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RE: st: A cry for help on ARMA with weak autocorrelation
From
"Dmytro Andriychenko" <[email protected]>
To
<[email protected]>
Subject
RE: st: A cry for help on ARMA with weak autocorrelation
Date
Thu, 6 May 2010 15:34:17 +0100
Thank you ever so much for the reply. I understand about the ARCH model, but why did you try to fit a linear regression model(I mean reg dmytro)? What does it do?
Another thing: what is it that is sympthomatic of ARCH: is it the weak autocorrelation or just the pattern of actual values?
May I also ask if it is appropriate to do ARCH on the actual values as they stand (say as opposed to residuals from another model)?
Thanks again,
Kindest regards,
Dmytro
-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Tirthankar Chakravarty
Sent: Thursday, May 06, 2010 1:35 AM
To: [email protected]
Subject: Re: st: A cry for help on ARMA with weak autocorrelation
This is symptomatic of GARCH effects:
****************************************
clear*
input dmytro
.0070224
-.0397735
.0190506
.029408
-.0102329
end
g id = _n
tsset id
tsline dmytro
reg dmytro
estat archlm, lags(1(1)10)
arch dmytro, arch(1) garch(1)
****************************************
T
2010/5/6 Robert A Yaffee <[email protected]>:
> Dmytro,
> It sounds as if you have more noise than signal. If you cannot
> decompose that into any signal, you may merely have white noise.
> - Robert
>
>
> Robert A. Yaffee, Ph.D.
> Research Professor
> Silver School of Social Work
> New York University
>
> Biosketch: http://homepages.nyu.edu/~ray1/Biosketch2009.pdf
>
> CV: http://homepages.nyu.edu/~ray1/vita.pdf
>
> ----- Original Message -----
> From: Dmytro Andriychenko <[email protected]>
> Date: Wednesday, May 5, 2010 2:50 pm
> Subject: st: A cry for help on ARMA with weak autocorrelation
> To: [email protected]
>
>
>> Dear Statalist,
>>
>> I have been recently asked to fit a univariate model for a particular
>> stationary time series. I thought ARMA will be the obvious choice, but
>> when
>> I looked at the autocorrelation within the series, I found that the first
>> two lags are not significant and the few significant ones are only
>> marginally so (see corrgram output below).
>>
>> I guess I can still do the estimates, but I am very much wondering if
>> ARMA
>> is appropriate modeling technique here. Is it even valid? Portmanteau
>> statistics is not rejecting hypothesis of no autocorrelation and Q stats
>> suggest marginal significance at lag 3,5 and 7 in the first series.
>>
>> The question is: is it even appropriate to be building ARMA in the
>> light of
>> such weak autocorrelation, especially that the first two lags are not
>> significant? If ARMA is not appropriate, then what can it be?
>>
>> If anyone can help me with that, or better still point me towards a
>> reference that would explain that, I would very much extremely appreciate
>> that. I have been reading books on econometrics for over a week, but still
>> cannot conclusively answer the question.
>>
>> Thank you,
>>
>> Dmytro
>>
>> -1 0 1 -1
>> 0
>> 1
>> LAG AC PAC Q Prob>Q [Autocorrelation] [Partial
>> Autocor]
>> ----------------------------------------------------------------------------
>> ---
>> 1 -0.0516 -0.0516 1.3555 0.2443 |
>> |
>>
>> 2 0.0574 0.0551 3.0348 0.2193 |
>> |
>>
>> 3 -0.1253 -0.1209 11.062 0.0114 -|
>> |
>>
>> 4 -0.0248 -0.0401 11.377 0.0226 |
>> |
>>
>> 5 0.0887 0.1020 15.417 0.0087 |
>> |
>>
>> 6 0.0809 0.0808 18.785 0.0045 |
>> |
>>
>> 7 -0.1274 -0.1468 27.146 0.0003 -| -|
>>
>> 8 0.0455 0.0491 28.214 0.0004 |
>> |
>>
>> 9 -0.0718 -0.0235 30.882 0.0003 |
>> |
>>
>> 10 -0.0196 -0.0722 31.081 0.0006 |
>> |
>>
>> 11 0.0029 -0.0091 31.085 0.0011 |
>> |
>>
>> 12 -0.0930 -0.0818 35.588 0.0004 |
>> |
>>
>> 13 0.1613 0.1684 49.154 0.0000 |-
>> |-
>>
>> 14 -0.0064 -0.0050 49.176 0.0000 |
>> |
>>
>> 15 0.0465 0.0277 50.305 0.0000 |
>> |
>>
>> 16 0.0520 0.0951 51.726 0.0000 |
>> |
>>
>> 17 -0.0261 -0.0090 52.084 0.0000 |
>> |
>>
>> 18 0.0407 0.0249 52.955 0.0000 |
>> |
>>
>> 19 0.0720 0.0485 55.692 0.0000 |
>> |
>>
>> 20 -0.0093 0.0368 55.738 0.0000 |
>> |
>>
>> 21 0.0882 0.0593 59.865 0.0000 |
>> |
>>
>> 22 0.0209 0.0623 60.098 0.0000 |
>> |
>>
>> 23 -0.0231 -0.0031 60.381 0.0000 |
>> |
>>
>> 24 -0.0112 -0.0256 60.448 0.0001 |
>> |
>>
>> 25 -0.0611 -0.0094 62.445 0.0000 |
>> |
>>
>> 26 0.0820 0.0641 66.046 0.0000 |
>> |
>>
>> 27 -0.0818 -0.1022 69.64 0.0000 |
>> |
>>
>> 28 -0.0372 -0.0531 70.384 0.0000 |
>> |
>>
>> 29 -0.0148 0.0117 70.503 0.0000 |
>> |
>>
>> 30 -0.0195 -0.0182 70.708 0.0000 |
>> |
>>
>> 31 0.0606 0.0384 72.693 0.0000 |
>> |
>>
>> 32 0.0101 -0.0140 72.748 0.0001 |
>> |
>>
>> 33 0.0248 0.0807 73.083 0.0001 |
>> |
>>
>> 34 0.0049 -0.0336 73.096 0.0001 |
>> |
>>
>> 35 -0.0110 -0.0529 73.162 0.0002 |
>> |
>>
>> 36 -0.0420 -0.0467 74.129 0.0002 |
>> |
>>
>> 37 0.0684 0.0485 76.693 0.0001 |
>> |
>>
>> 38 0.0291 0.0632 77.159 0.0002 |
>> |
>>
>> 39 0.0517 -0.0230 78.631 0.0002 |
>> |
>>
>> 40 -0.0336 0.0225 79.255 0.0002 |
>> |
>>
>>
>>
>> The values are:
>>
>> -.0090714
>> .0218658
>> -.0268755
>> .0024567
>> -.056356
>> .0046611
>> .0136881
>> -.0091224
>> .0054574
>> -.0334902
>> .0212493
>> .0597358
>> -.0207405
>> .0116024
>> -.01581
>> -.0096569
>> .0243721
>> -.0002346
>> -.0107546
>> -.0070105
>> .0029306
>> .0054045
>> .0222607
>> .0032482
>> .033515
>> -.0261011
>> -.0244341
>> -.0354443
>> .0121222
>> .0120258
>> -.0312228
>> .0112433
>> .0132771
>> .0068617
>> .0016813
>> .0044956
>> -.0182991
>> -.0232587
>> .0172067
>> -.0174499
>> -.0107841
>> .019073
>> -.0025773
>> -.0036931
>> .0090313
>> .0116596
>> -.0042143
>> -.01231
>> -.0116882
>> -.0226994
>> -.0131874
>> .007977
>> -.05966
>> -.0327191
>> .0383449
>> -.0062823
>> .0268879
>> .0207028
>> .0112748
>> -.0086665
>> .0050945
>> .0044184
>> -.0026326
>> -.0121818
>> .0221472
>> -.0393658
>> -.0099735
>> -.0052757
>> -.0292039
>> .0091033
>> -.0250168
>> -.0004563
>> .027513
>> -.021317
>> -.0123415
>> .0211291
>> -.0212989
>> -.0510502
>> -.0655146
>> -.079906
>> .0951033
>> .0257664
>> .0244412
>> -.0225444
>> .0309162
>> -.0119662
>> .026412
>> .0141501
>> .0005832
>> -.016212
>> .0151157
>> -.0394745
>> .0161915
>> .0154595
>> .0185943
>> -.0217462
>> -.0145679
>> .0094967
>> -.0019608
>> -.0120802
>> .0098996
>> -.0255461
>> .0237536
>> .0244961
>> .0004768
>> -.0053186
>> .0042987
>> -.0058708
>> -.0125189
>> .0147271
>> -.015285
>> .0082312
>> -.005342
>> .0082111
>> -.009253
>> -.01542
>> -.0301108
>> -.0584188
>> -.0084252
>> .0072241
>> -.0106797
>> -.0837865
>> -.0313945
>> -.0242662
>> .0136309
>> .0507717
>> .0040598
>> .0164299
>> -.0355163
>> -.0292273
>> -.0222354
>> -.0383153
>> .0077167
>> -.027843
>> .0302272
>> .043324
>> -.015892
>> -.0109243
>> .0109863
>> .0109072
>> .019958
>> -.0000401
>> -.0357337
>> -.0340881
>> .0012894
>> -.0131588
>> .0413365
>> -.0064459
>> -.0354757
>> -.0530305
>> -.0156755
>> .0089307
>> .0016389
>> .0281925
>> -.0176201
>> -.0430017
>> .0250711
>> .0661936
>> -.0374131
>> .0256433
>> .0016427
>> .0218129
>> -.0025196
>> .0220518
>> .0072665
>> .0238113
>> -.0167165
>> .018806
>> .0283427
>> -.0035315
>> .0055637
>> -.0215859
>> -.0089717
>> .0117569
>> .0052133
>> .0135822
>> -.0033212
>> .0096278
>> .0253091
>> -.0016627
>> -.0127578
>> .0227208
>> -.0063972
>> .006104
>> -.0260959
>> .0258164
>> .0116844
>> .0090237
>> -.0258517
>> .0119371
>> .0197902
>> .0026026
>> -.0191984
>> .0068007
>> .0063615
>> -.0058165
>> .0127311
>> .0071321
>> .0144997
>> -.0052276
>> .0084658
>> -.0059638
>> -.0135465
>> .0038967
>> .0044174
>> .0219884
>> -.0048823
>> .0122457
>> -.0176673
>> -.009655
>> -.0123987
>> .0232635
>> .004787
>> .0067487
>> .0085082
>> -.0185409
>> -.0008988
>> -.0144238
>> -.002049
>> .0013633
>> .0054221
>> .0073538
>> .0035315
>> .0001254
>> -.0163507
>> -.0059991
>> -.0107484
>> -.0047631
>> .0170636
>> -.0178342
>> -.0078974
>> .0154333
>> .0259404
>> .0131297
>> .0016165
>> .0096965
>> -.0041585
>> .0171118
>> .0085721
>> -.0161495
>> -.0008807
>> .0023966
>> .0251546
>> .0112433
>> -.0052514
>> -.0034738
>> .0024099
>> -.0090661
>> .0025158
>> .0200453
>> .0044689
>> .0076365
>> -.0037117
>> -.0016336
>> .0056829
>> .022727
>> .0188918
>> .0005565
>> -.0095177
>> .0065622
>> -.0097098
>> -.0106926
>> -.0022764
>> -.0008583
>> .0134516
>> -.0193677
>> -.008615
>> -.0148244
>> .0210567
>> -.0056529
>> .0173368
>> .0061102
>> .00454
>> .0065217
>> .0098181
>> -.0000982
>> .0154285
>> .0129695
>> -.00073
>> .0021348
>> .0089025
>> .0067787
>> .0054498
>> -.0059829
>> -.0127592
>> .0177407
>> .0060458
>> .0085001
>> .0001955
>> .0115237
>> -.021904
>> -.0161366
>> -.0252199
>> .0126491
>> .0416818
>> .0083432
>> .0076814
>> .006319
>> .0036798
>> -.0017376
>> .0038514
>> .0128078
>> .0041885
>> .0190792
>> -.0025673
>> -.0047374
>> .0207295
>> -.0031738
>> .0021157
>> .0141172
>> .0022464
>> -.0001411
>> .0059633
>> .0192223
>> .0063477
>> -.0110016
>> .0098848
>> -.0019283
>> .0168991
>> -.016264
>> .0130329
>> -.0294342
>> -.0474505
>> .0242586
>> -.004715
>> -.0229926
>> -.0079083
>> .0155926
>> .0242987
>> .0081582
>> -.0317149
>> .0022745
>> .0402284
>> -.0121889
>> -.0115776
>> .0160389
>> -.0036221
>> .013381
>> -.0112391
>> .0025024
>> -.0076647
>> .0229626
>> .0084715
>> .0246611
>> -.000844
>> .0007362
>> -.0011082
>> .0119686
>> -.0007591
>> -.0114279
>> -.0122776
>> .0217314
>> .016614
>> -.0089483
>> .0057192
>> .000289
>> .0015287
>> .0005388
>> -.0017853
>> .0141611
>> .0119972
>> .0053654
>> -.0015335
>> -.0459242
>> .0222826
>> -.0173922
>> .0336294
>> -.004158
>> .0146761
>> .0085745
>> .0027933
>> -.0084667
>> .0272865
>> -.0069933
>> .0115929
>> -.0105085
>> .0153751
>> -.0298243
>> .0334148
>> -.025835
>> .0040855
>> .0145779
>> .0039845
>> -.0174904
>> -.0595789
>> .0040874
>> -.0296612
>> -.0002079
>> .0253992
>> .0157719
>> -.0175371
>> .0108528
>> .0232458
>> .0005913
>> .0209351
>> .0197239
>> -.0291605
>> .0194979
>> -.0176277
>> -.0376501
>> -.0035934
>> -.0084867
>> .0254431
>> .0140886
>> -.0237761
>> .0064907
>> .0073729
>> -.0218363
>> -.0263119
>> -.0443525
>> -.0044308
>> .0287313
>> -.0400453
>> .0019059
>> .0169611
>> .0000362
>> -.0302677
>> -.0127449
>> -.0253201
>> .037117
>> .0400047
>> -.0103674
>> .0268259
>> .0023079
>> .0210543
>> .0002432
>> .0138454
>> -.0347366
>> -.0052414
>> -.0239954
>> -.0180578
>> -.0313873
>> -.018117
>> -.0275869
>> -.0278697
>> .0277452
>> -.0048842
>> .0003047
>> .0267324
>> -.0051508
>> .0073652
>> .0230937
>> -.0676994
>> .027998
>> -.0175819
>> -.0480194
>> -.0234528
>> -.2254887
>> .0186381
>> -.050343
>> .1131096
>> .0031643
>> -.0352201
>> -.1120925
>> .1211257
>> -.0579996
>> .0575261
>> .0037999
>> -.0139828
>> .0747881
>> -.0212183
>> -.0686975
>> -.0238781
>> .0235171
>> .0349255
>> -.021409
>> -.0750003
>> -.0129738
>> -.0756612
>> .0597296
>> .0227227
>> .0146079
>> .0395327
>> -.0081658
>> .0301604
>> .0145698
>> .0219765
>> .0479522
>> -.0284438
>> .0047235
>> .0110078
>> .0070996
>> 9.06e-06
>> -.0253553
>> -.0203786
>> -.0011497
>> -.0259624
>> .059896
>> .0423455
>> .0072837
>> .0299325
>> -.0012712
>> .0270276
>> .0129409
>> -.0113106
>> .0352964
>> .0290713
>> -.0188484
>> -.0181832
>> .0361772
>> .0055947
>> .0070224
>> -.0397735
>> .0190506
>> .029408
>> -.0102329
>>
>>
>>
>> *
>> * For searches and help try:
>> * http://www.stata.com/help.cgi?search
>> * http://www.stata.com/support/statalist/faq
>> * http://www.ats.ucla.edu/stat/stata/
> *
> * For searches and help try:
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>
--
To every ω-consistent recursive class κ of formulae there correspond
recursive class signs r, such that neither v Gen r nor Neg(v Gen r)
belongs to Flg(κ) (where v is the free variable of r).
*
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