A new day a new question. I have now done a rolling window regression according to CAPM model and thus determined my time series alphas and betas. Now I want to do the whole thing with the Fama French 3 Factor Model- The variables for smb and hml I have given. However, I want to keep the variables of alpha and beta from the CAPM model and generate new variables for alpha, beta 2 and beta 3, also for a period of 24 months. And after that I have to do this regression again with Carhart 4 factor Model and given MOM factor. An overall question I have is: Does the Alpha and Beta 1 change when applying the Fama French model or does it stay the same like in the CAPM model and only the new Betas are following? The goal in the end is to create mean Alphas divide them into Quintiles based on their Turnover Ratio to see if more active fonds perform better.
clear
input double portfolioid float mofd double(smb hml Alpha Beta)
4 439 .0231 -.0058 .0011276676681867825 1.2582311269663249
4 440 -.0079 -.0375 -.00066037569874813 1.4018742984812849
4 441 -.041100000000000005 .0479 -.003203570453383219 1.4122109199175594
4 442 -.036000000000000004 .0015 -.005067735517733929 1.355875609082542
4 443 .0308 .0101 -.004276204678426189 1.3299128910546867
4 444 -.015300000000000001 -.0236 -.00264340576862393 1.2650903114961072
4 445 -.026099999999999998 .0467 -.004977918697552257 1.3431614071668685
4 446 -.0033 .0385 -.0013603183772131176 1.2780154835862378
4 447 -.052000000000000005 -.0103 -.0020266099299921167 1.2059703395801908
4 448 .0483 -.0437 -.0011593780606042707 1.31435990940695
4 449 .015 .0076 -.0017615356820123058 1.3171521637192598
4 450 -.0252 -.0013 -.0024929980839788132 1.1887365089356519
4 451 .0735 .013600000000000001 .0028820224147934476 1.052381136162448
4 452 .0268 -.0022 .004593126737425821 1.107596270636486
4 453 -.0079 .022000000000000002 .003565814453837919 1.1359603071001119
4 454 -.0506 .0098 .0015064737708275246 1.1076438503130182
4 455 -.0239 .0382 -.001450077625743531 1.113812080451299
4 456 -.009300000000000001 -.020499999999999997 .0025399518285950835 1.1037358810718263
4 457 .0032 -.0091 -.00008314149448057293 1.0701662544985826
4 458 -.0101 .0125 -.00264706689732443 1.071068086961803
4 459 .0048 .0034000000000000002 -.0046777288729113395 1.0582751471024578
4 460 -.0354 .041299999999999996 -.00914245381680592 1.091173464905962
4 461 -.0313 -.0217 -.00700097423044709 1.0418785338348306
4 462 -.0492 -.011699999999999999 -.008433296568919339 1.0577201843378217
4 463 -.0574 .051699999999999996 -.013204861540199477 1.2129156439573077
4 464 -.002 -.038 -.014364183593742185 1.196618857079138
4 465 -.032 -.026699999999999998 -.015444051513141611 1.1553881750332935
4 466 .0116 -.0352 -.01279344256693269 1.212134473367146
4 467 -.0031 -.046799999999999994 -.009466272067912462 1.3071835246479455
4 468 .0087 -.055999999999999994 -.007383238950604474 1.3275470634435544
4 469 -.0558 .016200000000000003 -.006018720126566169 1.3215990484788809
4 470 -.0384 -.028900000000000002 -.006023297375925912 1.3569408906521836
4 471 .032 .023700000000000002 -.0032789059631669858 1.381550354500943
4 472 .0363 .026699999999999998 -.004582010000065449 1.359300783394689
4 473 .0348 -.04190000000000001 -.0033608506502379766 1.3781827796152266
4 474 .0222 .005 .0007751663600516108 1.3989994612642689
4 475 -.013000000000000001 -.0088 -.0004450044521979099 1.4382687226428141
4 476 .0315 -.029900000000000003 .0006037295772227964 1.4079304046767325
4 477 -.06860000000000001 -.0313 .0023284462734532926 1.435825313138035
4 478 .0796 -.0801 .009645787785370119 1.4936431929735288
4 479 .0724 -.094 .016357732373009762 1.6044313280489981
4 480 .0435 .0006 .01597773318892428 1.5946455737985565
4 481 .2232 -.1311 .027394798933897874 1.6992565318944537
4 482 -.16699999999999998 .0797 .022705446549832985 1.6150227037789622
4 483 -.0787 .0929 .02714756186533702 1.5311388726294246
4 484 -.050499999999999996 .0387 .02905797453659893 1.5113798309819366
4 485 .13720000000000002 -.1018 .0325332487512009 1.5407386848023146
4 486 -.0276 .0855 .03539859656314524 1.5129316398483346
4 487 -.009399999999999999 -.0129 .03952823818555333 1.4413293810263585
4 488 -.0194 .0682 .04010228565448254 1.508162664132336
4 489 -.036699999999999997 .047 .0395180477500601 1.7276303539624807
4 490 -.031200000000000002 .1229 .03805323807267757 1.8454745871451168
4 491 .015 .0611 .039059513800083615 1.8075571043821559
4 492 .0708 -.056600000000000004 .03618047031114062 1.7719855556708064
4 493 -.011699999999999999 .1391 .04044433959165882 1.6364718551310553
4 494 .0054 .0622 .04133914859278934 1.6409544591072212
4 495 .0024 -.0438 .041312379120544175 1.6210791411003753
4 496 .0305 .028300000000000002 .04032862324377629 1.5982747032873128
4 497 .064 -.022799999999999997 .039515050400760664 1.605425821043517
4 498 -.0415 .0556 .03921126931429379 1.6096129702114477
4 499 .0216 .032799999999999996 .037104918792983395 1.6387696597258556
4 500 -.0654 .0182 .036233238601829657 1.666017326014775
4 501 .06860000000000001 -.07150000000000001 .03443272530766962 1.650894618243433
4 502 .0040999999999999995 .0069 .02526996563362867 1.5044371281541726
4 503 .0513 .004699999999999999 .019073450673706516 1.3709393835160322
4 504 .0115 .0339 .018588612534819627 1.3731733858779236
4 505 -.016200000000000003 .038900000000000004 .007151904262588452 1.2501049977419219
4 506 .0431 .011200000000000002 .014357413609561769 1.3780569644227463
4 507 .059000000000000004 .0421 .014499444223885 1.3921632021599477
4 508 -.037000000000000005 .0255 .013921937092171734 1.3902319525124722
4 509 .0355 .015 .01271685737387346 1.3300269472123742
4 510 -.052199999999999996 -.0362 .012079164666963182 1.347059628385688
4 511 -.0226 .0229 .00716736984339204 1.246875507800501
4 512 .0275 .0131 .00788063315810916 1.176088227792914
4 513 -.0298 -.0645 .00681633879941004 1.1024467023764373
4 514 .032 -.0159 .006783476955592701 .9574366968811625
4 515 -.0045000000000000005 .0388 .0008174012149019787 .9282927484776891
4 516 .0139 -.008199999999999999 .00277341205796916 .9519475110158521
4 517 -.0027 -.014499999999999999 .0017975961479823905 .9865480266990998
4 518 .0073 -.0158 .002657955196104919 .9887523775601875
4 519 .0111 -.0009 .0009851211820280752 .9489484757852131
4 520 .048 .0009 .0048100191602722 1.009931924480321
4 521 .015 .0070999999999999995 .005723510274338288 1.0162651853427491
4 522 .0558 -.0204 .005084054580076671 1.0257052402606504
4 523 .0265 .0176 .0074259662326077325 .9974451764705381
4 524 .006 .009300000000000001 .01017841319013133 .9094270020647715
4 525 .028900000000000002 .0169 .011344522290153904 .9356177934221122
4 526 .0225 .0139 .0119847233815383 .9530052601641461
4 527 -.027999999999999997 .0278 .00846514544659567 .9041195373359033
4 528 .0263 .0166 .00872006067702675 .9031825818984502
4 529 -.011899999999999999 .0044 .007937297081933515 .8981742842069178
4 530 .019 -.0005 .008264231995338047 .9179754072471189
4 531 -.025699999999999997 -.0167 .002626290973518384 1.0048314540166439
4 532 -.0019 -.0026 .004769733071080048 1.0056063740699328
4 533 .023399999999999997 .0163 .004288828037580048 1.0288279960686055
4 534 -.0377 .045599999999999995 .0030103450348373043 1.0308271783454848
4 535 -.015700000000000002 .0124 .0010676980608890965 1.0389759514987018
4 536 .029300000000000003 .004699999999999999 -.00198054981620948 1.2362266866201386
4 537 .0039000000000000003 -.008199999999999999 -.0002576709104457238 1.3656707315021561
4 538 .041299999999999996 .0194 .001719370536849455 1.5219219722006376
end
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