Hi statalisters
I am going to calculate the residuals from EGARCH model for each company to compute the standard deviation of residuals for each company (panel)
I have three time series independent variables. each is complete and consists of 200 observations and want to regress them against each panel from the dependent one (the dependent is panel 200 time points and 2088 firms". "looping using the same observations of the independent and use different panel for the dependent each time" In other words, I want to fix the same independent variables in all EGARCH and change only the dependent each time to use the observations of the dependent belong to the following panel and so on.
In other words, I want my first regression to be
arch returns mktrf SMB HML if id==1 , earch(1) egarch(1)
and the second one will be the same except using the returns of the second panel and the third will be the same except using the returns of the third panel and so on till i finish 2088 panels
here is a small sample if my data and the way of setting (i have time variable and panel variable)
input float(id returns SMB HML mktrf)
1 -11.151515 -2.2382624 .4518271 2.26
1 13.77899 2.3433826 -2.7514324 1.33
1 8.633094 1.106418 1.0299275 .73
1 -3.239741 5.333519 -3.702847 2.06
1 14.285714 2.911956 -2.739344 2.36
1 4.6875 -2.740549 -2.2713015 -1.14
1 10.541045 -5.820807 4.430209 -5.97
1 4.810127 2.9001956 -2.1319022 2.76
1 19.73684 -.007637183 -2.645491 5.02
1 3.296703 -1.50192 1.0523652 .86
1 -2.659574 -3.629962 .6442674 6.25
1 -.533333 3.467854 3.958202 -1.7
1 -1.608579 -.9766766 -2.865544 4.99
1 6.478873 -4.593571 4.96722 -.49
1 -18.414322 -1.555714 3.510212 -5.03
1 15.67398 -6.493771 .5108788 4.04
1 6.775068 9.918304 -5.239732 6.74
1 -5.181347 .5862162 -.8625144 4.1
1 -13.934426 -1.0128304 -.7239342 7.33
1 20.257235 7.398891 1.6254376 -4.15
1 28.475937 1.8310946 .756231 5.35
1 12.59105 -2.4508116 -1.2311492 -3.8
1 20.2 -6.336085 2.544591 2.98
1 -2.329451 -1.1205255 -.8665166 1.32
1 -8.517888 -3.0823665 -1.9120054 .15
1 -50.67505 .6439686 .3383765 7.03
1 -1.085418 -.15901716 -3.51255 4.76
1 -11.450382 -.9652972 2.1861134 .73
1 67.24138 -2.0155404 -.18698525 -3.07
1 -7.216495 -7.118085 -7.520288 3.18
1 21.52778 -7.961112 -1.7431357 -2.46
1 -13.900862 -6.341659 .5287399 -16.08
1 2.628285 .03358968 -8.834009 6.15
1 -19.14634 .4392631 6.046391 7.13
1 -19.332405 4.3881574 -3.8904605 6.1
1 -3.62069 -4.487304 -6.433276 6.16
1 -7.839721 2.0881655 -2.496774 3.5
1 14.859438 -5.334937 -2.721245 -4.08
1 .524476 -1.1243354 -8.81052 3.45
1 -4.695652 6.420864 6.709959 4.33
1 -25.36765 3.548169 6.949412 -2.46
1 20.93596 .8716612 -2.7120745 4.77
1 -19.34827 3.074622 -1.9390762 -3.47
1 -4.292929 -1.364687 -2.3041184 -1.38
1 26.91293 4.250344 -1.6836834 -2.81
1 19.95842 -3.0048516 -6.493091 6.13
1 7.279029 6.052834 -4.89089 3.37
1 15.831987 7.41185 -4.0126905 7.72
1 -1.312336 4.917301 -.56832767 -4.74
1 -33.59736 15.521524 -26.17497 2.45
1 -25.84493 -14.66277 12.607206 5.2
1 12.064343 -4.5761967 8.384338 -6.4
1 6.326034 1.9128653 .7734435 -4.42
1 -2.28833 7.752117 -19.764885 4.64
1 -9.601874 -1.572749 12.24717 -2.51
1 2.849741 .3939558 -5.97026 7.03
1 15.869018 4.4888024 2.4440646 -5.45
1 .869565 -.074298285 2.4448156 -2.76
1 37.284485 -1.5808455 12.828352 -10.72
1 18.053375 5.869763 9.916326 1.19
1 7.978723 -7.602592 18.7826 3.13
1 69.79866 6.394565 7.272977 -10.05
1 -43.2398 3.937033 10.12917 -7.26
1 -41.68207 3.4723265 -9.619989 7.94
1 6.022187 9.447039 -2.264044 .72
1 37.81764 7.157274 4.661578 -1.94
1 11.968562 -6.847993 1.0164733 -2.13
1 22.580645 1.4011184 3.2781196 -6.46
1 16.28788 -9.0615425 5.871483 -9.25
1 -7.491857 10.72014 -9.396211 2.46
1 -30.985914 4.033714 -1.7173657 7.54
1 -32.338306 7.563811 2.2184682 1.61
1 26.47059 -.06502911 .6993363 -1.44
1 -15.11628 -.14024942 .25148177 -2.29
1 -37.328766 7.827937 -.8366251 4.24
1 14.01093 8.333906 4.4294753 -5.2
1 -14.723927 -4.907973 1.3810486 -1.38
1 -20.56856 1.0251492 3.570562 -7.21
1 3.157897 -6.2574 -4.5322313 -8.18
1 -16.122448 -4.7151465 -.04583877 .5
1 -18.478258 1.6369543 -1.0011082 -10.35
1 10.399996 -4.0158134 -7.015924 7.84
1 8.212564 7.835046 3.058433 5.96
1 42.41072 -2.899629 4.6829357 -5.76
1 -6.269594 .6383933 -1.8447014 -2.57
1 -19.73244 -1.5701616 .16291857 -1.88
1 27.291664 1.9096388 -2.949774 1.09
1 -5.56465 5.120932 2.435094 8.22
1 -3.639515 10.16439 7.434109 6.05
1 -18.669127 1.9451013 -3.362454 1.42
1 2.500003 3.807448 2.913566 2.35
1 7.641919 .54233366 -.8440563 2.34
1 -20.081133 2.3345742 4.513561 -1.24
1 7.081213 1.5517427 .9360932 6.08
1 28.75 -2.666812 -2.1736033 1.35
1 -10.097087 4.843633 -.13474119 4.29
1 -8.639311 -1.550557 .3419315 2.15
1 -.945626 2.579258 2.579469 1.4
1 17.446299 -5.987915 -3.0824256 -1.32
1 5.669575 -2.1689422 .915616 -1.83
1 -5.576923 .4199519 1.672237 1.17
1 -4.887979 -7.464518 5.071144 1.86
1 19.999996 -.26883465 3.034544 -4.06
1 3.684211 3.882688 -.0016477555 .08
1 21.82741 2.049222 1.4188266 1.6
1 3.172414 3.611497 3.404722 1.43
1 9.2246 1.0382502 -1.2493355 4.54
1 -5.982903 -1.1211882 -.6879337 3.43
1 -19.261824 -1.627978 .9536579 -2.76
1 .857142 -2.8746696 1.870346 1.89
1 -12.889516 -3.647442 -1.4782875 -1.97
1 -.614446 4.657075 -2.0318992 -2.61
1 -3.400306 4.6846633 .9482778 3.65
1 -21.12 2.5839336 .018172503 .57
1 -8.519262 -.3889057 .9438565 3.92
1 -6.430165 .54952717 .100318 -1.22
1 1.470587 -.9305272 .17834795 .49
1 7.246382 1.9476655 -.09998143 -2.02
1 -6.081081 -.1999179 -.410763 3.61
1 -11.990407 6.839678 1.075318 -.25
1 -2.45232 .8020797 -.3807647 3.04
1 -.558659 2.469377 2.449507 -.3
1 -11.51685 .9582642 3.148264 1.46
1 16.190475 -3.2173 2.1402364 .73
1 -.819671 -1.8030342 .3235521 -3.57
1 -3.95778 -4.631225 2.728379 -.35
1 -6.868132 2.2796483 -1.4670253 -.78
1 20.353975 -2.725906 -.20239723 2.03
1 -5.637255 1.7066797 .18904495 1.84
1 -6.233767 .599547 .6288986 3.23
1 -.277008 -.6735392 3.231115 1.71
1 26.3889 -1.0619256 -2.151921 .87
1 2.1978 2.289512 .1979628 1.4
1 10.107522 .7639145 .3924535 -1.96
1 6.944443 -2.2187293 -2.6557 .68
1 -16.326525 -.3335389 2.1627197 3.49
1 13.52549 .3215615 .8441625 3.24
1 -7.617185 -3.5986836 -2.7400045 -1.96
1 -6.131077 1.9437873 -3.5308 -3.73
1 3.521118 .4436928 -3.8081694 .92
1 10.204088 .50304556 -6.715467 3.22
1 -13.991775 -3.019177 -1.8844032 1.8
1 2.23881 3.399432 -2.2837214 -4.83
1 -4.866181 -1.951408 4.897825 -.87
1 -1.023023 -2.1645489 3.858493 -6.36
1 1.033597 -.58827144 1.4677434 -3.09
1 3.069057 -.963577 1.0981948 -.93
1 16.129023 .8720689 -1.3873596 4.6
1 -11.752131 -2.82032 -1.7492063 1.86
1 -3.147702 4.32838 -1.423043 -8.44
1 -6.25 -1.0461148 1.7903104 -.77
1 39.15493 2.609858 .6448457 1.53
1 -1.214574 -4.756718 -4.847512 -9.24
1 -11.68033 4.7503633 -4.5612965 -17.23
1 4.872391 1.980261 1.5572448 -7.86
1 -8.628316 1.4519715 3.004251 1.74
1 -30.87886 -5.079965 -.6881678 -8.12
1 -30.39514 2.2454748 3.122322 -10.1
1 4.366819 4.833651 17.611708 8.95
1 5.439325 1.5190474 3.056315 10.19
1 -15.87302 3.729494 -3.7140646 5.21
1 -11.32075 3.2939785 -.4511137 .43
1 11.578943 -1.1098449 2.1283154 7.72
1 9.905663 2.8459246 2.0262146 3.33
1 17.167387 -5.586765 -2.2128682 4.08
1 -13.362067 -3.3826256 -2.0256305 -2.59
1 13.432835 4.803412 .7627878 5.56
1 3.555552 2.417136 1.284681 2.75
1 -7.112974 .9803599 3.361793 -3.36
1 39.18918 2.742736 .3258035 3.4
1 31.06797 4.6609044 .08148906 6.31
1 5.10949 -.4494575 .13221025 2
1 9.490737 .3496032 -2.592491 -7.89
1 -20.295984 -.14834166 1.549809 -5.56
1 15.384613 -2.9768155 -3.2034464 6.93
1 20.22989 2.360508 -1.794295 -4.77
1 -1.720844 1.5017577 -.2301898 9.54
1 43.38522 3.774201 -.16986275 3.88
1 1.763909 3.5581725 .24109125 .6
1 -1.062422 -2.632218 .6285104 6.82
1 1.059602 2.5636685 .6942521 1.99
1 .524246 2.531797 -1.34741 3.49
2 5.714286 1.444051 -2.716812 .45
2 6.081081 -1.0350094 .7011179 2.9
2 -16.56051 -1.1485633 -.6427278 -1.27
2 5.511811 -3.619072 -4.48918 -1.75
2 2.238806 -4.964158 -.2380595 -2.36
2 18.978102 -4.0486846 -3.153793 -5.99
2 20.253164 3.105765 .9798808 -7.59
2 -7.894737 -.8387822 -.1582913 11.35
2 -5.780347 -.27420163 3.400982 -.28
2 3.384615 2.2958205 3.9887905 .74
2 -4.166667 -2.005987 -4.599459 5.05
2 14.906832 -.7256613 -2.1968036 4.42
2 -10.659898 -1.8026018 -1.478053 3.11
2 -38.63636 .6443136 -3.1114945 -.85
2 16.990292 3.7809606 -1.8170675 -6.19
2 -7.053942 -4.1107845 1.3724067 3.89
2 -28.57143 -.4606912 -.17814445 .79
2 -10.027473 1.826555 -1.603779 2.55
2 24.58015 -2.355324 4.4000816 2.73
2 11.764706 -.7175763 1.90101 -1.76
2 -24.561403 2.508785 3.514937 .78
2 -16.27907 .986661 4.834257 1.18
2 -27.77778 -.17691155 2.8120005 5.57
2 11.538462 .7742693 -.3653766 1.29
2 -1.39211 -1.860084 .4619933 4.03
2 -16.470589 2.489413 .6899269 1.56
2 5.633804 2.488582 1.417376 2.8
2 -.319484 2.0626495 -2.646436 -1.2
2 -29.038465 -.7213553 -2.5282695 5.65
2 1.355019 2.5901675 -.04507709 -2.71
2 27.005344 -4.908375 3.392666 3.77
2 -14.526314 1.2144206 -1.6199777 4.18
2 .57471 -1.4248588 .4068598 3.12
2 29.71429 .4787387 -1.1549063 2.81
2 -14.34865 .03978141 .7793741 -3.32
2 -16.01763 -1.5590897 6.325492 4.65
2 -3.937008 -4.840122 3.839979 .43
2 -25.08196 -1.4510443 -.11438549 -.19
2 -28.371096 4.275532 -2.480185 2.06
2 -.903614 -6.117807 .9007202 2.61
2 6.534959 1.0155158 -.6752317 -2.04
2 12.60053 -3.811473 -.6703405 4.23
2 -7.142851 .04083993 -.0018862616 -1.97
2 14.884618 -.02555931 -.011580653 2.52
2 -24.785187 .016534345 .020916123 2.55
2 -30.860535 .01436003 -.035370424 -.06
2 8.583693 -.015908575 -.03394542 -3.11
2 22.33202 .02553672 -.008388526 6.13
2 13.276835 -.04274475 .003459619 -1.12
2 -10.699583 -.005744055 -.0113133 .59
2 3.686632 .026743596 -.016615406 1.36
2 -1.200002 -4.5039024 -1.9399352 -1.53
2 -18.758434 .5600551 2.682251 1.54
2 -1.495009 -1.77611 4.6925716 -6.04
2 1.180433 .20604737 -3.355757 -3.07
2 8.611107 4.80538 -.007307068 7.75
2 -2.813295 -2.2386727 1.26762 .56
2 12.47369 . . -2.17
2 10.76924 . . .
2 -14.062507 . . .
2 1.464651 . . .
2 -15.928326 . . .
2 -4.558902 . . .
2 17.639511 . . .
2 -8.342425 . . .
2 -14.515168 . . .
2 10.297165 . . .
2 14.285713 . . .
2 -.493422 . . .
2 20.716255 . . .
2 -12.140574 . . .
2 4.727272 . . .
2 22.69364 . . .
2 -18.053886 . . .
2 -1.668294 . . .
2 12.906313 . . .
2 -7.324307 . . .
2 -19.73504 . . .
2 -12.122938 . . .
2 -9.002587 . . .
2 7.943261 . . .
2 1.590592 . . .
2 3.403676 . . .
2 -39.69717 . . .
2 3.711792 . . .
2 28 . . .
2 -1.292406 . . .
2 16.612108 . . .
2 -23.7193 . . .
2 -11.585364 . . .
2 9.517242 . . .
2 -23.27366 . . .
2 -22.97297 . . .
2 28.46004 . . .
2 6.373294 . . .
2 -.860831 . . .
2 4.341537 . . .
2 0 . . .
2 13.45354 . . .
2 12.836176 . . .
2 -4.442035 . . .
2 23.92291 . . .
2 3.385177 . . .
2 -7.079648 . . .
2 28.26087 . . .
2 -3.601697 . . .
2 13.99268 . . .
2 -12.911392 . . .
2 -8.793605 . . .
2 17.928288 . . .
2 -14.932432 . . .
2 24.78157 . . .
2 68.11971 . . .
2 8.900926 . . .
2 11.904764 . . .
2 -9.36805 . . .
2 71.513664 . . .
2 -.858022 . . .
2 -5.99369 . . .
2 -4.170665 . . .
2 -1.400704 . . .
2 12.270583 . . .
2 -15.133114 . . .
2 -23.004955 . . .
2 16.29736 . . .
2 -4.056551 . . .
2 -7.751442 . . .
2 32.777786 . . .
2 22.50388 . . .
2 5.089292 . . .
2 25.27612 . . .
2 3.085791 . . .
2 7.358491 . . .
2 11.306387 . . .
2 15.026313 . . .
2 -23.71111 . . .
2 32.420097 . . .
2 2.781607 . . .
2 19.324535 . . .
2 8.434864 . . .
2 -4.165946 . . .
2 -12.770556 . . .
2 18.61042 . . .
2 26.88284 . . .
2 -6.456422 . . .
2 7.585417 . . .
2 6.727578 . . .
2 5.038911 . . .
2 15.280607 . . .
2 26.25568 . . .
2 23.64289 . . .
2 -16.356394 . . .
2 -2.277118 . . .
2 -22.130066 . . .
2 -19.96619 . . .
2 6.991976 . . .
2 18.065147 . . .
2 -16.170567 . . .
2 -2.193385 . . .
2 -13.3433 . . .
2 -.184818 . . .
2 -.093525 . . .
2 -.083681 . . .
2 -.088115 . . .
2 .039577 . . .
2 -.102724 . . .
2 -.084974 . . .
2 -.133518 . . .
2 -.10471 . . .
2 -32.58197 . . .
2 4.3313046 . . .
2 -13.204746 . . .
2 -12.90043 . . .
2 -9.343942 . . .
2 -4.7149158 . . .
3 10 . . .
3 -17.045456 . . .
3 42.46575 . . .
3 0 . . .
3 -14.018692 . . .
3 4.891304 . . .
3 18.134714 . . .
3 -9.649123 . . .
3 -15.929204 . . .
3 -9.473684 . . .
3 3.488372 . . .
3 0 . . .
3 -5 . . .
3 -1.265823 . . .
3 -5.194805 . . .
3 0 . . .
3 26.369864 . . .
3 -4.494382 . . .
3 -20 . . .
3 -2.985075 . . .
3 -30.76923 . . .
3 2.222222 . . .
3 17.045456 . . .
3 -25.24272 . . .
3 5.194805 . . .
3 -19.753086 . . .
3 -35.384617 . . .
3 30.95238 . . .
3 30.90909 . . .
3 39.44444 . . .
3 -17.928288 . . .
3 42.71845 . . .
3 -26.71233 . . .
3 -54.20561 . . .
3 -37.7551 . . .
3 27.272726 . . .
3 15.47619 . . .
3 -43.29897 . . .
3 16.363636 . . .
3 10.500002 . . .
3 76.92308 . . .
3 89.58334 . . .
3 -40.52198 . . .
3 13.163976 . . .
3 -57.64463 . . .
3 -13.658536 . . .
3 29.9435 . . .
3 -9.565219 . . .
3 -34.615383 . . .
3 -58.08824 . . .
3 78.94736 . . .
3 -30.40441 . . .
3 -4.208485 . . .
4 -8.898307 . . .
4 -39.6124 . . .
4 .598793 . . .
4 -16.097557 . . .
4 16.860462 . . .
4 10.199 . . .
4 -11.51241 . . .
4 3.316329 . . .
4 36.796 . . .
4 -41.0796 . . .
4 -6.832299 . . .
4 39.61605 . . .
4 -4.624999 . . .
4 17.265194 . . .
4 -14.321922 . . .
4 -2.810652 . . .
4 16.590557 . . .
4 9.170848 . . .
4 42.69275 . . .
4 -22.66129 . . .
4 -7.820646 . . .
4 24.77375 . . .
4 -14.687216 . . .
4 8.926676 . . .
4 15.60976 . . .
4 -17.066895 . . .
4 -12.511854 . . .
4 8.342367 . . .
4 -6.700001 . . .
4 7.482303 . . .
4 -12.417683 . . .
4 8.485499 . . .
4 218.01978 . . .
5 -13.56467 . . .
5 -16.423359 . . .
5 -36.24454 . . .
5 23.28767 . . .
5 8.333333 . . .
5 5.128205 . . .
5 -1.463415 . . .
5 7.978723 . . .
5 -27.5 . . .
5 14.94253 . . .
5 39 . . .
5 19.23077 . . .
5 -19.35484 . . .
5 -14.4 . . .
5 -16.82243 . . .
5 -25.8427 . . .
5 19.84436 . . .
5 -7.792208 . . .
5 10.56338 . . .
5 -13.375796 . . .
5 5.714286 . . .
5 29.054054 . . .
5 -20.95238 . . .
5 -28.91566 . . .
5 5.508475 . . .
5 -2.811245 . . .
5 -39.66942 . . .
5 -10.344828 . . .
5 -12.820513 . . .
5 -36.764706 . . .
5 -90.90909 . . .
5 37.5 . . .
5 -36.363636 . . .
5 42.85714 . . .
5 -7.200003 . . .
how can I sort this out?
I am going to calculate the residuals from EGARCH model for each company to compute the standard deviation of residuals for each company (panel)
I have three time series independent variables. each is complete and consists of 200 observations and want to regress them against each panel from the dependent one (the dependent is panel 200 time points and 2088 firms". "looping using the same observations of the independent and use different panel for the dependent each time" In other words, I want to fix the same independent variables in all EGARCH and change only the dependent each time to use the observations of the dependent belong to the following panel and so on.
In other words, I want my first regression to be
arch returns mktrf SMB HML if id==1 , earch(1) egarch(1)
and the second one will be the same except using the returns of the second panel and the third will be the same except using the returns of the third panel and so on till i finish 2088 panels
here is a small sample if my data and the way of setting (i have time variable and panel variable)
input float(id returns SMB HML mktrf)
1 -11.151515 -2.2382624 .4518271 2.26
1 13.77899 2.3433826 -2.7514324 1.33
1 8.633094 1.106418 1.0299275 .73
1 -3.239741 5.333519 -3.702847 2.06
1 14.285714 2.911956 -2.739344 2.36
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5 37.5 . . .
5 -36.363636 . . .
5 42.85714 . . .
5 -7.200003 . . .
how can I sort this out?
