Dear Stata community,

I am currently conducting an event study and I want to use SCARs for my univariate regression, however the coefficient I get when running the regression are rather large. I think something goes wrong with calculating the standard deviation (si) to calculate standardized abnormal returns (SAR), because the si seems rather small. The si I get when running the code below is: .0012519. Can someone take a look and see what is wrong with my code?

The data I am using is as follows:

Code:
* Example generated by -dataex-. To install: ssc install dataex
clear
input int eventtime float(firmid NR_MMM AR_MMM)
-171 1    -.02592428   -.0011417216
-170 1    .001208978   -.0021109781
-169 1     .01920737   .00023763232
-168 1   .0019564312  -8.431195e-06
-167 1    .014404905     .000799095
-166 1    .018414522    .0003734784
-165 1  -.0036540066   .00057500665
-164 1    .008071223    .0017457767
-163 1    .008860034   -.0003260339
-162 1    .000696554     .000740446
-161 1   .0012523525   -.0014783525
-160 1   -.006919197   -.0008798032
-159 1    -.00479183    .0004938302
-158 1     .01494759  -.00022159042
-157 1    .004575039   -.0011770388
-156 1   .0002386002   -.0009146002
-155 1   -.001468135    .0002941349
-154 1   -.005910488   -.0021195116
-153 1    .016738048    -.002780048
-152 1    .011091297   -.0015792975
-151 1  -.0019644196   -.0008685804
-150 1   -.002611002    -.001872998
-149 1    .011908351    .0017536485
-148 1 -.00048867875   -.0017213213
-147 1   -.004886649    .0008736486
-146 1    .011942647    .0005193526
-145 1   .0027169974    .0003920026
-144 1   -.003610632   .00021963214
-143 1   -.001176618  -.00022138184
-142 1  -.0003857905   6.790481e-06
-141 1   -.009943306    .0003263055
-140 1    .001489399    -.000199399
-139 1  -.0032908716   -.0008451284
-138 1   -.014146594   -.0003704057
-137 1   -.011339358     .001554358
-136 1    .014998026   -.0012430262
-135 1  -.0013854208  .000017420794
-134 1     .01626799   -.0009789907
-133 1  -.0011675397   .00017253975
-132 1   .0038084204   -.0007964204
-131 1   -.001280515     .000604515
-130 1   .0011978822    .0011741178
-129 1  -.0001648833    .0013298832
-128 1  .00056441315   .00021558686
-127 1   -.004716177     .000860177
-126 1    .010739258   -.0012152576
-125 1    -.01112652     .000397521
-124 1    -.01453394   .00020393883
-123 1    .020669995    -.004214995
-122 1   -.007085634    -.002709366
-121 1    -.00658128    .0004672795
-120 1   -.007841157     .001241157
-119 1   .0022358433  -.00018584334
-118 1    -.01962691  -.00022409014
-117 1    .004762659    -.003165659
-116 1    .010676718    .0006362817
-115 1    .014606647    .0002993528
-114 1   -.015206748    .0005917477
-113 1   -.017986748    .0029187484
-112 1    .007810976   -.0006589764
-111 1    .008859024 -.000020024383
-110 1    .012491385    .0011936155
-109 1   -.001647685    .0008166851
-108 1  -.0022327362   -.0010952638
-107 1    .010687814   -.0006668141
-106 1   -.007314611  -.00006138924
-105 1   -.009528726    .0013267263
-104 1   -.015472038    .0005720377
-103 1    .001994762   -.0005977621
-102 1   -.013263974  -.00055802567
-101 1   -.023941156  -.00001884448
-100 1   -.010967145   .00004214474
 -99 1   .0008256687    -.002541669
 -98 1    .007836194    -.001758194
 -97 1   -.025217174   -.0006418264
 -96 1    .016806642   -.0013456416
 -95 1    -.02182186   .00012485836
 -94 1   .0005018732    -.002919873
 -93 1     -.0118306     .001221599
 -92 1    .005205482    .0004795182
 -91 1     .02042589    .0020711122
 -90 1   -.015808947   -.0008870526
 -89 1    .014232416    .0017055843
 -88 1   -.010992362   .00043836216
 -87 1     .00554239   -.0004623905
 -86 1    .024940867    -.000371867
 -85 1  -.0004816178   .00012261781
 -84 1   -.018940987   -.0010710129
 -83 1    .005000714    .0007582858
 -82 1   .0015055384    .0021454617
 -81 1   -.018676706   -.0009412944
 -80 1   -.014312023   -.0026449766
 -79 1  -.0007045424   -.0023594575
 -78 1  -.0002254058    .0004864058
 -77 1   -.012442886    .0004638859
 -76 1    .019653216     .000492784
 -75 1    .016626082    .0010589176
 -74 1     .01658876    .0015292395
 -73 1   -.004741395    .0005343949
 -72 1 -.00006098628   -.0001660137
end
With the following code:

Code:
quietly describe
bys eventtime: gen N = _N

preserve
 drop if eventtime>-11
 collapse  (sd) AR_MMM,by(firmid)
 rename AR_MMM si
 keep firmid si
 save "M:\tmp"
 restore
 
 merge m:1 firmid using "M:\tmp"
 erase "M:\tmp.dta"
 
 drop if eventtime <-2
 drop if eventtime >2

 gen SAR = AR_MMM/si

    sort firmid eventtime
    by firmid: gen CSAR_MMM = sum(SAR)

collapse CSAR_MMM, by(eventtime)

reg CSAR_MMM
My result from the regression is as follows:

Array

Thank you in advance