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10951 10
2019-06-21
数据如下,有多个id,每个id有多个年月的数据,现在我想对每36个月的数据进行滚动回归:reg r1 riskpre s h,然后提取回归的截距项,请问该如何实现呢?代码应该怎么写呢?

* Example generated by -dataex-. To install: ssc install dataex
clear
input str6 id int date float(month r1) double(riskpre s h)
"000001" 16860 553  .014094  .036575 -.009702  .000703
"000001" 16891 554  .048357  .015575 -.010818   -.0072
"000001" 16919 555  .171182  .118575  -.05408  .035216
"000001" 16952 556  .167908  .175575  .119062 -.013383
"000001" 16982 557  .019099  .037575  .053433 -.008172
"000001" 17013 558 -.060051 -.056425  .048721 -.009608
"000001" 17044 559 -.007551    .0265  .001268 -.022068
"000001" 17074 560  .088243    .0445  .027422 -.031225
"000001" 17105 561  .007703    .0255 -.049526  .037411
"000001" 17135 562  .146581    .1315 -.132637  .006661
"000001" 17166 563   .14491    .2235 -.097754 -.002073
"000001" 17197 564   .07704    .0925   .06739 -.002018
"000001" 17225 565  .034486    .0645  .101705  .035859
"000001" 17256 566  .051416   .11135  .110285   .00374
"000001" 17286 567  .224213   .22435  .046436  .052993
"000001" 17317 568  .120223  .077275   -.0258 -.014164
"000001" 17347 569  .002479 -.082725 -.113558 -.097157
"000001" 17378 570     .153   .17905  .082684  .013097
"000001" 17409 571  .155778  .167825  -.03319  .001608
"000001" 17439 572  .035816    .0466 -.017388  .043838
"000001" 17470 573   .00484    .0546 -.128444  -.03629
"000001" 17500 574 -.131055   -.1364  .091215  .008438
"000001" 17531 575  .126657  .082225  .064503  .008662
"000001" 17562 576 -.069271 -.158775  .071419  -.02444
"000001" 17591 577  .002497  .015225  .084746  .027775
"000001" 17622 578 -.121141 -.193775  .004756 -.037009
"000001" 17652 579 -.007265  .051225 -.095481  -.02018
"000001" 17682 580 -.034113 -.084775  .045018  .045009
"000001" 17713 581 -.115162 -.216775  -.03627 -.015263
"000001" 17744 582  .015988  .020225  .087876  .002494
"000001" 17773 583 -.112924 -.150775 -.088313  .030025
"000001" 17805 584 -.063161 -.071775  -.03067  .038559
"000001" 17836 585 -.191622   -.2624  .010838  .030914
"000001" 17864 586  .082047   .11235  .095303 -.016304
"000001" 17897 587  .025322 -.006425  .075216  -.03906
"000001" 17920 588  .068734  .110575  .040809 -.017948
"000001" 17955 589  .008822  .050575  .045556 -.017867
"000001" 17987 590  .136349  .162575  .075964 -.051336
end


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2019-6-22 01:38:24
请将问题表述清楚一些,然后help dataex输出数据
方便人回答^_^
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2019-6-22 15:22:26
ritaing 发表于 2019-6-22 01:38
请将问题表述清楚一些,然后help dataex输出数据
方便人回答^_^
抱歉!没表述清楚......是这样的,我的数据有多家公司(用id表示),每家公司有不同年月的收益率(收益率用r1表示),每个年月对应三个因子数据(riskpre SMB HML),现在我想以r1为因变量,riskpre SMB HML为自变量,对每家公司的数据进行滚动回归,区间为36个月,即先对第1~36月的数据进行回归,得到截距项;再对第2~37月的数据进行回归,得到截距项;对第3~38月的数据进行回归,得到截距项......如此滚动上百次,将每次回归的截距项提取出来,请问代码该怎么写呢?

* Example generated by -dataex-. To install: ssc install dataex
clear
input str6 id int date float r1 double(riskpre SMB HML)
"000001" 16860  .014094  .036575 -.009702  .000703
"000001" 16891  .048357  .015575 -.010818   -.0072
"000001" 16919  .171182  .118575  -.05408  .035216
"000001" 16952  .167908  .175575  .119062 -.013383
"000001" 16982  .019099  .037575  .053433 -.008172
"000001" 17013 -.060051 -.056425  .048721 -.009608
"000001" 17044 -.007551    .0265  .001268 -.022068
"000001" 17074  .088243    .0445  .027422 -.031225
"000001" 17105  .007703    .0255 -.049526  .037411
"000001" 17135  .146581    .1315 -.132637  .006661
"000001" 17166   .14491    .2235 -.097754 -.002073
"000001" 17197   .07704    .0925   .06739 -.002018
"000001" 17225  .034486    .0645  .101705  .035859
"000001" 17256  .051416   .11135  .110285   .00374
"000001" 17286  .224213   .22435  .046436  .052993
"000001" 17317  .120223  .077275   -.0258 -.014164
"000001" 17347  .002479 -.082725 -.113558 -.097157
"000001" 17378     .153   .17905  .082684  .013097
"000001" 17409  .155778  .167825  -.03319  .001608
"000001" 17439  .035816    .0466 -.017388  .043838
"000001" 17470   .00484    .0546 -.128444  -.03629
"000001" 17500 -.131055   -.1364  .091215  .008438
"000001" 17531  .126657  .082225  .064503  .008662
"000001" 17562 -.069271 -.158775  .071419  -.02444
"000001" 17591  .002497  .015225  .084746  .027775
"000001" 17622 -.121141 -.193775  .004756 -.037009
"000001" 17652 -.007265  .051225 -.095481  -.02018
"000001" 17682 -.034113 -.084775  .045018  .045009
"000001" 17713 -.115162 -.216775  -.03627 -.015263
"000001" 17744  .015988  .020225  .087876  .002494
"000001" 17773 -.112924 -.150775 -.088313  .030025
"000001" 17805 -.063161 -.071775  -.03067  .038559
"000001" 17836 -.191622   -.2624  .010838  .030914
"000001" 17864  .082047   .11235  .095303 -.016304
"000001" 17897  .025322 -.006425  .075216  -.03906
"000001" 17920  .068734  .110575  .040809 -.017948
"000001" 17955  .008822  .050575  .045556 -.017867
"000001" 17987  .136349  .162575  .075964 -.051336
"000001" 18017  .067147  .045575  .034073  .014925
"000001" 18044   .03534  .051575  .030208  .003847
"000001" 18078  .104957  .135575 -.091759 -.016677
"000001" 18109  .127733  .164575 -.031906  .021235
"000001" 18140 -.207425 -.219425  .061762 -.023972
"000001" 18170  .067721  .050575 -.025297 -.016304
"000001" 18200  .078669  .086575  .032472 -.003578
"000001" 18231  .071341  .074575   .08275  .003528
"000001" 18262 -.000156  .030575  .012538  .025173
"000001" 18291 -.055753 -.090425  .072026 -.018919
"000001" 18319  .019166  .023575  .065067 -.019494
"000001" 18352  .012421  .023575  .021798 -.005504
"000001" 18382 -.041756 -.079425  .008749 -.019223
"000001" 18413 -.054996 -.085425  .003087 -.002986
"000001" 18443 -.033994 -.077425 -.024001  .003928
"000001" 18473  .071036  .114575  .042515 -.026854
"000001" 18505  .032405  .013575  .087313 -.075616
"000001" 18535   .01529  .009575  .000901 -.044449
"000001" 18564  .043494  .119408 -.041887  .013824
"000001" 18596  .004414 -.049592  .056424 -.035434
"000001" 18627   .00699 -.007875 -.007332  .015335
"000001" 18658  -.01911 -.017875 -.028295   .04089
"000001" 18686   .05561  .043833  .064226 -.030131
"000001" 18717 -.043971  .001833   .01064  .008039
"000001" 18746 -.027162 -.010375 -.024443  .003981
"000001" 18778 -.054655 -.063375  -.01172  .002114
"000001" 18808  .013656  .020625  .021925 -.016578
"000001" 18837 -.010458 -.017583  .031034 -.044861
"000001" 18870 -.036032 -.049583  .018516 -.012194
"000001" 18900 -.075987 -.086583  -.02658  .036443
"000001" 18931   .02122  .045417 -.009817  .023869
"000001" 18961 -.038741 -.053583   .01112 -.014629
"000001" 18992 -.103155 -.064583 -.100993  .078564
"000001" 19023 -.010145  .033417 -.041265 -.007071
"000001" 19052  .057284  .061417  .061752 -.035422
"000001" 19083 -.048608 -.068583  .000601  .011932
"000001" 19110  .041344  .050417  .017014 -.020843
"000001" 19144  .021661 -.006583  .016148  -.02016
"000001" 19174 -.030245 -.047375 -.013416  .012482
"000001" 19205 -.042465 -.055167 -.048085  .008125
"000001" 19236 -.026211 -.025167  .077211 -.009528
"000001" 19266  .025203  .018833 -.022034 -.020546
"000001" 19297 -.005283 -.009167  .016063   .00764
"000001" 19327   -.0549 -.053167 -.062844  .049476
"000001" 19358   .11292  .144833  .011474  .020982
"000001" 19389  .050864  .050833  .029558  .014323
"000001" 19417   .01552 -.008167  .046338 -.013598
"000001" 19448 -.010986 -.052167  .026283 -.011905
"000001" 19474 -.011045 -.024167 -.010315  .011247
"000001" 19509  .078455  .066833  .086174 -.024026
"000001" 19539 -.083401 -.131167 -.031212   .00577
"000001" 19570  .037528  .021833  .056314  .002367
"000001" 19600   .01604  .045833  .054832   .00036
"000001" 19631  .048206  .036833   .01293  .033868
"000001" 19662 -.027767 -.019167 -.006769  .020912
"000001" 19691   .02054  .039833  .049459  .005128
"000001" 19723 -.021217 -.044167  .004934  .003458
"000001" 19753 -.004654 -.030167  .066738  .019184
"000001" 19782 -.006457  .008833  .036368  .003771
"000001" 19813 -.052337 -.019167 -.007871   .00388
"000001" 19843 -.008362 -.008167 -.013466 -.001654
"000001" 19873  .003231  .011833  .018031  .002149
"000001" 19904  .013912  .022833  .033131 -.000557
"000001" 19935  .016415  .084833 -.000125   .01633
"000001" 19964  .019685  .008833  .062478 -.028451
"000001" 19996  .083921  .068833  .105106 -.021968
"000001" 20027  .006022  .020833  .001645  .013502
"000001" 20055  .027611  .099042 -.039925  .048569
"000001" 20088 -.000474  .175042 -.235818  .160519
"000001" 20118  .040014 -.000958   .05308 -.082967
"000001" 20146  .049573  .036042  .040994 -.047361
"000001" 20178  .166437   .14025  .110666 -.041366
"000001" 20208  .117452   .17525  .035606 -.000337
"000001" 20237  .170025  .060458  .241196 -.147872
"000001" 20269 -.144884 -.076333 -.048289  .087549
"000001" 20300 -.127134 -.146333 -.059522  .028096
"000001" 20331 -.098722 -.148125  .005223  .010289
"000001" 20361 -.022542 -.050125  .013906 -.007356
"000001" 20391  .061432  .131083  .108769 -.085249
"000001" 20422  .022806  .033083   .11568 -.029977
"000001" 20453  .020401  .033083  .071379 -.030819
"000001" 20482 -.223964 -.242917 -.065598  .057345
"000001" 20513 -.035034 -.026917 -.000701  .015814
"000001" 20544  .078349  .134083  .064168 -.061516
"000001" 20573 -.026381 -.021917  .034052  .001917
"000001" 20605  -.00789 -.002917 -.030435  .003401
"000001" 20635  .017689  .021083  .050193 -.012338
"000001" 20664  .004767  .015083 -.026012  .038566
"000001" 20697  .010142  .040083  .022926  .007594
"000001" 20727 -.012887 -.020917  .028981 -.001482
"000001" 20758  .012781  .027083  .017991  .005984
"000001" 20788 -.015583  .043083 -.007136  .023814
"000001" 20819 -.054233 -.048917  .017772  .019456
"000001" 20845  .001773  .013083 -.043792  .036533
"000001" 20878  .030094  .025083  .016278 -.000104
"000001" 20909  .023277 -.005917 -.021367  .015441
"000001" 20937 -.006289 -.021917 -.049147  .034431
"000001" 20970 -.020909 -.010917 -.066299   .05227
"000001" 21000  .056015  .038083 -.010369 -.013342
"000001" 21031 -.015766  .033083 -.034617  .045636
"000001" 21062  .025448  .028083  .003494  -.01204
"000001" 21092   .01859  .005083  .002161 -.025099
"000001" 21123  .032339  .015083  -.05884 -.008669
"000001" 21153 -.049838 -.022917 -.050927   .03423
"000001" 21184   .02601  .003083 -.030003 -.005106
"000001" 21215  .006656  .050083 -.078864  .072665
"000001" 21243 -.025744 -.062917  .000953 -.019362
"000001" 21274 -.017279 -.020917  .064936 -.060283
"000001" 21301 -.025164 -.033917 -.008043  .014989
"000001" 21335  .019685 -.001917 -.024891 -.007945
"000001" 21365 -.059607 -.078917 -.035656  .029824
"000001" 21396 -.012572  .017083 -.015769  .029916
"000001" 21427 -.055542 -.053917 -.025413   .02519
"000001" 21457  .001712  .029083 -.041685  .017189
"000001" 21488 -.061326 -.081917 -.008425  .054078
"000001" 21518  .012594  .001083   .06526  -.04863
"000001" 21549 -.026064 -.043917  .001934  .006778
"000011" 16860 -.046876  .036575 -.009702  .000703
"000011" 16891  .109387  .015575 -.010818   -.0072
"000011" 16919  .193932  .118575  -.05408  .035216
"000011" 16952  .191368  .175575  .119062 -.013383
"000011" 16982  .107409  .037575  .053433 -.008172
"000011" 17013 -.016051 -.056425  .048721 -.009608
"000011" 17044  .042779    .0265  .001268 -.022068
"000011" 17074  .058723    .0445  .027422 -.031225
"000011" 17105  .035473    .0255 -.049526  .037411
end
format %td date
[/CODE]
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2019-6-22 16:06:33
请 ssc install rangestat,然后试试
复制代码
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2019-6-22 21:54:20
黃河泉 发表于 2019-6-22 16:06
请 ssc install rangestat,然后试试
啊,解决了!谢谢老师~
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2019-12-27 21:24:10
为什么我用这个方法滚动回归出来的截距项不同公司是不一样的,但每家公司每年的数据是一样的,你有这种情况吗
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