Hello,
I have to calculate the cost of equity capital based on fama and french 3 factor model. For this, I had a monthly data from Fama and french website (http://mba.tuck.dartmouth.edu/pages/....html#Research ) . I used rangestat command to calculate the market betas for the 3 factors as below
Then i caculated the monthly expected returns as
where
mkt, sb, and hl are calculated as
final data file looks like the one below.
the ce i got is the expected monthly return through 3-factor model. Now, i want to convert this variable into annual returns as i need the cost of equity on annual basis to merge it with another file. Problem is i donot know how to do it because of the following:
1. Fama and french factors (mktrf smb hml rf) are montly returns (this is what i understand) so the returns that i got are monthly (i beleive), then if i have to calculate the annual returns i should add these monthy returns, so
Otherwise, if i have to calculate cumulative returns then I did this
However, the results I get from these two are much higher to be the cost of equity capital and much different from the ce i calculated.
I do not know if I applied the rangestat correctly, or which method is the right one and if there is a mistake in my calculations. Any help in this regard is much appreciated.
regards,
I have to calculate the cost of equity capital based on fama and french 3 factor model. For this, I had a monthly data from Fama and french website (http://mba.tuck.dartmouth.edu/pages/....html#Research ) . I used rangestat command to calculate the market betas for the 3 factors as below
Code:
rangestat (reg) ret mktrf smb hml, interval(month -60 -1) by(permno)
Code:
gen ce=rf+mkt+sb+hl+ce
mkt, sb, and hl are calculated as
Code:
gen mkt=b_mktrf*mktrf gen sb=b_smb*smb gen hl=b_hml*hml
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input double(permno date) float month double ret float(year mktrf smb hml rf) double(reg_nobs b_mktrf b_smb b_hml b_cons) float(mkt sb hl ce returns) 10026 11353 1 .01587301678955555 1991 4.69 3.79 -1.84 .52 . . . . . . . . . 0 10026 11381 2 .375 1991 7.19 3.95 -.54 .48 1 . . . . . . . . 0 10026 11409 3 .05681818351149559 1991 2.65 3.89 -1.23 .44 2 . . . . . . . . 0 10026 11442 4 .19354838132858276 1991 -.28 .5 1.42 .53 3 . . . . . . . . 0 10026 11473 5 -.045045044273138046 1991 3.65 -.34 -.57 .47 4 . . . . . . . . 0 10026 11501 6 .07547169923782349 1991 -4.94 .07 1.21 .42 5 . . . . . . . . 0 10026 11534 7 .05263157933950424 1991 4.24 -.93 -1.25 .49 6 . . . . . . . . 0 10026 11564 8 -.07500000298023224 1991 2.32 1.59 -.78 .46 7 . . . . . . . . 0 10026 11595 9 0 1991 -1.59 1.63 -1 .46 8 . . . . . . . . 0 10026 11626 10 -.09909909963607788 1991 1.29 .9 -.43 .42 9 . . . . . . . . 0 10026 11655 11 -.03999999910593033 1991 -4.19 -.48 -1.93 .39 10 . . . . . . . . 0 10026 11687 12 .1875 1991 10.84 -2.24 -4.03 .38 11 . . . . . . . . 0 10026 11718 13 -.2017543911933899 1992 -.59 8.47 4.51 .34 12 . . . . . . . . 0 10026 11746 14 -.05494505539536476 1992 1.09 .88 6.37 .28 13 . . . . . . . . 0 10026 11778 15 .04651162773370743 1992 -2.66 -1.03 3.65 .34 14 . . . . . . . . 0 10026 11808 16 0 1992 1.07 -6.12 4.31 .32 15 . . . . . . . . 0 10026 11837 17 0 1992 .3 .39 1.28 .28 16 . . . . . . . . 0 10026 11869 18 -.15555556118488312 1992 -2.34 -3.09 3.4 .32 17 . . . . . . . . 0 10026 11900 19 .02631578966975212 1992 3.77 -.44 -.53 .31 18 . . . . . . . . 0 10026 11931 20 .025641025975346565 1992 -2.38 -.12 -1.03 .26 19 . . . . . . . . 0 10026 11961 21 -.08749999850988388 1992 1.19 .56 -.21 .26 20 . . . . . . . . 0 10026 11991 22 -.054794520139694214 1992 1.02 2.05 -2.1 .23 21 . . . . . . . . 0 10026 12022 23 .2028985470533371 1992 4.13 3.7 -1.48 .23 22 . . . . . . . . 0 10026 12053 24 -.1325301229953766 1992 1.53 1.64 2.52 .28 23 . . . . . . . . 0 10026 12082 25 .02777777798473835 1993 .93 2.03 5.87 .23 24 . . . . . . . . 0 10026 12110 26 .06756756454706192 1993 .12 -3.43 6.42 .22 25 . . . . . . . . 0 10026 12143 27 .17721518874168396 1993 2.3 .23 1.22 .25 26 . . . . . . . . 0 10026 12173 28 .19354838132858276 1993 -3.05 -.7 2.61 .24 27 . . . . . . . . 0 10026 12201 29 .06306306272745132 1993 2.89 1.96 -3.41 .22 28 . . . . . . . . 0 10026 12234 30 .12711864709854126 1993 .31 -.31 2.62 .25 29 . . . . . . . . 0 10026 12264 31 .04511278122663498 1993 -.34 .93 3.25 .24 30 . . . . . . . . 0 10026 12296 32 .12230215966701508 1993 3.71 .31 -.45 .25 31 . . . . . . . . 0 10026 12326 33 -.07692307978868485 1993 -.12 3.11 -.44 .26 32 . . . . . . . . 0 10026 12355 34 .0763888880610466 1993 1.41 1.45 -1.54 .22 33 . . . . . . . . 0 10026 12387 35 -.07741935551166534 1993 -1.89 -1.42 -.27 .25 34 . . . . . . . . 0 10026 12418 36 .1538461595773697 1993 1.65 1.22 .57 .23 35 . . . . . . . . 0 10026 12449 37 -.1090909093618393 1994 2.87 .15 2.09 .25 36 . . . . . . . . 0 10026 12477 38 .040816325694322586 1994 -2.55 2.73 -1.45 .21 37 . . . . . . . . 0 10026 12508 39 -.13071896135807037 1994 -4.78 -.98 1.29 .27 38 . . . . . . . . 0 10026 12537 40 -.07518796622753143 1994 .68 -.92 1.68 .27 39 . . . . . . . . 0 10026 12569 41 -.1869918704032898 1994 .58 -2.01 .2 .31 40 . . . . . . . . 0 10026 12599 42 .009999999776482582 1994 -3.03 -.45 1.69 .31 41 . . . . . . . . 0 10026 12628 43 0 1994 2.82 -1.72 .62 .28 42 . . . . . . . . 0 10026 12661 44 .019801979884505272 1994 4.01 1.34 -2.81 .37 43 . . . . . . . . 0 10026 12691 45 -.009708737954497337 1994 -2.31 2.83 -1.91 .37 44 . . . . . . . . 0 10026 12722 46 -.0882352963089943 1994 1.34 -2.35 -1.74 .38 45 . . . . . . . . 0 10026 12752 47 .05376344174146652 1994 -4.04 .26 -.94 .37 46 . . . . . . . . 0 10026 12782 48 -.051020409911870956 1994 .86 .04 .54 .44 47 . . . . . . . . 0 10026 12814 49 -.07526881992816925 1995 1.8 -2.65 .81 .42 48 . . . . . . . . .50427437 10026 12842 50 .075581394135952 1995 3.63 -.67 1.09 .4 49 . . . . . . . . .50427437 10026 12873 51 -.10270269960165024 1995 2.19 -.69 -1.1 .46 50 . . . . . . . . .50427437 10026 12901 52 .14457830786705017 1995 2.11 -.63 2.27 .44 51 . . . . . . . . .50427437 10026 12934 53 .021052632480859756 1995 2.9 -2.21 1.72 .54 52 . . . . . . . . .50427437 10026 12964 54 .04123711213469505 1995 2.72 2.93 -2.28 .47 53 . . . . . . . . .50427437 10026 12995 55 -.06930693238973618 1995 3.72 2.09 -1.67 .45 54 . . . . . . . . .50427437 10026 13026 56 .042553190141916275 1995 .55 1.59 2.71 .47 55 . . . . . . . . .50427437 10026 13055 57 -.040816325694322586 1995 3.35 -2.11 -.75 .43 56 . . . . . . . . .50427437 10026 13087 58 -.05319149047136307 1995 -1.52 -3.75 -.74 .47 57 . . . . . . . . .50427437 10026 13117 59 .10112359374761581 1995 3.96 -1.17 .95 .42 58 . . . . . . . . .50427437 10026 13146 60 -.10204081982374191 1995 1.03 .58 .87 .49 59 .011446257996319266 .0031083488575380336 .0007837813901823772 -.00017117708573134022 .011789645 .0018028422 .0006818898 .50427437 .50427437 10026 13179 61 .09090909361839294 1996 2.26 -2.62 .3 .43 60 .01141655651937715 .002967164165872884 .0006055615597711293 -.0019491555659077921 .02580142 -.00777397 .0001816685 .4482091 5.21823 10026 13208 62 -.010416666977107525 1996 1.33 1.88 -1.42 .39 60 .011900308081964553 .002763905517556863 .0003414133385293526 -.00025384844357286343 .01582741 .005196142 -.0004848069 .4105387 5.21823 10026 13237 63 0 1996 .73 1.31 1.01 .39 60 .007687146241300398 -.0012732620443929611 -.0005641615953833017 -.000563244623076835 .005611617 -.0016679732 -.00056980323 .3933738 5.21823 10026 13269 64 .031578946858644485 1996 2.06 4.91 -3.91 .46 60 .007529811550781114 -.001830991260804364 -.0004555116839428207 -.0011657622466918014 .01551141 -.008990167 .0017810507 .4683023 5.21823 10026 13300 65 .0714285746216774 1996 2.36 3.05 -1.2 .42 60 .0079407465432455 -.0018103854215813886 -.001229417435213649 -.0040901289992197176 .01874016 -.005521676 .001475301 .4346938 5.21823 10026 13328 66 -.12380952388048172 1996 -1.14 -3.58 1.56 .4 60 .008528617858535856 -.0014406584047278966 -.0014911112030403912 -.0023809649517397722 -.009722624 .005157557 -.0023261334 .3931088 5.21823 10026 13361 67 -.11413043737411499 1996 -5.97 -3.84 4.45 .45 60 .010950893763645197 -.000036063405052529525 -.0010928401485301793 -.00905351148931477 -.06537683 .00013848348 -.004863138 .3798985 5.21823 10026 13391 68 .0061349691823124886 1996 2.77 2.3 -.46 .41 60 .011317748034082701 .0003493341034354797 -.0011856636247659256 -.01015029636184068 .031350162 .0008034684 .00054540526 .44269904 5.21823 10026 13422 69 .04878048598766327 1996 5.01 -.88 -3.15 .44 60 .011489058119879785 .0005700755382551095 -.0013789715986972436 -.008938277046662259 .05756018 -.00050166645 .0043437607 .50140226 5.21823 10026 13453 70 .023255813866853714 1996 .86 -4.44 5.12 .42 60 .011658735162414474 .0004988506544728838 -.0011809599963711376 -.009664512139540274 .010026513 -.002214897 -.006046515 .4217651 5.21823 10026 13482 71 0 1996 6.25 -3.89 1.16 .41 60 .011786612659324326 .00039690356457086954 -.0010769792844097057 -.007566547962950346 .07366633 -.001543955 -.001249296 .4808731 5.21823 10026 13514 72 .22727273404598236 1996 -1.7 3.2 .89 .46 60 .011219465357253846 .00106821132613723 -.0011006322324798314 -.00820967580915348 -.01907309 .003418276 -.0009795626 .4433656 5.21823 10026 13545 73 -.03703703731298447 1997 4.98 -1.84 -1.65 .45 60 .0076026139279346 .004133372557213107 -.00009013771381250087 -.002937093672833596 .03786102 -.007605406 .00014872722 .4804043 5.417622 10026 13573 74 -.004807692486792803 1997 -.49 -2.9 5.2 .39 60 .0072888819067101875 .014147528188169979 .007218145173153877 -.003178988902958861 -.003571552 -.04102783 .03753435 .382935 5.417622 10026 13604 75 -.014492753893136978 1997 -5.02 -.38 3.81 .43 60 .00822528484509296 .016210580744074055 .010791101857272107 -.0037914964087542302 -.04129093 -.006160021 .0411141 .4236631 5.417622 10026 13634 76 0 1997 4.04 -5.65 -.07 .43 60 .008598203322921504 .016092811849285245 .010372286211103494 -.004782104727757051 .03473674 -.0909244 -.00072606 .3730863 5.417622 10026 13664 77 .11764705926179886 1997 6.74 4.89 -3.87 .49 60 .008792893989605711 .015567131985001415 .009501344270253377 -.00437628726046675 .0592641 .07612327 -.036770202 .5886172 5.417622 10026 13695 78 .07894736528396606 1997 4.1 1.33 1.23 .37 60 .009027231813392806 .01590567580172512 .009505501431766018 -.00392141456528047 .03701165 .02115455 .011691767 .439858 5.417622 10026 13726 79 .024390242993831635 1997 7.33 -2.8 .82 .43 60 .008451853366378093 .015213053258285246 .010019612082444994 -.001391448185985307 .06195208 -.04259655 .008216082 .4575716 5.417622 10026 13755 80 -.01587301678955555 1997 -4.15 7.31 1.38 .41 60 .008388208804159199 .015244734234995989 .010029202709099341 -.001476808380188186 -.03481107 .111439 .0138403 .50046825 5.417622 10026 13787 81 .04838709533214569 1997 5.35 2.61 .01 .44 60 .009825254035005768 .013310332592056901 .009817734347560427 -.005714941567701748 .05256511 .034739967 .00009817734 .52740324 5.417622 10026 13818 82 .04615384712815285 1997 -3.8 -.68 1.95 .42 60 .009401765847729109 .013037602862270936 .00932731768750297 -.00382576671540542 -.03572671 -.00886557 .01818827 .393596 5.417622 10026 13846 83 -.022058824077248573 1997 2.98 -4.95 .79 .39 60 .008462178030529215 .01298676259084703 .008596374054801691 .00009111926405636767 .02521729 -.06428447 .006791136 .35772395 5.417622 10026 13879 84 -.015037594363093376 1997 1.32 -2.35 3.45 .48 60 .00767323133133011 .011553202790176857 .008497483325831196 -.0011324868901720388 .010128666 -.027150026 .02931632 .4922949 5.417622 10026 13909 85 -.12977099418640137 1998 .15 -1.16 -1.45 .43 60 .008432652745646118 .013249059907109792 .0105114580691476 -.0003319728418594674 .001264898 -.01536891 -.015241615 .4006544 4.6049457 10026 13937 86 .09649122506380081 1998 7.04 0 -.13 .39 60 .009679829145056329 .01530102908887609 .014174554010816803 -.003626232315944637 .068146 0 -.001842692 .4563033 4.6049457 10026 13969 87 .25200000405311584 1998 4.76 -.93 1.05 .39 60 .00992897214478818 .01537481895289052 .013535235197958824 -.0036411039628239297 .04726191 -.014298582 .014211996 .4371753 4.6049457 10026 13999 88 -.00319488812237978 1998 .73 .2 .74 .43 60 .011079744984311066 .015113591077757081 .014139403395187693 -.004235085918772419 .008088214 .003022718 .010463159 .4515741 4.6049457 10026 14028 89 -.009615384973585606 1998 -3.07 -3.74 4.16 .4 60 .012434543834965582 .015058242565961697 .01293565080603436 -.009422668601833764 -.03817405 -.05631783 .05381231 .3593204 4.6049457 10026 14060 90 .08090614527463913 1998 3.18 -3.16 -2.33 .41 60 .01227249254358975 .014821326011025208 .0141162450830164 -.01002398609141457 .03902653 -.04683539 -.03289085 .3693003 4.6049457 10026 14091 91 -.07784431427717209 1998 -2.46 -5.12 -.96 .4 60 .011875289263169104 .012738680302744899 .010479468771873066 -.008216211789862399 -.02921321 -.06522204 -.01006029 .29550445 4.6049457 10026 14122 92 -.1818181872367859 1998 -16.08 -5.31 3.4 .43 60 .011474942846727836 .012055990030511035 .00957861893172194 -.007309859488132307 -.1845171 -.0640173 .032567304 .2140329 4.6049457 10026 14152 93 .1746031790971756 1998 6.15 -.14 -3.31 .46 60 .010373365855938203 .011557784845239817 .00927005949250417 -.007178185350153804 .0637962 -.00161809 -.030683896 .4914942 4.6049457 10026 14182 94 .21621622145175934 1998 7.13 -3.29 -2.21 .32 60 .010599836986073372 .011852870833005442 .007237313324441011 -.0023769650189052723 .07557684 -.03899594 -.015994463 .3405864 4.6049457 10026 14213 95 -.07222222536802292 1998 6.1 1.07 -3.15 .31 60 .011615376347231513 .00976441323594587 .005602760197684415 -.002002426278449248 .07085379 .010447923 -.017648695 .373653 4.6049457 10026 14244 96 .071856290102005 1998 6.16 -.35 -4.46 .38 60 .011083616097553841 .009593069876276507 .006630169213786634 -.0033149719985044856 .06827507 -.003357574 -.029570555 .41534695 4.6049457 10026 14273 97 .08379888534545898 1999 3.5 .37 -4.03 .35 60 .01097009973453511 .008733551926613651 .005374829835790114 -.004846160989898674 .03839535 .0032314144 -.021660564 .3699662 4.7597466 10026 14301 98 -.12886597216129303 1999 -4.08 -5.67 1.4 .35 60 .011523481211702859 .009301770918655345 .0061530297213067625 -.0017018709672941956 -.0470158 -.05274104 .008614241 .2588574 4.7597466 10026 14334 99 -.047337278723716736 1999 3.45 -3.93 -2.65 .43 60 .012140977552255948 .009330856072121621 .00686896805546518 -.004129815266759631 .04188637 -.036670264 -.018202767 .41701335 4.7597466 10026 14364 100 .08074533939361572 1999 4.33 4 2.53 .37 60 .011664151151841606 .00969045683031407 .007108625775940371 -.002520592684405517 .05050577 .03876183 .017984822 .4772524 4.7597466 end format %d date
the ce i got is the expected monthly return through 3-factor model. Now, i want to convert this variable into annual returns as i need the cost of equity on annual basis to merge it with another file. Problem is i donot know how to do it because of the following:
1. Fama and french factors (mktrf smb hml rf) are montly returns (this is what i understand) so the returns that i got are monthly (i beleive), then if i have to calculate the annual returns i should add these monthy returns, so
Code:
bys permno year: egen returns=total(ce)
Code:
bys permno : asrol ce, stat(product) add(1) window(month 12) gen(ce_cum)
I do not know if I applied the rangestat correctly, or which method is the right one and if there is a mistake in my calculations. Any help in this regard is much appreciated.
regards,
Comment