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EXERCICIO 02
ECONOMETRIA DE SERIES TEMPORAIS
Econometria de series temporais
Amanda Steffany da silva Araujo
Ciências econômicas
Noite
 EXERCÍCIO 2
Dada a série ACR, calcule os retornos e estime um modelo ARMA
(p,q) para os mesmos.
#INDICADOR DO AÇÚCAR CRISTAL ESALQ/BVMF - São Paulo
# de 23/01/2013 a 30/08/2017
# Instalar urca
ACR = AC$ACR
plot.ts(ACR)
#Criar a Variável acr = retornos de ACR
acr <- diff(log(ACR))
acr; plot.ts(acr)
> ACR = AC$ACR
> plot.ts(ACR)
> acr <- diff(log(ACR))
> acr; plot.ts(acr)
 [1] -0.0050079777 0.0050079777 0.0022680890 0.0139484826 -0.0071749187
 [6] 0.0062808641 0.0017873106 -0.0026821652 -0.0022406462 0.0017929185
 [11] -0.0022416508 0.0044782878 0.0053476063 -0.0017793599 0.0008900757
 [16] 0.0026654836 0.0022158219 0.0101300140 -0.0172379959 0.0053357174
 [21] -0.0053357174 -0.0062612011 0.0022406462 0.0106857651 -0.0088968558
 [26] 0.0008932560 0.0168219992 -0.0026373642 0.0030762494 0.0135107743
 [31] -0.0082591211 -0.0039361520 0.0466594370 -0.0168709189 -0.0076857765
 [36] -0.0151158136 -0.0118189163 0.0008802817 -0.0022021590 -0.0057484129
 [41] -0.0133930573 0.0142795822 -0.0044405046 -0.0026737984 0.0084426185
 [46] -0.0008853476 -0.0048834725 -0.0071460778 0.0071460778 0.0097432126
 [51] 0.0035195813 0.0004390779 0.0043802085 0.0074026029 0.0047608833
 [56] 0.0124438422 0.0080696976 -0.0192190413 0.0051613018 0.0042808285
 [61] -0.0017101330 -0.0038585257 -0.0047362844 0.0073102884 0.0012845217
 [66] -0.0073008699 0.0034423442 -0.0081949995 0.0077653539 0.0008591066
 [71] -0.0021491519 -0.0056095077 0.0000000000 -0.0043365202 -0.0074155193
 [76] -0.0158873598 0.0044385337 -0.0008861321 0.0000000000 -0.0178895648
 [81] 0.0004511617 -0.0177479061 0.0100503359 0.0045351552 0.0004523863
 [86] -0.0081744324 -0.0202678518 0.0097245499 -0.0111215233 -0.0004660918
 [91] -0.0004663092 -0.0037383221 -0.0028129414 -0.0042343041 0.0075153008
 [96] -0.0042204049 -0.0009402916 -0.0127812391 -0.0009532889 0.0057061496
 [101] -0.0421267809 0.0009886308 0.0132517277 0.0188365869 0.0081010688
 [106] 0.0113262183 -0.0127510582 -0.0047641824 -0.0076702198 -0.0057915220
 [111] 0.0067535230 -0.0077220461 0.0110817805 -0.0096293474 -0.0107004912
 [116] -0.0053934919 0.0044150182 0.0024443913 -0.0058766085 0.0004910386
 [121] -0.0014738396 0.0058823699 0.0058479699 -0.0117303398 0.0039254221
 [126] 0.0078049177 -0.0097657026 -0.0078818142 -0.0049578684 0.0064404483
 [131] 0.0054173981 0.0000000000 -0.0039370130 -0.0059347355 -0.0009925559
 [136] 0.0034696441 -0.0014855165 -0.0144749221 -0.0030211503 -0.0131981611
 [141] -0.0020460365 -0.0206939614 0.0036524956 -0.0010422096 -0.0073260401
 [146] 0.0156334607 0.0164106247 -0.0153770329 0.0214622443 -0.0040526905
 [151] -0.0117438164 0.0122513018 -0.0025400064 0.0156450327 0.0044966351
 [156] 0.0153354477 0.0107422908 0.0077407256 -0.0048309273 0.0081987438
 [161] 0.0023986579 0.0043031384 -0.0014323230 0.0057170237 0.0225467512
 [166] -0.0004645761 0.0115501400 0.0013770945 -0.0069045153 0.0101103802
 [171] -0.0161330994 0.0129272345 0.0154759575 0.0179055813 0.0013300822
 [176] 0.0008857397 0.0153747812 0.0129928203 -0.0060423145 0.0107643666
 [181] -0.0038618370 0.0119659547 -0.0008499788 0.0135137192 0.0062722347
 [186] 0.0041597398 0.0095022405 0.0024640670 0.0004100882 -0.0041084692
 [191] 0.0073831344 0.0052985655 0.0016246957 -0.0004059265 -0.0155485947
 [196] -0.0216765469 0.0054633462 -0.0126530579 -0.0115262749 -0.0073260401
 [201] -0.0130606994 0.0026258221 -0.0026258221 0.0008760404 0.0026235258
 [206] 0.0233070541 -0.0047038787 -0.0221027416 0.0152209940 -0.0038918968
 [211] 0.0000000000 -0.0056485051 -0.0127166809 -0.0026513493 -0.0147094250
 [216] -0.0185819985 -0.0045850608 -0.0018399269 0.0027586224 0.0054945193
 [221] 0.0113508597 -0.0140943456 -0.0041293933 -0.0097020858 0.0069396531
 [226] 0.0091785867 -0.0142629517 -0.0097788905 -0.0079868877 0.0089223414
 [231] 0.0125437185 0.0073597388 0.0059401591 -0.0267790702 0.0055996413
 [236] 0.0060311016 0.0000000000 -0.0013885677 -0.0168149688 0.0056364640
 [241] 0.0153384369 -0.0167445773 -0.0009385266 -0.0051777004 -0.0018894668
 [246] 0.0098801086 -0.0075188324 -0.0128176452 -0.0019129609 -0.0130090970
 [251] 0.0029055711 -0.0014517302 -0.0063152991 0.0000000000 0.0048614583
 [256] 0.0134876804 -0.0057581733 0.0000000000 0.0048007773 0.0052543708
 [261] 0.0014282316 -0.0124463072 0.0071994551 -0.0052745267 0.0081398582
 [266] 0.0113799237 0.0014134278 0.0070373267 0.0041987465 0.0078831848
 [271] 0.0201195630 0.0045167195 0.0027002717 0.0062724220 0.0022306500
 [276] 0.0008908687 0.0066563370 -0.0066563370 0.0035555593 -0.0040008944
 [281] -0.0089486056 0.0116176463 -0.0075808613 -0.0044863243 0.0071684895
 [286] 0.0013383897 -0.0049162110 0.0071428875 0.0039955658 0.0075038975
 [291] -0.0039656364 0.0179396629 0.0133536337 -0.0034290647 -0.0025795371
 [296] -0.0082127110 0.0013012364 0.0146302093 0.0017072134 0.0101825233
 [301] -0.0063519163 0.0038159894 -0.0059422925 0.0046719134 -0.0085106897
 [306] 0.0029869875 -0.0081283870 0.0000000000 0.0042863332 0.0059701670
 [311] 0.0046659682 -0.0025423743 0.0055003312 -0.0093260532 -0.0025586368
 [316] 0.0029844405 -0.0029844405 -0.0021372096 0.0051216501 -0.0119915784
 [321] 0.0025817570 0.0025751087 0.0021408700 0.0042680389 0.0017021281
 [326] -0.0085397615 0.0025695946 -0.0098861755 0.0012950574 -0.0008631852
 [331] 0.0017256260 -0.0138891122 0.0043611059 0.0000000000 -0.0149060191
 [336] -0.0030966625 -0.0062222423 -0.0121104867 -0.0072464085 0.0157838677
 [341] 0.0008944544 0.0008936551 0.0000000000 -0.0004467277 -0.0112335488
 [346] -0.0013565455 0.0018083188 0.0103348482 0.0057945337 -0.0080321717
 [351] 0.0026845654 0.0049030631 0.0110547224 -0.0035242327 -0.0102019071
 [356] -0.0013383897 -0.0049228115 0.0008968610 -0.0044923705 -0.0063234176
 [361] 0.0027149338 -0.0054372585 -0.0040974335 -0.0110092855 -0.0027713644
 [366] -0.0135042797 0.0051438037 0.0074349785 -0.0013898543 0.0009267841
 [371] -0.0041773094 -0.0116960398 0.0032887039 -0.0032887039 -0.0099315075
 [376] -0.0071548123 -0.0125242485 -0.0038853861 -0.0127327871 0.0068762550
 [381] -0.0103321952 -0.0054550098 0.0138273808 0.0048923777 0.0000000000
 [386] 0.0043827682 0.0019417482 0.0019379851 -0.0043657600 0.0024277749
 [391] 0.0000000000 -0.0146558559 0.0049091900 -0.0029426211 0.0097752489
 [396] 0.0048520231 0.0009675859 0.0024148768 -0.0033824628 0.0125061755
 [401] -0.0071960013 -0.0057943185 -0.0053411149 -0.0196663172 -0.0049776111
 [406] 0.0044809634 -0.0261715994 -0.0046000592 -0.0035925109 0.0025673955
 [411] -0.0170679085 0.0057217321 -0.0109518696 -0.0063124881 0.0000000000
 [416] 0.0089309761 -0.0010465726 0.0015694484 0.0020887736 -0.0073298757
 [421] 0.0026239847 0.0036620496 0.0409264277 0.0050000104 0.0069582786
 [426] 0.0078934796 -0.0073983075 0.0147422817 -0.0058708583 -0.0138342127
 [431] -0.0140282862 0.0175048231 0.0009910804 -0.0049652535 0.0034782644
 [436] -0.0054712895 0.0049751346 -0.0175223507 0.0165293020 0.0235651553
 [441] 0.0106178604 -0.0145070242 -0.0083150393 -0.0218479395 -0.0025131956
 [446] 0.0045192143 -0.0161619680 0.0231515121 -0.0029895388 0.0079523282
 [451] -0.0119523335 -0.0176906307 0.0101472205 0.0115434155 0.0049776111
 [456] 0.0157638732 0.0024408116 0.0072868916 0.0105922993 0.0052543708
 [461] -0.0250857342 -0.0009775172 -0.0044106908 0.0044106908 -0.0088409220
 [466] 0.0024636622 -0.0054280913 -0.0039662918 0.0093943831 -0.0173744753
 [471] -0.0197225103 -0.0035814825 -0.0264881755 0.0073414069 0.0262969523
 [476] 0.0055823540-0.0015193723 -0.0107007390 -0.0071979745 0.0041194703
 [481] 0.0081883774 -0.0159263577 -0.0130311982 -0.0010498689 0.0031463057
 [486] -0.0052493559 0.0167018496 -0.0010357329 0.0072277031 0.0117618334
 [491] -0.0015263295 0.0015263295 -0.0035650662 0.0005100740 0.0171895031
 [496] 0.0124534611 -0.0079523282 -0.0075131834 0.0035131780 -0.0005011275
 [501] -0.0060332008 -0.0224384733 -0.0124547536 -0.0020909574 -0.0110498362
 [506] -0.0186921330 -0.0081191244 -0.0049033059 -0.0104310581 -0.0183797989
 [511] 0.0011235956 0.0111670619 -0.0066852617 -0.0011185683 -0.0084293840
 [516] -0.0011293056 0.0005648122 0.0011286683 -0.0084962278 -0.0028481933
 [521] 0.0085203583 -0.0113766870 -0.0266682471 -0.0058927690 -0.0083086531
 [526] -0.0168273201 -0.0054694758 0.0103062446 0.0012055457 -0.0343170929
 [531] 0.0018685773 -0.0194790953 0.0063251318 -0.0012618298 0.0100503359
 [536] 0.0179627004 0.0115961019 -0.0024301349 -0.0153236219 -0.0055744957
 [541] -0.0106151481 0.0161896438 0.0232000637 0.0054168053 0.0266524512
 [546] -0.0046865932 0.0046865932 0.0162322405 -0.0104047181 -0.0105141155
 [551] 0.0041019688 0.0104712999 0.0109353608 -0.0115142320 0.0074993141
 [556] 0.0074434927 0.0062553516 0.0140728469 0.0111174019 0.0038620738
 [561] -0.0188999511 -0.0238512158 -0.0232568622 0.0035231980 0.0087540682
 [566] -0.0034924366 0.0104409301 -0.0069484935 -0.0034924366 0.0098637295
 [571] 0.0034582167 0.0068807611 -0.0120725812 0.0011560695 -0.0046323186
 [576] -0.0034883756 -0.0152585120 -0.0179002393 -0.0127235888 -0.0141236612
 [581] -0.0024767815 -0.0043491836 0.0006224712 0.0117539244 0.0122250911
 [586] -0.0146881466 0.0177212092 0.0114424615 0.0011968882 -0.0285126989
 [591] 0.0055231807 -0.0024509816 -0.0117249106 -0.0056022555 0.0031162381
 [596] -0.0150473059 -0.0006319116 -0.0108040454 0.0057343260 -0.0050955524
 [601] -0.0044800075 -0.0032123381 0.0096062218 -0.0096062218 0.0044943896
 [606] 0.0019200006 -0.0032020520 -0.0083736399 -0.0156456907 0.0169385157
 [611] 0.0153849188 0.0132703369 -0.0113637587 0.0031695748 -0.0133802570
 [616] -0.0083736399 0.0077319973 -0.0122700926 -0.0270019698 -0.0147951589
 [621] -0.0108992905 -0.0075627724 0.0109815791 -0.0034188067 -0.0124053969
 [626] -0.0174890782 -0.0134993169 -0.0043010819 -0.0181230042 0.0036509716
 [631] 0.0065383451 -0.0087273281 0.0065526263 0.0000000000 0.0101083893
 [636] 0.0000000000 -0.0021574981 -0.0007202017 0.0107489390 -0.0057183858
 [641] -0.0151682215 0.0021810259 -0.0235132067 0.0264138614 -0.0029006547
 [646] -0.0227699885 -0.0044676173 -0.0112571545 -0.0022667180 0.0015117161
 [651] 0.0037693222 0.0186363948 -0.0059259433 0.0074019583 0.0095413568
 [656] 0.0094511790 0.0143680633 -0.0064400938 -0.0043165535 -0.0130625950
 [661] -0.0095413568 -0.0133632278 -0.0173392961 0.0697530388 -0.0078320087
 [666] -0.0165769562 0.0384937048 0.0234979713 0.0013651879 0.0355146201
 [671] 0.0425321837 0.0395846362 -0.0030367469 0.0340840168 -0.0047142103
 [676] 0.0099912674 0.0122059057 0.0028843400 -0.0145056213 0.0333364203
 [681] -0.0119421379 0.0051355320 0.0241788557 0.0257760363 -0.0070633274
 [686] 0.0194390570 -0.0069761485 0.0338836014 0.0165207681 0.0122138923
 [691] -0.0045627456 0.0015232295 0.0080849354 0.0010060363 0.0253178080
 [696] -0.0118344576 0.0054415173 -0.0059376721 0.0108589418 -0.0024576075
 [701] 0.0180448690 0.0105770217 0.0042949243 -0.0163229740 -0.0004841443
 [706] 0.0120338396 -0.0271597684 -0.0059171770 0.0059171770 0.0189925358
 [711] 0.0105567199 0.0080818125 -0.0114286958 0.0114286958 0.0000000000
 [716] -0.0133462420 -0.0106127383 0.0149220579 -0.0149220579 0.0091721618
 [721] 0.0023998092 -0.0198505671 0.0014659177 0.0034121408 0.0144930073
 [726] 0.0204137162 -0.0199342149 -0.0306667984 0.0073873766 -0.0063992342
 [731] -0.0024721891 0.0039525743 0.0112773934 0.0053489065 0.0158771678
 [736] -0.0139391827 0.0014510281 0.0028957549 0.0009633912 -0.0165052291
 [741] -0.0152900636 0.0014899432 -0.0029821096 0.0108911968 -0.0039467244
 [746] 0.0088583256 0.0087805442 -0.0038929490 0.0019483689 0.0140132759
 [751] -0.0081908432 -0.0136387891 -0.0108482326 0.0019811794 -0.0024770882
 [756] -0.0034782644 -0.0100050860 0.0100050860 -0.0190960577 0.0225743220
 [761] -0.0039761484 -0.0185981737 0.0085880801 0.0030135633 -0.0090680722
 [766] -0.0081301261 0.0197025823 0.0114400651 0.0273187721 -0.0184560848
 [771] 0.0029368597 0.0164812262 0.0105213787 0.0141712338 0.0028103063
 [776] -0.0217502664 -0.0271334475 0.0394851485 0.0047103243 -0.0023523888
 [781] 0.0000000000 -0.0123224308 -0.0066985896 0.0114559725 -0.0061890224
 [786] 0.0156364238 0.0084270162 -0.0140847399 -0.0037896777 -0.0196507641
 [791] -0.0121744869 0.0014687885 0.0077973105 0.0254027558 0.0004731488
 [796] -0.0028422568 0.0094429408 -0.0004700353 -0.0094474014 0.0075650479
 [801] -0.0033026687 -0.0104514015 0.0151661675 0.0074976921 -0.0023369957
 [806] 0.0083877472 0.0124511639 -0.0101336657 -0.0205807077 0.0061248719
 [811] -0.0009398497 -0.0051850222 0.0000000000 0.0103432986 0.0107002649
 [816] -0.0046382272 -0.0093414972 0.0084112645 0.0018596007 -0.0037226660
 [821] -0.0164516049 0.0201742709 -0.0046555019 0.0055840071 -0.0079199110
 [826] -0.0075117724 0.0089139694 0.0018665428 0.0023282898 0.0161479864
 [831] 0.0239667813 0.0194696416 0.0173766318 0.0342890735 0.0128180378
 [836] -0.0124019779 -0.0054223282 -0.0012554929 0.0091705520 0.0107306023
 [841] 0.0134558605 0.0283508707 -0.0023649991 0.0027586224 0.0136801039
 [846] -0.0062305498 -0.0109977542 0.0249622946 0.0266074229 0.0014992507
 [851] -0.0003746020 0.0018716083 -0.0124178454 -0.0095111997 -0.0130821412
 [856] 0.0077160877 -0.0030792942 0.0065322038 -0.0123315628 0.0165356584
 [861] -0.0088106297 0.0011536244 -0.0030792942 0.0015408324 0.0065221793
 [866] 0.0011465700 0.0000000000 -0.0011465700 -0.0061373419 0.0061373419
 [871] 0.0072395058 -0.0191650174 0.0073260401 -0.0166573675 0.0269765877
 [876] 0.0143452819 -0.0011250704 0.0137881819 -0.0014814818 -0.0100578237
 [881] 0.0007485030 0.0044792908 0.0040884651 -0.0183422698 -0.0037850159
 [886] -0.0034188067 0.0075815375 0.0067745837 -0.0037579901 -0.0037721659
 [891] 0.0135137192 -0.0176796029 0.0037878833 -0.0049270518 0.0011391685
 [896] -0.0041833109 -0.0015255533 0.0049495627 0.0173197100 -0.0291632105
 [901] 0.0007683443 0.0019182818 -0.0220896407 0.0023483377 0.0050692251
 [906] 0.0223086175 0.0034175085 0.0109331909 0.0259081849 0.0007304602
 [911] 0.0036443189 0.0122922734 0.0035868044 0.0417238434 -0.0089686700
 [916] -0.0013869628 0.0048459769 0.0006903694 0.0027567212 0.0140101386
 [921] -0.0030586260 0.0027192403 0.0003393857 0.0128120431 0.0040120415
 [926] 0.0013337781 0.0119246196 0.0042714046 -0.0013123361 0.0223998978
 [931] 0.0168713217 0.0000000000 -0.0085592534 -0.0099184944 -0.0012870015
 [936] -0.0159016818 -0.0161586368 0.0006646727 0.0197374828 -0.0042435187
 [941] -0.0068931834 -0.0345150695 -0.0332786342 -0.0127706595 0.0014270427
 [946] -0.0017841218 0.0000000000 0.0110105889 -0.0021216415 -0.0265438827
 [951] -0.0220516102 0.0018563213 0.0125324161 -0.0066152391 -0.0059171770
 [956] -0.0130672011 -0.0117181458 -0.0019029501 0.0072120259 0.0172482716
 [961] -0.0157365555 0.0037693222 0.0101067677 0.0040884651 -0.0048336216
 [966] -0.0275853501 -0.0049932887 0.0007698230 0.0107157550 0.0056936954
 [971] 0.0003784295 0.0198545574 0.0025930742 0.0040612941 -0.0003685277
 [976] 0.0047802996 -0.0088430937 0.0029563954 0.0029476808 -0.0051641575
 [981] 0.0029542119 0.0058823699 0.0010991025 -0.0062442811 0.0084388686
 [986] -0.0088073964 -0.0070279557 -0.0048372187 -0.0018667170 -0.0029940142
 [991] 0.0033676365 0.0078139932-0.0029695642 -0.0202785770 0.0094393754
 [996] 0.0156602753 0.0066371925 -0.0260625325 -0.0094751514 0.0041801315
 [ reached getOption("max.print") -- omitted 142 entries ]
• Calcule FAC e a FACP;
#FAC
acf(acr, lag.max =30)
#FACP
pacf(acr, lag.max = 30)
• Defina p e q;
armafit <- arima(acr,order=c(1,0,1), method = "ML",include.mean = FALSE)
summary(armafit)
	Call:
arima(x = acr, order = c(1, 0, 1), include.mean = FALSE, method = "ML")
Coefficients:
 ar1 ma1
 0.9458 -0.9028
s.e. 0.0258 0.0333
sigma^2 estimated as 0.0001421: log likelihood = 3437.85, aic = -6869.7
Training set error measures:
 ME RMSE MAE MPE MAPE MASE ACF1
Training set -0.0001385744 0.01192216 0.00879015 NaN Inf 0.7237593 0.002808659
	
		> 
• Faça o diagnóstico dos melhores modelos, usando como
critério o R2-ajustado, t-student, AIC, BIC, Q (Ljung-Box) e Erro
de previsão (acurrancy);
> AIC(armafit)
[1] -6869.704
> rfit <- residuals(armafit); rfit
Time Series:
Start = 1 
End = 1142 
Frequency = 1 
 [1] -4.964694e-03 5.264213e-03 2.238634e-03 1.375077e-02 -7.979645e-03
 [6] 5.871558e-03 1.129469e-03 -3.348805e-03 -2.717055e-03 1.461092e-03
 [11] -2.617239e-03 4.234394e-03 4.928294e-03 -2.389471e-03 4.167416e-04
 [16] 2.198898e-03 1.678774e-03 9.547097e-03 -1.819806e-02 5.212198e-03
 [21] -5.676547e-03 -6.338232e-03 2.440580e-03 1.076900e-02 -9.281078e-03
 [26] 9.291573e-04 1.681532e-02 -3.366796e-03 2.531068e-03 1.288603e-02
 [31] -9.403856e-03 -4.614509e-03 4.621568e-02 -1.927702e-02 -9.132823e-03
 [36] -1.609179e-02 -1.205032e-02 1.179329e-03 -1.969998e-03 -5.444154e-03
 [41] -1.287129e-02 1.532621e-02 -4.109255e-03 -2.183901e-03 8.999811e-03
 [46] -7.451218e-04 -4.718822e-03 -6.787556e-03 7.776860e-03 1.000560e-02
 [51] 3.337756e-03 1.236685e-04 4.076578e-03 6.940238e-03 4.025323e-03
 [56] 1.157516e-02 6.750657e-03 -2.075670e-02 4.598987e-03 3.551350e-03
 [61] -2.552693e-03 -4.545722e-03 -5.190887e-03 7.103399e-03 7.835805e-04
 [66] -7.808336e-03 3.297940e-03 -8.473305e-03 7.866267e-03 6.165025e-04
 [71] -2.405102e-03 -5.748228e-03 1.158244e-04 -4.231951e-03 -7.134751e-03
 [76] -1.531520e-02 5.637848e-03 5.900904e-06 8.434344e-04 -1.712809e-02
 [81] 1.907438e-03 -1.645253e-02 1.198255e-02 5.847706e-03 1.442500e-03
 [86] -7.299970e-03 -1.912707e-02 1.162548e-02 -9.823215e-03 1.183999e-03
 [91] 1.043471e-03 -2.355209e-03 -1.403575e-03 -2.841002e-03 8.955181e-03
 [96] -3.243405e-03 1.231421e-04 -1.178073e-02 4.992641e-04 7.058524e-03
 [101] -4.115104e-02 3.679934e-03 1.563903e-02 2.042243e-02 8.723321e-03
 [106] 1.153987e-02 -1.304491e-02 -4.481509e-03 -7.210276e-03 -5.046648e-03
 [111] 7.674904e-03 -7.180425e-03 1.190262e-02 -9.364501e-03 -1.004756e-02
 [116] -4.344164e-03 5.594164e-03 3.319226e-03 -5.191828e-03 1.361822e-03
 [121] -7.087733e-04 6.636431e-03 6.275967e-03 -1.159524e-02 4.551495e-03
 [126] 8.201462e-03 -9.743103e-03 -7.441735e-03 -4.221836e-03 7.318021e-03
 [131] 5.932922e-03 2.326207e-04 -3.726996e-03 -5.575936e-03 -4.135793e-04
 [136] 4.035016e-03 -1.124188e-03 -1.408487e-02 -2.046945e-03 -1.218879e-02
 [141] -5.675624e-04 -1.927122e-02 5.826294e-03 7.633952e-04 -5.651099e-03
 [146] 1.746048e-02 1.738827e-02 -1.519962e-02 2.228323e-02 -4.233803e-03
 [151] -1.173317e-02 1.276560e-02 -2.602176e-03 1.569806e-02 3.872173e-03
 [156] 1.457843e-02 9.399798e-03 6.067040e-03 -6.674632e-03 6.741799e-03
 [161] 7.309502e-04 2.694402e-03 -3.069661e-03 4.300340e-03 2.102204e-02
 [166] -2.810060e-03 9.452533e-03 -1.013046e-03 -9.121584e-03 8.405463e-03
 [171] -1.810684e-02 1.183860e-02 1.393756e-02 1.585161e-02 -1.293788e-03
 [176] -1.540326e-03 1.314639e-02 1.032025e-02 -9.013551e-03 8.341512e-03
 [181] -6.511853e-03 9.739403e-03 -3.374404e-03 1.127112e-02 3.666809e-03
 [186] 1.537940e-03 6.956441e-03 -2.427080e-04 -2.139559e-03 -6.427988e-03
 [191] 5.465564e-03 3.250041e-03 -4.524743e-04 -2.351077e-03 -1.728729e-02
 [196] -2.257810e-02 5.580935e-03 -1.278168e-02 -1.109864e-02 -6.444625e-03
 [201] -1.195010e-02 4.189779e-03 -1.326679e-03 2.161787e-03 3.746688e-03
 [206] 2.420833e-02 -4.891783e-03 -2.207024e-02 1.620019e-02 -3.661965e-03
 [211] 3.748412e-04 -5.310088e-03 -1.216841e-02 -1.609860e-03 -1.365520e-02
 [216] -1.699808e-02 -2.356506e-03 3.691175e-04 4.832082e-03 7.247949e-03
 [221] 1.269778e-02 -1.336610e-02 -2.866216e-03 -8.384194e-03 8.546425e-03
 [226] 1.033100e-02 -1.361696e-02 -8.582732e-03 -6.486719e-03 1.061997e-02
 [231] 1.369295e-02 7.858244e-03 6.073944e-03 -2.691356e-02 6.629034e-03
 [236] 6.719826e-03 3.626176e-04 -1.061186e-03 -1.645973e-02 6.679800e-03
 [241] 1.603817e-02 -1.677200e-02 -2.436965e-04 -4.510055e-03 -1.064189e-03
 [246] 1.070639e-02 -7.197431e-03 -1.220436e-02 -8.084363e-04 -1.192969e-02
 [251] 4.439148e-03 -1.920378e-04 -5.115625e-03 1.354497e-03 6.084338e-03
 [256] 1.438281e-02 -5.529646e-03 4.537753e-04 5.210459e-03 5.417933e-03
 [261] 1.350097e-03 -1.257823e-02 7.615227e-03 -5.208548e-03 8.426095e-03
 [266] 1.128854e-02 8.418799e-04 6.460575e-03 3.375614e-03 6.959598e-03
 [271] 1.894695e-02 2.593422e-03 7.697593e-04 4.413457e-03 2.827685e-04
 [276] -9.635964e-04 4.943787e-03 -8.488529e-03 2.187455e-03 -5.388857e-03
 [281] -1.002976e-02 1.102611e-02 -8.614181e-03 -5.093453e-03 6.813153e-03
 [286] 7.095201e-04 -5.541489e-03 6.789639e-03 3.369682e-03 6.767124e-03
 [291] -4.953292e-03 1.721840e-02 1.193151e-02 -5.286864e-03 -4.109450e-03
 [296] -9.483107e-03 5.072218e-04 1.385743e-02 3.808015e-04 8.911634e-03
 [301] -7.936900e-03 2.657989e-03 -7.151759e-03 3.835338e-03 -9.466746e-03
 [306] 2.489573e-03 -8.705831e-03 -1.720210e-04 4.131028e-03 5.645750e-03
 [311] 4.116511e-03 -3.238957e-03 4.980693e-03 -1.003157e-02 -2.794818e-03
 [316] 2.881165e-03 -3.205935e-03 -2.208927e-03 5.148747e-03 -1.218721e-02
 [321] 2.920462e-03 2.769952e-03 2.206116e-03 4.234943e-03 1.488832e-03
 [326] -8.805480e-03 2.696687e-03 -9.881859e-03 1.723807e-03 -5.317522e-04
 [331] 2.061948e-03 -1.365963e-02 5.165167e-03 5.385136e-04 -1.441983e-02
 [336] -2.017143e-03 -5.114543e-03 -1.084303e-02 -5.581668e-03 1.759825e-02
 [341] 1.854233e-03 1.721733e-03 7.092084e-04 1.935663e-04 -1.063627e-02
 [346] -3.345544e-04 2.789299e-03 1.114279e-02 6.079837e-03 -8.023608e-03
 [351] 3.037475e-03 5.106312e-03 1.102752e-02 -4.023865e-03 -1.050154e-02
 [356] -1.170485e-03 -4.713706e-03 1.297203e-03 -4.169473e-03 -5.838839e-03
 [361] 3.424170e-03 -4.913612e-03 -3.391007e-03 -1.019542e-02 -1.563464e-03
 [366] -1.229465e-02 6.816227e-03 8.723839e-03 -5.457471e-04 1.748597e-03
 [371] -3.475181e-03 -1.088262e-02 4.525713e-03 -2.313226e-03 -8.909488e-03
 [376] -5.805303e-03 -1.099840e-02 -1.969582e-03 -1.083617e-02 9.135758e-03
 [381] -8.587752e-03 -3.436056e-03 1.588458e-02 6.155451e-03 9.300926e-04
 [386] 5.222483e-03 2.511520e-03 2.368947e-03 -4.059959e-03 2.891477e-03
 [391] 3.143114e-04 -1.437209e-02 5.795212e-03 -2.353664e-03 1.043343e-02
 [396] 5.026166e-03 9.162948e-04 2.326988e-03 -3.565589e-03 1.248620e-02
 [401] -7.751478e-03 -5.986575e-03 -5.265683e-03 -1.936868e-02 -3.863751e-03
 [406] 5.700498e-03 -2.526313e-02 -2.655162e-03 -1.638917e-03 4.485543e-03
 [411] -1.544648e-02 7.919087e-03 -9.213921e-03 -4.272768e-03 2.112794e-03
 [416] 1.083847e-02 2.917638e-04 2.822713e-03 3.152812e-03 -6.458995e-03
 [421] 3.725238e-03 4.543529e-03 4.156488e-02 3.817635e-03 5.675923e-03
 [426] 6.436704e-03 -9.052744e-03 1.356655e-02 -7.565888e-03 -1.511224e-02
 [431] -1.458761e-02 1.760271e-02 3.271947e-04 -5.607220e-03 3.112057e-03
 [436] -5.951388e-03 4.776813e-03 -1.791520e-02 1.692763e-02 2.321444e-02
 [441] 9.288531e-03 -1.616348e-02 -9.187104e-03 -2.227793e-02-1.962503e-03
 [446] 5.124399e-03 -1.580980e-02 2.416401e-02 -3.070348e-03 8.007845e-03
 [451] -1.224396e-02 -1.744027e-02 1.113349e-02 1.199778e-02 4.891755e-03
 [456] 1.547245e-02 1.500264e-03 6.332845e-03 9.417809e-03 3.738809e-03
 [461] -2.667983e-02 -1.338670e-03 -4.694742e-03 4.343787e-03 -9.090871e-03
 [466] 2.617934e-03 -5.394684e-03 -3.702862e-03 9.802664e-03 -1.740959e-02
 [471] -1.900755e-02 -2.088434e-03 -2.498630e-02 9.835660e-03 2.823334e-02
 [476] 6.200490e-03 -1.201199e-03 -1.034819e-02 -6.419824e-03 5.131336e-03
 [481] 8.924887e-03 -1.561331e-02 -1.206414e-02 3.832269e-04 4.485264e-03
 [486] -4.175716e-03 1.789675e-02 -6.746928e-04 7.598171e-03 1.178570e-02
 [491] -2.010243e-03 1.155031e-03 -3.965878e-03 3.014159e-04 1.697920e-02
 [496] 1.152489e-02 -9.325853e-03 -8.411495e-03 3.025030e-03 -1.092818e-03
 [501] -6.545861e-03 -2.264204e-02 -1.167426e-02 -8.510737e-04 -9.840575e-03
 [506] -1.712552e-02 -5.901455e-03 -2.552215e-03 -8.097708e-03 -1.582491e-02
 [511] 4.220080e-03 1.391437e-02 -4.684807e-03 9.747956e-04 -6.491364e-03
 [516] 9.826427e-04 2.520072e-03 2.869661e-03 -6.972912e-03 -1.107780e-03
 [521] 1.021405e-02 -1.021373e-02 -2.512939e-02 -3.357389e-03 -5.766400e-03
 [526] -1.417504e-02 -2.351777e-03 1.335604e-02 3.516087e-03 -3.228288e-02
 [531] 5.179883e-03 -1.656985e-02 9.788782e-03 1.593436e-03 1.268238e-02
 [536] 1.990708e-02 1.257961e-02 -2.040532e-03 -1.486744e-02 -4.504121e-03
 [541] -9.409222e-03 1.773457e-02 2.389913e-02 5.050931e-03 2.608935e-02
 [546] -6.340354e-03 3.394933e-03 1.486469e-02 -1.233695e-02 -1.181146e-02
 [551] 3.382528e-03 9.645488e-03 9.739796e-03 -1.306356e-02 6.595350e-03
 [556] 6.305089e-03 4.907688e-03 1.258732e-02 9.171450e-03 1.627449e-03
 [561] -2.108341e-02 -2.501029e-02 -2.327832e-02 4.503278e-03 9.487506e-03
 [566] -3.206469e-03 1.084920e-02 -7.028592e-03 -3.266145e-03 1.021812e-02
 [571] 3.354281e-03 6.638310e-03 -1.258717e-02 1.210296e-03 -4.633043e-03
 [576] -3.289958e-03 -1.492946e-02 -1.694744e-02 -1.109412e-02 -1.210574e-02
 [581] -4.799066e-05 -2.049962e-03 2.885179e-03 1.377001e-02 1.354016e-02
 [586] -1.402623e-02 1.895002e-02 1.179031e-02 1.019202e-03 -2.872455e-02
 [591] 6.557226e-03 -1.754770e-03 -1.099102e-02 -4.435808e-03 4.410094e-03
 [596] -1.401309e-02 9.484545e-04 -9.350089e-03 7.511297e-03 -3.737680e-03
 [601] -3.035102e-03 -1.715310e-03 1.109583e-02 -8.674181e-03 5.748685e-03
 [606] 2.859271e-03 -2.436562e-03 -7.544927e-03 -1.453765e-02 1.861125e-02
 [611] 1.616719e-02 1.331544e-02 -1.189333e-02 3.179816e-03 -1.350722e-02
 [616] -7.913259e-03 8.507495e-03 -1.190223e-02 -2.614255e-02 -1.285886e-02
 [621] -8.515329e-03 -4.942073e-03 1.367263e-02 -1.461175e-03 -1.049107e-02
 [626] -1.522765e-02 -1.070605e-02 -1.199118e-03 -1.513762e-02 7.125085e-03
 [631] 9.517977e-03 -6.318210e-03 9.102699e-03 2.020685e-03 1.193272e-02
 [636] 1.212660e-03 -1.062673e-03 3.609552e-04 1.175599e-02 -5.271120e-03
 [641] -1.451867e-02 3.419302e-03 -2.248898e-02 2.834903e-02 -2.288651e-03
 [646] -2.209280e-02 -2.877706e-03 -9.629743e-03 -3.136742e-04 3.372392e-03
 [651] 5.384230e-03 1.993240e-02 -5.556763e-03 7.989929e-03 9.754099e-03
 [656] 9.233215e-03 1.376512e-02 -7.601907e-03 -5.088713e-03 -1.357422e-02
 [661] -9.441912e-03 -1.286341e-02 -1.631377e-02 7.142406e-02 -9.320957e-03
 [666] -1.758465e-02 3.829632e-02 2.166552e-02 -1.299013e-03 3.305063e-02
 [671] 3.878141e-02 3.437053e-02 -9.445318e-03 2.842867e-02 -1.128476e-02
 [676] 4.261775e-03 6.603785e-03 -2.697959e-03 -1.966944e-02 2.929775e-02
 [681] -1.702098e-02 1.063409e-03 2.028173e-02 2.121852e-02 -1.228569e-02
 [686] 1.502770e-02 -1.179423e-02 2.983349e-02 1.140808e-02 6.888040e-03
 [691] -9.895965e-03 -3.095675e-03 3.849394e-03 -3.165379e-03 2.150850e-02
 [696] -1.636163e-02 1.862832e-03 -9.402459e-03 7.985999e-03 -5.518041e-03
 [701] 1.538743e-02 7.402346e-03 9.741931e-04 -1.950560e-02 -2.656041e-03
 [706] 1.009379e-02 -2.942845e-02 -6.798231e-03 5.376023e-03 1.824968e-02
 [711] 9.069855e-03 6.285759e-03 -1.339754e-02 1.014231e-02 -1.652527e-03
 [716] -1.483819e-02 -1.138617e-02 1.467986e-02 -1.578199e-02 9.037058e-03
 [721] 1.883665e-03 -2.041969e-02 1.805165e-03 3.655427e-03 1.456602e-02
 [726] 1.985680e-02 -2.131428e-02 -3.105610e-02 8.353791e-03 -5.844195e-03
 [731] -1.696080e-03 4.759509e-03 1.183606e-02 5.368646e-03 1.566512e-02
 [736] -1.481293e-02 1.261208e-03 2.662023e-03 6.279276e-04 -1.684950e-02
 [741] -1.489158e-02 2.506790e-03 -2.128100e-03 1.179038e-02 -3.602962e-03
 [746] 9.338293e-03 8.833191e-03 -4.222756e-03 1.817907e-03 1.381176e-02
 [751] -8.974989e-03 -1.399474e-02 -1.058348e-02 2.686403e-03 -1.925532e-03
 [756] -2.873852e-03 -9.309929e-03 1.106266e-02 -1.857121e-02 2.386881e-02
 [761] -3.777567e-03 -1.824802e-02 9.703458e-03 3.651491e-03 -8.621638e-03
 [766] -7.337378e-03 2.076769e-02 1.155497e-02 2.693088e-02 -1.998029e-02
 [771] 2.353898e-03 1.582870e-02 9.223990e-03 1.254776e-02 7.355900e-04
 [776] -2.374415e-02 -2.799888e-02 3.986985e-02 3.360797e-03 -3.773205e-03
 [781] -1.181662e-03 -1.338927e-02 -7.132214e-03 1.135235e-02 -6.774888e-03
 [786] 1.537346e-02 7.517636e-03 -1.526790e-02 -4.252586e-03 -1.990583e-02
 [791] -1.156029e-02 2.546494e-03 8.707174e-03 2.588912e-02 -1.794128e-04
 [796] -3.451742e-03 9.014824e-03 -1.262356e-03 -1.014253e-02 7.343460e-03
 [801] -3.827828e-03 -1.078360e-02 1.531539e-02 6.980659e-03 -3.125997e-03
 [806] 7.775845e-03 1.153826e-02 -1.149294e-02 -2.137241e-02 6.294540e-03
 [811] -1.049881e-03 -5.243972e-03 1.696015e-04 1.049642e-02 1.039401e-02
 [816] -5.374560e-03 -9.806955e-03 8.392481e-03 1.481173e-03 -4.144237e-03
 [821] -1.667223e-02 2.068208e-02 -5.064014e-03 5.415258e-03 -8.312232e-03
 [826] -7.525618e-03 9.224283e-03 1.763631e-03 2.155164e-03 1.589163e-02
 [831] 2.304138e-02 1.760421e-02 1.485577e-02 3.126641e-02 8.615541e-03
 [836] -1.674696e-02 -8.812139e-03 -4.082892e-03 6.671848e-03 8.080600e-03
 [841] 1.060222e-02 2.519626e-02 -6.431431e-03 -8.110366e-04 1.033876e-02
 [846] -9.835105e-03 -1.398430e-02 2.273858e-02 2.352705e-02 -2.425240e-03
 [851] -3.982176e-03 -1.369316e-03 -1.542428e-02 -1.169185e-02 -1.464215e-02
 [856] 6.869860e-03 -4.174888e-03 5.675401e-03 -1.338583e-02 1.611378e-02
 [861] -9.902124e-03 5.468227e-04 -3.676709e-03 1.133800e-03 6.088482e-03
 [866] 4.747289e-04 -6.558309e-04 -1.738673e-03 -6.622637e-03 5.962952e-03
 [871] 6.818313e-03 -1.985640e-02 7.525448e-03 -1.679217e-02 2.757073e-02
 [876] 1.372239e-02 -2.303919e-03 1.277223e-02 -2.991250e-03 -1.135722e-02
 [881] 7.598474e-06 3.778214e-03 3.263018e-03 -1.926321e-02 -3.828217e-03
 [886] -3.295151e-03 7.840098e-03 6.682208e-03 -4.132523e-03 -3.948808e-03
 [891] 1.351635e-02 -1.825797e-02 4.025484e-03 -4.875321e-03 1.397609e-03
 [896] -3.998938e-03 -1.179321e-03 5.327711e-03 1.744841e-02 -2.979132e-02
 [901] 1.454539e-03 2.504779e-03 -2.164257e-02 3.701254e-03 6.189759e-03
 [906] 2.310242e-02 3.175479e-03 1.056781e-02 2.510847e-02 -1.104938e-03
 [911] 1.955877e-03 1.061129e-02 1.540907e-03 3.972261e-02 -1.256850e-02
 [916] -4.251572e-03 2.319328e-03 -1.799016e-03 4.795635e-04 1.183579e-02
 [921] -5.623772e-03 5.347941e-04 -1.749654e-03 1.091141e-02 1.745507e-03
 [926] -8.849302e-04 9.864187e-03 1.898733e-03 -3.638015e-03 2.035660e-02
 [931] 1.406396e-02 -3.259607e-03 -1.150212e-02 -1.220757e-02 -2.927407e-03
 [936] -1.732738e-02 -1.676243e-02 8.139544e-04 1.984369e-02 -4.995833e-03
 [941] -7.390033e-03 -3.466741e-02 -3.193291e-02 -1.012557e-02 4.363918e-03
 [946] 8.060489e-04 2.415153e-03 1.319106e-02 -6.262221e-04 -2.510260e-02
 [951] -1.960967e-02 5.008631e-03 1.529864e-02 -4.656385e-03 -3.864381e-03
 [956] -1.095959e-02 -9.253778e-03 8.255328e-04 9.757158e-03 1.923616e-02[961] -1.468307e-02 5.396711e-03 1.141404e-02 4.834375e-03 -4.335892e-03
 [966] -2.692826e-02 -3.214588e-03 2.590269e-03 1.232622e-02 6.687171e-03
 [971] 1.030685e-03 2.042717e-02 2.256808e-03 3.646268e-03 -9.177572e-04
 [976] 4.300276e-03 -9.481903e-03 2.759686e-03 2.643037e-03 -5.565874e-03
 [981] 2.813457e-03 5.628337e-03 6.169630e-04 -6.726804e-03 8.271577e-03
 [986] -9.321087e-03 -7.113238e-03 -4.612192e-03 -1.455680e-03 -2.542697e-03
 [991] 3.903765e-03 8.153303e-03 -2.999027e-03 -2.017756e-02 1.040203e-02
 [996] 1.612374e-02 6.382632e-03 -2.657759e-02 -8.820136e-03 5.178687e-03
 [ reached getOption("max.print") -- omitted 142 entries ]
> LjungBoxTest(rfit, lag.max = 20)
 m Qm pvalue
 1 0.01 0.9242838
 2 1.39 0.4982003
 3 1.55 0.6707107
 4 2.27 0.6862418
 5 2.31 0.8054475
 6 2.94 0.8160434
 7 3.05 0.8804417
 8 3.77 0.8774554
 9 3.94 0.9151753
 10 4.11 0.9424145
 11 4.28 0.9609451
 12 4.48 0.9731434
 13 4.52 0.9843480
 14 4.52 0.9914446
 15 5.92 0.9811324
 16 6.24 0.9852522
 17 6.30 0.9909058
 18 6.37 0.9944624
 19 6.38 0.9968550
 20 6.86 0.9971328
rdaxfore <- forecast(armafit,level = 0.95)
> rdaxfore
 Point Forecast Lo 95 Hi 95
1143 -0.0013155380 -0.02468254 0.02205146
1144 -0.0012442405 -0.02463281 0.02214433
1145 -0.0011768071 -0.02458465 0.02223104
1146 -0.0011130283 -0.02453810 0.02231204
1147 -0.0010527061 -0.02449318 0.02238777
1148 -0.0009956532 -0.02444990 0.02245859
1149 -0.0009416923 -0.02440825 0.02252486
1150 -0.0008906559 -0.02436822 0.02258691
1151 -0.0008423855 -0.02432979 0.02264502
1152 -0.0007967312 -0.02429293 0.02269947
> plot.rdaxfore
Error: object 'plot.rdaxfore' not found
> accuracy(armafit)
 ME RMSE MAE MPE MAPE MASE ACF1
Training set -0.0001385744 0.01192216 0.00879015 NaN Inf 0.7237593 0.002808659
• Depois que escolher o melhor modelo, faça a previsão ex-ante
para 6 períodos à frente.
> rdaxfore <- forecast(armafit,level = c(0.95), h=6)
> rdaxfore
 Point Forecast Lo 95 Hi 95
1143 -0.0013155380 -0.02468254 0.02205146
1144 -0.0012442405 -0.02463281 0.02214433
1145 -0.0011768071 -0.02458465 0.02223104
1146 -0.0011130283 -0.02453810 0.02231204
1147 -0.0010527061 -0.02449318 0.02238777
1148 -0.0009956532 -0.02444990 0.02245859
> plot(rdaxfore,main = "ex-ante")
• Discuta os resultados e mostre graficamente.