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RE: RE: st: A cry for help on ARMA with weak autocorrelation
From
"Dmytro Andriychenko" <[email protected]>
To
<[email protected]>
Subject
RE: RE: st: A cry for help on ARMA with weak autocorrelation
Date
Thu, 6 May 2010 20:00:26 +0100
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: [email protected]
[mailto:[email protected]] On Behalf Of Robert A Yaffee
Sent: Thursday, May 06, 2010 5:31 PM
To: [email protected]
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 <[email protected]>
Date: Thursday, May 6, 2010 10:35 am
Subject: RE: st: A cry for help on ARMA with weak autocorrelation
To: [email protected]
> 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:
> > * 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
> * 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/
*
* 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/