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| From | "Dmytro Andriychenko" <dmytro@blueyonder.co.uk> |
| To | <statalist@hsphsun2.harvard.edu> |
| 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: 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 * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/