.15358 61.34333
## 236 10.650197 20.33352 61.51910
## 237 10.767232 20.24355 62.34547
## 238 10.494150 20.28853 62.25365
## 239 10.494150 20.24355 61.06000
## 240 10.299092 20.10859 61.06000
## 241 10.299092 20.19856 59.77453
## 242 10.299092 20.10859 60.50908
## 243 10.650197 19.83868 59.68271
## 244 10.533162 20.15358 60.04998
## 245 10.533162 19.88366 59.86635
## 246 10.299092 20.06361 59.86635
## 247 10.767232 19.83868 59.86635
## 248 10.767232 20.15358 60.14180
## 249 10.923279 20.33352 60.04998
## 250 11.157350 20.51346 60.04998
## 251 10.923279 20.28853 59.68271
## 252 11.157350 20.24355 59.86635
## 253 11.157350 20.46848 60.32544
## 254 11.118338 20.51346 58.94815
## 255 11.118338 20.69340 59.22361
## 256 11.118338 20.73839 59.22361
## 257 11.118338 20.78338 59.22361
## 258 11.118338 20.60343 59.49907
## 259 10.923279 20.78338 59.86635
## 260 11.118338 20.87335 59.86635
## 261 11.001303 21.00830 59.49907
## 262 10.845256 21.23323 59.77453
## 263 10.767232 21.23323 61.06000
## 264 10.845256 21.41318 61.06000
## 265 10.923279 21.77306 60.60090
## 266 10.611186 21.81805 63.17185
## 267 10.728221 21.90802 59.86635
## 268 10.728221 21.59312 59.86635
## 269 10.728221 21.81805 60.60090
## 270 10.260080 21.41318 62.89639
## 271 10.728221 21.41318 61.97820
## 272 10.611186 21.41318 61.70274
## 273 10.611186 21.41318 60.69272
## 274 10.299092 21.27822 60.69272
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## 280 10.455139 21.86303 61.97820
## 281 10.299092 21.81805 61.97820
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## 283 10.143045 21.77306 63.35549
## 284 9.986998 21.72807 62.43729
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## 287 10.143045 21.72807 61.24364
## 288 10.299092 21.95300 59.86635
## 289 10.026010 21.90802 61.97820
## 290 10.065022 21.90802 59.95817
## 291 10.143045 22.04297 59.95817
## 292 10.143045 22.17793 59.86635
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## 294 10.065022 22.04297 60.60090
## 295 10.143045 22.22292 60.60090
## 296 10.143045 22.31289 61.70274
## 297 10.104033 22.49283 58.85633
## 298 10.143045 22.49283 61.42728
## 299 10.065022 22.49283 61.42728
## 300 10.065022 22.44785 61.42728
## 301 10.143045 22.44785 61.42728
## 302 9.986998 22.40286 61.42728
## 303 10.065022 22.31289 58.94815
## 304 10.065022 22.31289 60.60090
## 305 10.065022 22.22292 60.50908
## 306 10.026010 22.08796 59.68271
## 307 10.065022 22.35787 59.68271
## 308 10.026010 22.22292 60.23362
## 309 10.221068 22.22292 60.32544
## 310 10.221068 21.99799 60.87636
## 311 10.221068 22.13295 59.03997
## 312 10.221068 22.40286 60.60090
## 313 10.299092 22.13295 61.06000
## 314 10.143045 22.26790 60.60090
## 315 10.065022 21.95300 60.14180
## 316 10.143045 22.13295 60.14180
## 317 10.143045 22.49283 60.14180
## 318 10.065022 22.67277 60.14180
## 319 9.986998 22.44785 60.14180
## 320 10.065022 22.44785 59.68271
## 321 10.104033 22.44785 59.68271
## 322 10.026010 22.40286 60.14180
## 323 10.026010 22.49283 59.86635
## 324 10.026010 22.31289 59.22361
## 325 9.986998 22.31289 59.13179
## 326 10.026010 22.31289 59.68271
## 327 10.104033 22.04297 59.68271
## 328 10.143045 21.95300 60.60090
## 329 10.416127 22.13295 60.60090
## 330 10.221068 22.22292 60.60090
## 331 10.221068 21.95300 59.22361
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## 333 10.689209 22.04297 58.76451
## 334 10.767232 22.13295 59.49907
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## 336 11.235373 22.04297 60.41726
## 337 11.235373 22.13295 60.04998
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## 354 12.756830 22.66588 60.23592
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## 357 12.834853 22.52059 59.29474
## 358 12.639795 22.47216 59.29474
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## 457 11.291550 23.24706 63.07407
## 458 11.123019 22.85961 62.49185
## 459 11.123019 23.39235 63.07407
## 460 11.123019 23.05333 63.07407
## 461 11.123019 23.24706 62.88000
## 462 11.123019 23.24706 62.88000
## 463 11.038754 23.24706 63.26815
## 464 11.038754 23.24706 63.55926
## 465 10.996621 23.44078 66.37333
## 466 11.123019 23.44078 63.07407
## 467 11.123019 23.53765 64.04444
## 468 11.249417 23.44078 64.52963
## 469 11.038754 23.44078 63.07407
## 470 11.038754 23.44078 63.55926
## 471 10.954489 23.53765 63.85037
## 472 11.123019 23.53765 64.52963
## 473 11.123019 23.44078 64.52963
## 474 11.291550 23.34392 64.04444
## 475 11.291550 23.24706 64.04444
## 476 11.291550 23.39235 64.04444
## 477 12.049938 23.44078 64.14148
## 478 12.892590 23.73137 64.33556
## 479 13.777376 23.87667 64.33556
## 480 14.704294 23.97353 64.33556
## 481 15.083488 23.92510 64.33556
## 482 14.030172 23.87667 65.01481
## 483 13.061121 23.73137 65.01481
## 484 13.650978 23.82824 67.63481
## 485 13.356050 23.77980 64.52963
## 486 13.356050 23.77980 64.52963
## 487 13.356050 24.21569 64.82074
## 488 13.440315 24.40941 64.82074
## 489 13.861641 24.50627 65.50000
## 490 14.104676 24.70000 65.70000
## 491 14.017878 24.36098 66.00000
## 492 13.887681 24.79686 66.00000
## 493 13.714085 24.99059 65.70000
## 494 13.714085 24.70000 65.70000
## 495 13.627287 24.90000 65.40000
## 496 13.627287 24.85000 65.00000
## 497 13.800883 25.00000 65.00000
## 498 13.800883 25.30000 65.80000CHP<-ts(CHP,start=c(1,1),frequency=1)
BTP<-ts(BTP,start=c(1,1),frequency=1)
DRL<-ts(DRL,start=c(1,1),frequency=1)###DONG TICH HOP###
#Kiem dinh so moi quan he Voi tieu chi "trace"
summary(ca.jo(data.frame(CHP,BTP,DRL),type="trace")) # có 1 mqh đồng tích hợp##
## ######################
## # Johansen-Procedure #
## ######################
##
## Test type: trace statistic , with linear trend
##
## Eigenvalues (lambda):
## [1] 0.063346614 0.011882433 0.001043128
##
## Values of teststatistic and critical values of test:
##
## test 10pct 5pct 1pct
## r <= 2 | 0.52 6.50 8.18 11.65
## r <= 1 | 6.45 15.66 17.95 23.52
## r = 0 | 38.91 28.71 31.52 37.22
##
## Eigenvectors, normalised to first column:
## (These are the cointegration relations)
##
## CHP.l2 BTP.l2 DRL.l2
## CHP.l2 1.0000000 1.0000000 1.00000000
## BTP.l2 -0.1810824 -10.7448583 0.85235183
## DRL.l2 -0.6566706 0.5192956 0.08164016
##
## Weights W:
## (This is the loading matrix)
##
## CHP.l2 BTP.l2 DRL.l2
## CHP.d -0.038833987 -9.681981e-05 -0.002688246
## BTP.d 0.005985269 2.098272e-03 -0.001487528
## DRL.d 0.153768121 -2.525485e-03 -0.010250825#Kiem dinh so moi quan he Voi tieu chi "eigen"
summary(ca.jo(data.frame(CHP,BTP,DRL),type="eigen")) # có 1##
## ######################
## # Johansen-Procedure #
## ######################
##
## Test type: maximal eigenvalue statistic (lambda max) , with linear trend
##
## Eigenvalues (lambda):
## [1] 0.063346614 0.011882433 0.001043128
##
## Values of teststatistic and critical values of test:
##
## test 10pct 5pct 1pct
## r <= 2 | 0.52 6.50 8.18 11.65
## r <= 1 | 5.93 12.91 14.90 19.19
## r = 0 | 32.46 18.90 21.07 25.75
##
## Eigenvectors, normalised to first column:
## (These are the cointegration relations)
##
## CHP.l2 BTP.l2 DRL.l2
## CHP.l2 1.0000000 1.0000000 1.00000000
## BTP.l2 -0.1810824 -10.7448583 0.85235183
## DRL.l2 -0.6566706 0.5192956 0.08164016
##
## Weights W:
## (This is the loading matrix)
##
## CHP.l2 BTP.l2 DRL.l2
## CHP.d -0.038833987 -9.681981e-05 -0.002688246
## BTP.d 0.005985269 2.098272e-03 -0.001487528
## DRL.d 0.153768121 -2.525485e-03 -0.010250825#Kiem dinh tinh dung voi 3 chuoi sai phan
summary(ur.df(diff(CHP), type = "none")) # Bác bỏ H0: dừng##
## ###############################################
## # Augmented Dickey-Fuller Test Unit Root Test #
## ###############################################
##
## Test regression none
##
##
## Call:
## lm(formula = z.diff ~ z.lag.1 - 1 + z.diff.lag)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.95781 -0.09333 0.00000 0.11010 1.10945
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## z.lag.1 -1.081531 0.066119 -16.357 <2e-16 ***
## z.diff.lag 0.006814 0.045085 0.151 0.88
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2405 on 493 degrees of freedom
## Multiple R-squared: 0.5368, Adjusted R-squared: 0.535
## F-statistic: 285.7 on 2 and 493 DF, p-value: < 2.2e-16
##
##
## Value of test-statistic is: -16.3573
##
## Critical values for test statistics:
## 1pct 5pct 10pct
## tau1 -2.58 -1.95 -1.62summary(ur.df(diff(BTP), type = "none")) # dừng##
## ###############################################
## # Augmented Dickey-Fuller Test Unit Root Test #
## ###############################################
##
## Test regression none
##
##
## Call:
## lm(formula = z.diff ~ z.lag.1 - 1 + z.diff.lag)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.02740 -0.10489 -0.00324 0.08405 1.09084
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## z.lag.1 -1.18998 0.06591 -18.053 <2e-16 ***
## z.diff.lag 0.09896 0.04481 2.209 0.0277 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.245 on 493 degrees of freedom
## Multiple R-squared: 0.5461, Adjusted R-squared: 0.5443
## F-statistic: 296.6 on 2 and 493 DF, p-value: < 2.2e-16
##
##
## Value of test-statistic is: -18.0533
##
## Critical values for test statistics:
## 1pct 5pct 10pct
## tau1 -2.58 -1.95 -1.62summary(ur.df(diff(DRL), type = "none")) # dừng##
## ###############################################
## # Augmented Dickey-Fuller Test Unit Root Test #
## ###############################################
##
## Test regression none
##
##
## Call:
## lm(formula = z.diff ~ z.lag.1 - 1 + z.diff.lag)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.3539 -0.3622 0.0019 0.4364 4.3855
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## z.lag.1 -1.52601 0.07289 -20.936 < 2e-16 ***
## z.diff.lag 0.14276 0.04460 3.201 0.00146 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9609 on 493 degrees of freedom
## Multiple R-squared: 0.6742, Adjusted R-squared: 0.6728
## F-statistic: 510 on 2 and 493 DF, p-value: < 2.2e-16
##
##
## Value of test-statistic is: -20.9356
##
## Critical values for test statistics:
## 1pct 5pct 10pct
## tau1 -2.58 -1.95 -1.62#Uoc luong phuong trinh va kiem dinh phan du
summary(lm(CHP~BTP+DRL))##
## Call:
## lm(formula = CHP ~ BTP + DRL)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.5250 -0.6096 0.1152 0.6619 3.3183
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.446857 1.117502 -5.769 1.41e-08 ***
## BTP 0.007549 0.045668 0.165 0.869
## DRL 0.462023 0.014812 31.193 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.012 on 495 degrees of freedom
## Multiple R-squared: 0.6699, Adjusted R-squared: 0.6686
## F-statistic: 502.3 on 2 and 495 DF, p-value: < 2.2e-16resid.CHP<- resid(lm(CHP~BTP+DRL))
summary(ur.df(resid.CHP, type="none")) # |-4.6304|>|Tqs|->phần dư dừng-> đồng tích hợp##
## ###############################################
## # Augmented Dickey-Fuller Test Unit Root Test #
## ###############################################
##
## Test regression none
##
##
## Call:
## lm(formula = z.diff ~ z.lag.1 - 1 + z.diff.lag)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.05953 -0.21952 0.01328 0.24129 2.17728
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## z.lag.1 -0.10853 0.02363 -4.593 5.55e-06 ***
## z.diff.lag -0.24532 0.04369 -5.615 3.28e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.5109 on 494 degrees of freedom
## Multiple R-squared: 0.1274, Adjusted R-squared: 0.1239
## F-statistic: 36.07 on 2 and 494 DF, p-value: 2.4e-15
##
##
## Value of test-statistic is: -4.5931
##
## Critical values for test statistics:
## 1pct 5pct 10pct
## tau1 -2.58 -1.95 -1.62summary(lm(BTP~CHP+DRL))##
## Call:
## lm(formula = BTP ~ CHP + DRL)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.1239 -0.7013 0.1165 0.6951 3.5194
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 15.415339 0.900477 17.119 <2e-16 ***
## CHP 0.007312 0.044234 0.165 0.8688
## DRL -0.062581 0.024946 -2.509 0.0124 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9959 on 495 degrees of freedom
## Multiple R-squared: 0.03338, Adjusted R-squared: 0.02947
## F-statistic: 8.546 on 2 and 495 DF, p-value: 0.0002245resid.BTP<- resid(lm(BTP~CHP+DRL))
summary(ur.df(resid.BTP, type="none")) # đồng tích hợp tại alpha= 0.05##
## ###############################################
## # Augmented Dickey-Fuller Test Unit Root Test #
## ###############################################
##
## Test regression none
##
##
## Call:
## lm(formula = z.diff ~ z.lag.1 - 1 + z.diff.lag)
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.98800 -0.12852 -0.00487 0.11160 1.05681
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## z.lag.1 -0.02566 0.01173 -2.188 0.0291 *
## z.diff.lag -0.08351 0.04505 -1.854 0.0644 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2554 on 494 degrees of freedom
## Multiple R-squared: 0.01913, Adjusted R-squared: 0.01516
## F-statistic: 4.816 on 2 and 494 DF, p-value: 0.008479
##
##
## Value of test-statistic is: -2.1879
##
## Critical values for test statistics:
## 1pct 5pct 10pct
## tau1 -2.58 -1.95 -1.62summary(lm(DRL~CHP+BTP))##
## Call:
## lm(formula = DRL ~ CHP + BTP)
##
## Residuals:
## Min 1Q Median 3Q Max
## -7.5751 -1.0553 0.1944 1.2592 4.8475
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 31.60253 1.45624 21.701 <2e-16 ***
## CHP 1.43457 0.04599 31.193 <2e-16 ***
## BTP -0.20061 0.07997 -2.509 0.0124 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.783 on 495 degrees of freedom
## Multiple R-squared: 0.674, Adjusted R-squared: 0.6727
## F-statistic: 511.8 on 2 and 495 DF, p-value: < 2.2e-16resid.DRL<- resid(lm(DRL~CHP+BTP))
summary(ur.df(resid.DRL, type="none")) # dừng-> đồng tích hợp##
## ###############################################
## # Augmented Dickey-Fuller Test Unit Root Test #
## ###############################################
##
## Test regression none
##
##
## Call:
## lm(formula = z.diff ~ z.lag.1 - 1 + z.diff.lag)
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.8330 -0.4333 0.0250 0.4458 4.4081
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## z.lag.1 -0.14534 0.02706 -5.371 1.21e-07 ***
## z.diff.lag -0.24878 0.04356 -5.712 1.93e-08 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.02 on 494 degrees of freedom
## Multiple R-squared: 0.1527, Adjusted R-squared: 0.1492
## F-statistic: 44.5 on 2 and 494 DF, p-value: < 2.2e-16
##
##
## Value of test-statistic is: -5.3709
##
## Critical values for test statistics:
## 1pct 5pct 10pct
## tau1 -2.58 -1.95 -1.62#Mo hinh hieu chinh sai so ECM
length(CHP)## [1] 498summary(lm(diff(CHP)~ diff(BTP)+ diff(DRL)+ resid.CHP[1:497])) ##
## Call:
## lm(formula = diff(CHP) ~ diff(BTP) + diff(DRL) + resid.CHP[1:497])
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.86778 -0.10776 -0.00784 0.11702 1.07639
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.013612 0.010501 1.296 0.195494
## diff(BTP) 0.143611 0.042686 3.364 0.000827 ***
## diff(DRL) -0.008036 0.010482 -0.767 0.443673
## resid.CHP[1:497] -0.043210 0.010656 -4.055 5.83e-05 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.234 on 493 degrees of freedom
## Multiple R-squared: 0.05734, Adjusted R-squared: 0.0516
## F-statistic: 9.996 on 3 and 493 DF, p-value: 2.093e-06# hệ số gama= -0.043321, có ý nghĩa thống kê ở mức 1% -> nếu có mẫu cân bằng ở kỳ trước tăng 1 đơn vị-> kỳ sau cần giảm 0.043321 đơn vị để về cân bằng.
# xem lại youtube
summary(lm(diff(BTP)~ diff(CHP)+ diff(DRL)+ resid.BTP[1:497]))##
## Call:
## lm(formula = diff(BTP) ~ diff(CHP) + diff(DRL) + resid.BTP[1:497])
##
## Residuals:
## Min 1Q Median 3Q Max
## -0.95581 -0.12105 -0.00936 0.08585 0.97456
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.0009487 0.0109080 -0.087 0.930726
## diff(CHP) 0.1535389 0.0454546 3.378 0.000788 ***
## diff(DRL) 0.0129063 0.0106351 1.214 0.225498
## resid.BTP[1:497] -0.0278132 0.0110198 -2.524 0.011918 *
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.2427 on 493 degrees of freedom
## Multiple R-squared: 0.03622, Adjusted R-squared: 0.03035
## F-statistic: 6.175 on 3 and 493 DF, p-value: 0.0003991summary(lm(diff(DRL)~ diff(CHP)+ diff(BTP)+ resid.DRL[1:497]))##
## Call:
## lm(formula = diff(DRL) ~ diff(CHP) + diff(BTP) + resid.DRL[1:497])
##
## Residuals:
## Min 1Q Median 3Q Max
## -4.2500 -0.3564 0.0088 0.4224 3.9243
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.02436 0.04453 0.547 0.585
## diff(CHP) -0.08940 0.19098 -0.468 0.640
## diff(BTP) 0.20047 0.18258 1.098 0.273
## resid.DRL[1:497] -0.15237 0.02550 -5.975 4.42e-09 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.9911 on 493 degrees of freedom
## Multiple R-squared: 0.07461, Adjusted R-squared: 0.06898
## F-statistic: 13.25 on 3 and 493 DF, p-value: 2.481e-08#————————————————————————
###VAR###
CHP.ln <- log(CHP[2:length(CHP)] / CHP[1:(length(CHP)-1)])*100
BTP.ln <- log(BTP[2:length(BTP)] / BTP[1:(length(BTP)-1)])*100
DRL.ln <- log(DRL[2:length(DRL)] / DRL[1:(length(DRL)-1)])*100
data1<-data.frame(CHP.ln,BTP.ln,DRL.ln)
View(data1)
#Xac dinh bac tre
VARselect(data1)## $selection
## AIC(n) HQ(n) SC(n) FPE(n)
## 1 1 1 1
##
## $criteria
## 1 2 3 4 5 6 7
## AIC(n) 2.704264 2.704795 2.705903 2.724025 2.720101 2.747527 2.767799
## HQ(n) 2.744806 2.775743 2.807257 2.855785 2.882267 2.940099 2.990777
## SC(n) 2.807466 2.885398 2.963907 3.059430 3.132907 3.237734 3.335408
## FPE(n) 14.943335 14.951347 14.968087 15.242131 15.182935 15.605843 15.926487
## 8 9 10
## AIC(n) 2.760445 2.761248 2.763096
## HQ(n) 3.013829 3.045039 3.077293
## SC(n) 3.405455 3.483659 3.562909
## FPE(n) 15.811154 15.825602 15.857038#MO HINH VAR(1)
var1<- VAR(data1, p=1,type="const")
summary(var1)##
## VAR Estimation Results:
## =========================
## Endogenous variables: CHP.ln, BTP.ln, DRL.ln
## Deterministic variables: const
## Sample size: 496
## Log Likelihood: -2772.39
## Roots of the characteristic polynomial:
## 0.3278 0.101 0.07722
## Call:
## VAR(y = data1, p = 1, type = "const")
##
##
## Estimation results for equation CHP.ln:
## =======================================
## CHP.ln = CHP.ln.l1 + BTP.ln.l1 + DRL.ln.l1 + const
##
## Estimate Std. Error t value Pr(>|t|)
## CHP.ln.l1 -0.065543 0.045465 -1.442 0.1500
## BTP.ln.l1 0.005912 0.025465 0.232 0.8165
## DRL.ln.l1 0.060047 0.029509 2.035 0.0424 *
## const 0.065234 0.051629 1.264 0.2070
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Residual standard error: 1.148 on 492 degrees of freedom
## Multiple R-Squared: 0.01357, Adjusted R-squared: 0.007551
## F-statistic: 2.255 on 3 and 492 DF, p-value: 0.08113
##
##
## Estimation results for equation BTP.ln:
## =======================================
## BTP.ln = CHP.ln.l1 + BTP.ln.l1 + DRL.ln.l1 + const
##
## Estimate Std. Error t value Pr(>|t|)
## CHP.ln.l1 -0.03059 0.08094 -0.378 0.706
## BTP.ln.l1 -0.10266 0.04534 -2.264 0.024 *
## DRL.ln.l1 0.04765 0.05254 0.907 0.365
## const 0.01548 0.09192 0.168 0.866
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Residual standard error: 2.044 on 492 degrees of freedom
## Multiple R-Squared: 0.01277, Adjusted R-squared: 0.006748
## F-statistic: 2.121 on 3 and 492 DF, p-value: 0.09668
##
##
## Estimation results for equation DRL.ln:
## =======================================
## DRL.ln = CHP.ln.l1 + BTP.ln.l1 + DRL.ln.l1 + const
##
## Estimate Std. Error t value Pr(>|t|)
## CHP.ln.l1 -0.03229 0.06568 -0.492 0.623
## BTP.ln.l1 -0.01174 0.03679 -0.319 0.750
## DRL.ln.l1 -0.33788 0.04263 -7.926 1.53e-14 ***
## const 0.05283 0.07459 0.708 0.479
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
##
## Residual standard error: 1.658 on 492 degrees of freedom
## Multiple R-Squared: 0.1141, Adjusted R-squared: 0.1087
## F-statistic: 21.13 on 3 and 492 DF, p-value: 6.868e-13
##
##
##
## Covariance matrix of residuals:
## CHP.ln BTP.ln DRL.ln
## CHP.ln 1.3176 0.3361 -0.0880
## BTP.ln 0.3361 4.1762 0.1956
## DRL.ln -0.0880 0.1956 2.7500
##
## Correlation matrix of residuals:
## CHP.ln BTP.ln DRL.ln
## CHP.ln 1.00000 0.14326 -0.04623
## BTP.ln 0.14326 1.00000 0.05771
## DRL.ln -0.04623 0.05771 1.00000#KD TTQ
serial.test(var1)##
## Portmanteau Test (asymptotic)
##
## data: Residuals of VAR object var1
## Chi-squared = 173.03, df = 135, p-value = 0.01512#Du bao 10 phien
forecast1<- predict(var1)
forecast1## $CHP.ln
## fcst lower upper CI
## [1,] 0.06050383 -2.189234 2.310242 2.249738
## [2,] 0.03753013 -2.226075 2.301136 2.263606
## [3,] 0.07384394 -2.191134 2.338821 2.264978
## [4,] 0.05988421 -2.205250 2.325018 2.265134
## [5,] 0.06460234 -2.200549 2.329753 2.265151
## [6,] 0.06304638 -2.202106 2.328199 2.265153
## [7,] 0.06355700 -2.201596 2.328710 2.265153
## [8,] 0.06338958 -2.201763 2.328543 2.265153
## [9,] 0.06344447 -2.201709 2.328597 2.265153
## [10,] 0.06342647 -2.201727 2.328579 2.265153
##
## $BTP.ln
## fcst lower upper CI
## [1,] 0.037286196 -3.968037 4.042609 4.005323
## [2,] -0.009206332 -4.039361 4.020949 4.030155
## [3,] 0.024108833 -4.006905 4.055122 4.031014
## [4,] 0.010232849 -4.020873 4.041339 4.031106
## [5,] 0.015167383 -4.015949 4.046284 4.031116
## [6,] 0.013504027 -4.017614 4.044622 4.031118
## [7,] 0.014054453 -4.017063 4.045172 4.031118
## [8,] 0.013873450 -4.017244 4.044991 4.031118
## [9,] 0.013932847 -4.017185 4.045051 4.031118
## [10,] 0.013913369 -4.017204 4.045031 4.031118
##
## $DRL.ln
## fcst lower upper CI
## [1,] -0.39900189 -3.649238 2.851235 3.250236
## [2,] 0.18525188 -3.246530 3.617034 3.431782
## [3,] -0.01086941 -3.461979 3.440240 3.451110
## [4,] 0.05383283 -3.399359 3.507025 3.453192
## [5,] 0.03258475 -3.420832 3.486001 3.453416
## [6,] 0.03955382 -3.413887 3.492994 3.453440
## [7,] 0.03726887 -3.416174 3.490712 3.453443
## [8,] 0.03801796 -3.415425 3.491461 3.453443
## [9,] 0.03777239 -3.415671 3.491216 3.453443
## [10,] 0.03785289 -3.415591 3.491296 3.453443plot(forecast1)
#Ham phan ung
irf1<-irf(var1)
plot(irf1)
#Phan ra phuong sai
fevd(var1)## $CHP.ln
## CHP.ln BTP.ln DRL.ln
## [1,] 1.0000000 0.0000000000 0.000000000
## [2,] 0.9923587 0.0002546537 0.007386601
## [3,] 0.9911679 0.0002814673 0.008550620
## [4,] 0.9910311 0.0002839220 0.008684982
## [5,] 0.9910162 0.0002841627 0.008699621
## [6,] 0.9910146 0.0002841876 0.008701198
## [7,] 0.9910144 0.0002841902 0.008701368
## [8,] 0.9910144 0.0002841905 0.008701386
## [9,] 0.9910144 0.0002841906 0.008701388
## [10,] 0.9910144 0.0002841906 0.008701388
##
## $BTP.ln
## CHP.ln BTP.ln DRL.ln
## [1,] 0.02052460 0.9794754 0.000000000
## [2,] 0.02139256 0.9771401 0.001467361
## [3,] 0.02140158 0.9767950 0.001803387
## [4,] 0.02140069 0.9767505 0.001848849
## [5,] 0.02140058 0.9767453 0.001854120
## [6,] 0.02140057 0.9767447 0.001854701
## [7,] 0.02140057 0.9767447 0.001854764
## [8,] 0.02140057 0.9767447 0.001854771
## [9,] 0.02140057 0.9767447 0.001854771
## [10,] 0.02140057 0.9767447 0.001854771
##
## $DRL.ln
## CHP.ln BTP.ln DRL.ln
## [1,] 0.002137385 0.004224907 0.9936377
## [2,] 0.001986689 0.004970713 0.9930426
## [3,] 0.001986509 0.005072924 0.9929406
## [4,] 0.001987047 0.005084838 0.9929281
## [5,] 0.001987123 0.005086152 0.9929267
## [6,] 0.001987132 0.005086294 0.9929266
## [7,] 0.001987132 0.005086309 0.9929266
## [8,] 0.001987133 0.005086311 0.9929266
## [9,] 0.001987133 0.005086311 0.9929266
## [10,] 0.001987133 0.005086311 0.9929266plot(fevd(var1))