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Re: RE: st: A cry for help on ARMA with weak autocorrelation


From   Tirthankar Chakravarty <tirthankar.chakravarty@gmail.com>
To   statalist@hsphsun2.harvard.edu
Subject   Re: RE: st: A cry for help on ARMA with weak autocorrelation
Date   Fri, 7 May 2010 00:39:41 +0530

Dmytro,

You can fit an ARMA and a GARCH equation simultaneously in Stata 11.
*********************************
arch dmytro,arch(1) garch(1) ar(1) ma(1)
*********************************

T

2010/5/7 Dmytro Andriychenko <dmytro@blueyonder.co.uk>:
> Thank you ever so much again,
>
> Does it mean that I need to fit a suitable ARMA model first, save the
> residuals and then fit garch model on the residuals? What I cannot
> understand is how then I will be able to interpret any forecasts from garch-
> the garch model will only forecast the variance of the residuals, not the
> actual series? I am really puzzled with this...
>
> Please accept my apologies for taking your time with this, you are an
> absolute lifesaver!
>
> Thank you,
>
> Kindest regards,
>
> Dmytro
>
> -----Original Message-----
> From: owner-statalist@hsphsun2.harvard.edu
> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Robert A Yaffee
> Sent: Thursday, May 06, 2010 5:31 PM
> To: statalist@hsphsun2.harvard.edu
> Subject: Re: RE: st: A cry for help on ARMA with weak autocorrelation
>
> Dmytro,
>   The arch variance model is not robust to misspecification of the
> mean model.  That must be properly specified, as must the arma
> components if significant.
>   -  Cheers,
>          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 <dmytro@blueyonder.co.uk>
> Date: Thursday, May 6, 2010 10:35 am
> Subject: RE: st: A cry for help on ARMA with weak autocorrelation
> To: statalist@hsphsun2.harvard.edu
>
>
>> 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: owner-statalist@hsphsun2.harvard.edu
>> [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Tirthankar
>> Chakravarty
>> Sent: Thursday, May 06, 2010 1:35 AM
>> To: statalist@hsphsun2.harvard.edu
>> 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 <bob.yaffee@nyu.edu>:
>> > 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 <dmytro@blueyonder.co.uk>
>> > Date: Wednesday, May 5, 2010 2:50 pm
>> > Subject: st: A cry for help on ARMA with weak autocorrelation
>> > To: statalist@hsphsun2.harvard.edu
>> >
>> >
>> >> 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:
>> > *   http://www.stata.com/help.cgi?search
>> > *   http://www.stata.com/support/statalist/faq
>> > *   http://www.ats.ucla.edu/stat/stata/
>> >
>>
>>
>>
>> --
>> 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).
>>
>> *
>> *   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:
>> *   http://www.stata.com/help.cgi?search
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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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