Hi!
It is my first post to this community so I hope I am doing this right.
I am using SAS University Edition
I want to perform an event study using SAS. I am familiar with the theory of event studies in general but I am a beginner in SAS. The past weeks I have been familiarizing with SAS base also, so I have some understanding already on how the program works. I have found some already written codes that I can use to run these event studies but I have some issues. Since I am not that experienced in SAS, I am not sure what has to go where and how my data needs to be formatted to run this code. I want to use the code provided in WRDS by Denys Glushkov (His code is attached below). I also need to mention that the code uses permno, crsp data and S&P 500 benchmark. However since my data regards European firms, I am using a database that uses ISIN and I am using the DAX as my benchmark.
The code seems long but it is just the inputs that I need to figure out where they go and how my data should be set up before I can run the code.
I have my data current sorted like this:
Event dates: -> work.event_dataset
Retuns of stocks and benchmarkt -> work.stocks_dataset
The code that I want to use is the following:
/*https://wrds-www.wharton.upenn.edu/pages/support/applications/event-studies/event-study-research-application/*/
/* ***************************************************************************** */
/* ********* W R D S R E S E A R C H A P P L I C A T I O N S *************** */
/* ***************************************************************************** */
/* Program : EVTSTUDY.SAS */
/* Summary : Provides a sample methodology for calculating Cumulative */
/* Abnormal Returns(CARs)& Buy-Hold Abnormal Returns(BHARs) */
/* with various t-statistics (CS test, Standardized CS test&Patell Z) */
/* in an event study setting. Displays the dynamics of mean CARs and */
/* BHARs in the event window specified by the user */
/* */
/* Date : Sep 2011 */
/* Author : Denys Glushkov, WRDS */
/* **************************************************************************** */
/* STEP 1A: Speficify the parameters necessary to run the event study such as */
/* the length of estimation period and event window, gap b/w estimation & event */
/* window, etc */
%let crsp=work.all_stocks_matched_nodups; /*CRSP libary to be used (CRSPQ - quarterly, CRSP-annual update */
%let estper=150; /*Length of the estimation period in trading days over which */
/*the risk model is estimated */
%let start=-10; /*Beginning of the event window (wtr to the event date,e.g. -2) */
%let end=10; /*End of the event window (relative to the event date, e.g., +1) */
%let gap=15; /*Length of pre-event window,i.e., number of trading days b/w */
/*the end of estimation period and the start of the event window */
%let minest=120; /*Minimum of non-missing returns required for estimation */
%let evtwin=%eval(&end-&start+1); /*length of event window in trading days */
/* STEP 1B: As an example, create the input table containing Permno-event dates */
/* corresponding to the stock additions to and deletions from S&P 500 index */
proc sql;
create table input
as select distinct ISIN_no, start as edate format date9.
from &crsp..dsp500list where not missing(start);
quit;
/* STEP 2. Creating Trading Calendar that accounts for the presence of */
/* weekends, holidays and other non-trading days in the estimation */
/* and event windows */
data caldates;
merge &crsp..dsi(keep=date rename=(date=estper_beg))
&crsp..dsi(keep=date firstobs=&estper rename=(date=estper_end))
&crsp..dsi(keep=date firstobs=%eval(&estper+&gap+1) rename=(date=evtwin_beg))
&crsp..dsi(keep=date firstobs=%eval(&estper+&gap-&start+1) rename=(date=evtdate))
&crsp..dsi(keep=date firstobs=%eval(&estper+&gap+&evtwin) rename=(date=evtwin_end));
format estper_beg estper_end evtwin_beg evtdate evtwin_end date9.;
label estper_beg='Start of the Estimation Window'
estper_end='End of the Estimation Window'
evtwin_beg='Start of the Event Window'
evtwin_end='End of the Event Window'
evtdate='Event Date';
index+1;
if nmiss(estper_beg,estper_end,evtwin_beg,evtwin_end,evtdate)=0;
run;
/*STEP 3: If event date is a non-trading day, select the closest trading day that*/
/* follows the event day */
proc sql; create table temp
as select a.permno, b.*
from input a left join caldates b
on b.evtdate-a.edate>=0
group by a.edate
having (b.evtdate-a.edate)=min(b.evtdate-a.edate);
/*Returns for sample securities around the event dates */
create table evtrets_temp
as select a.permno, a.date format date9., a.ret as ret1,
b.evtdate, b.estper_beg, b.estper_end,
b.evtwin_beg, b.evtwin_end
from &crsp..dsf a, temp b
where a.permno=b.permno and b.estper_beg<=a.date<=b.evtwin_end;
/* Merge in the risk factors */
/* User can create her own risk factors and use it instead of FF+M ones*/
create view evtrets1
as select a.*, (b.mktrf+b.rf) as mkt, b.mktrf, b.rf,b.smb, b.hml, b.umd
from evtrets_temp a left join
ff.factors_daily (keep=date mktrf smb hml umd rf) b
on a.date=b.date;
/*Bring in delisting returns*/
create table evtrets (drop=ret1 where=(not missing(mkt)))
as select a.*,
(1+a.ret1)*sum(1,b.dlret)-1-a.mkt as exret label='Market-adjusted total ret',
(1+a.ret1)*sum(1,b.dlret)-1 as ret "Ret adjusted for delisting"
from evtrets1 a left join &crsp..dsedelist (where=(missing(dlret)=0)) b
on a.permno=b.permno and a.date=b.dlstdt
order by a.permno,a.evtdate,a.date;
quit;
/* STEP 4. Estimating Factor Exposures over the estimation period*/
proc printto log=junk; run;
proc reg data=evtrets edf outest=params noprint;
where estper_beg<=date<=estper_end;
by permno evtdate;
eq0: model exret=;
eq1: model ret=mktrf;
eq2: model ret=mktrf smb hml;
eq3: model ret=mktrf smb hml umd;
run;
proc printto;run;
/* STEP 5. Calculating Abnormal Returns for all models */
/* for each trading day in the event window */
data abrets1/view=abrets1; merge
evtrets(where=(evtwin_beg<=date<=evtwin_end) in=a)
params (where=(_model_='eq0')
keep=permno evtdate _model_ _rmse_ _p_ _edf_
rename=(_rmse_=std0 _p_=p0 _edf_=edf0))
params (where=(_model_='eq1')
keep=permno evtdate _model_ _rmse_ intercept mktrf
rename=(_rmse_=std1 intercept=alpha1 mktrf=beta1))
params (where=(_model_='eq2')
keep=permno evtdate _model_ _rmse_ intercept mktrf smb hml
rename=(_rmse_=std2 intercept=alpha2 mktrf=beta2 smb=sminb2 hml=hminl2))
params (where=(_model_='eq3')
keep=permno evtdate _model_ _rmse_ intercept mktrf smb hml umd
rename=(_rmse_=std3 intercept=alpha3 mktrf=beta3 smb=sminb3 hml=hminl3 umd=umind3));
by permno evtdate;
retain missret;
if first.permno then missret=missing(ret);
if missing(ret) then missret+1; /*count number of missing returns*/
var0=std0**2; var1=std1**2;var2=std2**2;var3=std3**2;
abret0=exret;
expret1=alpha1+beta1*mktrf; abret1=ret-expret1;
expret2=alpha2+beta2*mktrf+sminb2*smb+hminl2*hml; abret2=ret-expret2;
expret3=alpha3+beta3*mktrf+sminb3*smb+hminl3*hml+umind3*umd; abret3=ret-expret3;
nobs=p0+edf0; /*number of observations used in estimation*/
drop p0 edf0 estper_beg estper_end std0 std1 std2 std3 _model_ exret;
if a and nobs>&minest;
run;
/* Transform dates to event time using CRSP Trading Calendar */
/* Using the latter takes into account non-consecutive date records*/
proc sql; create table abrets
as select a.*, (b.index-c.index) as evttime
from abrets1 a left join caldates b
on a.date=b.evtdate
left join caldates c
on a.evtdate=c.evtdate
order by permno, evtdate, date;
quit;
/* Calculating Rolling Cumulative Abnormal Returns and various stats */
/* Transformout= calculates cumulative product of gross returns and */
/* subtracts 1 to arrive at the total net cumulative return */
proc expand data=abrets out=car method=none;
by permno evtdate; id date;
convert ret=cret/transformout=(+1 cuprod -1);
convert mkt=cmkt/transformout=(+1 cuprod -1);
convert expret1 =cexpret1 /transformout=(+1 cuprod -1);
convert expret2 =cexpret2 /transformout=(+1 cuprod -1);
convert expret3 =cexpret3 /transformout=(+1 cuprod -1);
convert abret0=car0/transformout=(sum);
convert abret1=car1/transformout=(sum);
convert abret2=car2/transformout=(sum);
convert abret3=car3/transformout=(sum);
run;
/* Car_Evtdate Table the cross-sectional output that contains for each */
/* "firm-event date": */
/* 1) CAR, BHAR, and SCAR (standardized CAR) */
/* 2) Alpha and Beta from the estimation period */
/* 3) Estimation period variance */
/* Car_Evtwin Table contains Raw, Abnormal, Std. and Buy-and-Hold Abnormal */
/* Daily Returns "firm-date" in event time */
proc printto log=junk;run;
data car_evtdate
(drop=evttime ret mkt smb hml umd date calpha1 calpha2 calpha3
cmrkt csmb chml cumd evtwin_beg evtwin_end abret0 abret1
abret2 abret3 sar0 sar1 sar2 sar3 missret cexpret1 cexpret2 cexpret3)
car_evtwin
(keep=permno evtdate evttime date ret cret abret0 abret1 abret2 abret3
sar0 sar1 sar2 sar3 bhar0 bhar1 bhar2 bhar3 car0 car1 car2 car3);
set car;
by permno evtdate date;
/*Standardized CARs and ARs for various models*/
scar0=car0/(&evtwin*var0)**0.5; scar1=car1/(&evtwin*var1)**0.5;
scar2=car2/(&evtwin*var2)**0.5; scar3=car3/(&evtwin*var3)**0.5;
sar0=abret0/sqrt(var0);sar1=abret1/sqrt(var1);
sar2=abret2/sqrt(var2);sar3=abret3/sqrt(var3);
pat_scale=(nobs-2)/(nobs-4); /*Patell Z scaling factor*/
/*Buy-Hold Abnormal Returns*/
bhar0=cret-cmkt; bhar1=cret-cexpret1;
bhar2=cret-cexpret2; bhar3=cret-cexpret3;
if last.evtdate then do; nrets=&evtwin-missret; output car_evtdate; end;
output car_evtwin;
run;
proc printto;run;
/*Put Cross-sectional and aggregate results together for further analysis*/
data allcars; merge
car_evtwin
(rename=(bhar0=bhar0win bhar1=bhar1win bhar2=bhar2win bhar3=bhar3win
car0=car0win car1=car1win car2=car2win car3=car3win cret=cretwin))
car_evtdate;
by permno evtdate;
run;
/* STEP 6: Compute Cumulative Average Abnormal Return (CAR_MEAN) */
/* and Average Buy-Hold Abnormal Return (BHAR_MEAN) */
/* and other stats across all distinct events */
proc means data=allcars noprint;
class evttime; id nobs;
var ret cret car0 car1 car2 car3 bhar0 bhar1 bhar2 bhar3
bhar0win bhar1win bhar2win bhar3win cretwin
car0win car1win car2win car3win
scar0 scar1 scar2 scar3 abret0 abret1 abret2 abret3
sar0 sar1 sar2 sar3 pat_scale;
output out=allstats
mean= n= t= sum=/autoname;
run;
/*calculate different stats for assessing */
/*statistical signficance of abnormal returns*/
data MA_Evtdate (keep=evttime car0_n cret_mean car0_mean car0_t scar0_t
bhar0_mean pat_car0 model)
MM_Evtdate (keep=evttime car1_n cret_mean car1_mean car1_t scar1_t
bhar1_mean pat_car1 model )
FF_Evtdate (keep=evttime car2_n cret_mean car2_mean car2_t scar2_t
bhar2_mean pat_car2 model )
FFM_Evtdate (keep=evttime car3_n cret_mean car3_mean car3_t scar3_t
bhar3_mean pat_car3 model )
MA_Evtwin (keep=evttime cretwin_mean abret0_n ret_mean abret0_mean
car0win_mean bhar0win_mean abret0_t sar0_t pat_ar0 )
MM_Evtwin (keep=evttime cretwin_mean abret1_n ret_mean abret1_mean
car1win_mean bhar1win_mean abret1_t sar1_t pat_ar1 )
FF_Evtwin (keep=evttime cretwin_mean abret2_n ret_mean abret2_mean
car2win_mean bhar2win_mean abret2_t sar2_t pat_ar2 )
FFM_Evtwin (keep=evttime cretwin_mean abret3_n ret_mean abret3_mean
car3win_mean bhar3win_mean abret3_t sar3_t pat_ar3 );
set allstats;
by evttime;
if _n_=1 and missing(evttime) then do;
abret0_mean=.; abret1_mean=.;
abret2_mean=.; abret3_mean=.;
cretwin_mean=0; ret_mean=.;
bhar1win_mean=0; bhar1win_mean=0;
bhar2win_mean=0;bhar3win_mean=0;
end;
/*Patell Z statistics*/
pat_car0=scar0_mean/(sqrt(pat_scale_sum)/scar0_n);
pat_car1=scar1_mean/(sqrt(pat_scale_sum)/scar1_n);
pat_car2=scar2_mean/(sqrt(pat_scale_sum)/scar2_n);
pat_car3=scar3_mean/(sqrt(pat_scale_sum)/scar3_n);
pat_ar0=sar0_mean/(sqrt(pat_scale_sum)/sar0_n);
pat_ar1=sar1_mean/(sqrt(pat_scale_sum)/sar1_n);
pat_ar2=sar2_mean/(sqrt(pat_scale_sum)/sar2_n);
pat_ar3=sar3_mean/(sqrt(pat_scale_sum)/sar3_n);
label
pat_ar0= 'Patell Z for AR_MA' pat_ar1= 'Patell Z for AR_MM'
pat_ar2= 'Patell Z for AR_FF' pat_ar3= 'Patell Z for AR_FFM'
abret0_t= 'CS t-stat, AR_MA' abret1_t= 'CS t-stat, AR_MM'
abret2_t= 'CS t-stat, AR_FF' abret3_t= 'CS t-stat, AR_FFM'
sar0_t= 'Std CS test, AR_MA' sar1_t= 'Std CS test, AR_MM'
sar2_t= 'Std CS test, AR_FF' sar3_t= 'Std CS test, AR_FFM'
abret0_mean= 'Mean AR_MA' abret1_mean= 'Mean AR_MM'
abret2_mean= 'Mean AR_FF' abret3_mean= 'Mean AR_FFM'
car0_n= 'Number of events in the portfolio'
abret0_n= 'Number of events in the portfolio'
evttime= 'Event Time t'
cret_mean= "Mean CTR (&start, &end)"
cretwin_mean= "Mean CTR (&start,t) "
car0win_mean= "Average CAR_MA (&start, t)"
car1win_mean= "Average CAR_MM (&start, t)"
car2win_mean= "Average CAR_FF (&start, t)"
car3win_mean= "Average CAR_FFM (&start, t)"
bhar0win_mean= "Mean BHAR_MA (&start, t)"
bhar1win_mean= "Mean BHAR_MM (&start, t)"
bhar2win_mean= "Mean BHAR_FF (&start, t)"
bhar3win_mean= "Mean BHAR_FFM (&start, t)"
;
format ret_mean cret_mean abret0_mean abret1_mean abret2_mean abret3_mean
car0_mean car1_mean car2_mean car3_mean bhar0_mean bhar1_mean
bhar2_mean bhar3_mean cretwin_mean
bhar0win_mean bhar1win_mean bhar2win_mean bhar3win_mean
car0win_mean car1win_mean car2win_mean car3win_mean percent7.4
abret0_t abret1_t abret2_t abret3_t sar0_t sar1_t sar2_t sar3_t
pat_car0 pat_car1 pat_car2 pat_car3 pat_ar0 pat_ar1 pat_ar2 pat_ar3
car0_t car1_t car2_t car3_t scar0_t scar1_t scar2_t scar3_t comma10.2;
if evttime=0 then do; model='Market-Adjusted'; output MA_Evtdate;
model='Market Model'; output MM_Evtdate;
model='FF Model'; output FF_Evtdate;
model='Carhart Model'; output FFM_Evtdate;
end;
if missing(evttime) then evttime=&start-1;
output MA_Evtwin; output MM_Evtwin; output FF_Evtwin; output FFM_Evtwin;
run;
/* STEP 7. Putting Event Date CARs and BHARS for various risk models together*/
data allevtdate; set
MA_Evtdate (rename=(car0_mean=car_mean bhar0_mean=bhar_mean
car0_n=n car0_t=car_t scar0_t=scar_t pat_car0=pat_car))
MM_Evtdate (rename=(car1_mean=car_mean bhar1_mean=bhar_mean
car1_n=n car1_t=car_t scar1_t=scar_t pat_car1=pat_car))
FF_Evtdate (rename=(car2_mean=car_mean bhar2_mean=bhar_mean
car2_n=n car2_t=car_t scar2_t=scar_t pat_car2=pat_car))
FFM_evtdate (rename=(car3_mean=car_mean bhar3_mean=bhar_mean
car3_n=n car3_t=car_t scar3_t=scar_t pat_car3=pat_car));
length=&evtwin;
label pat_car= 'Patell Z'
car_mean= "Mean CAR (&start, &end)"
bhar_mean= "Mean BHAR (&start, &end)"
car_t= 'Cross-sectional t-stat for CAR'
scar_t= 'Standaridized cross-sectional t-stat for CAR'
length= 'Length of event window in trading days';
run;
/*Cross-sectional output for CARs/BHARs at the firm-event level*/
data car_evtdate;
retain permno evtdate alpha1 beta1 cret car0 bhar0 var0 car1 bhar1 var1
car2 bhar2 var2 car3 bhar3 var3 nrets nobs;
set car_evtdate;
label alpha1= 'Alpha (Market Model)' beta1='Beta (Market Model'
car0= 'CAR_MA' car1='CAR_MM'
car2= 'CAR_FF' car3='CAR_FFM'
bhar0= 'BHAR_MA' bhar1='BHAR_MM'
bhar2= 'BHAR_FF' bhar3='BHAR_FFM'
var0= 'Estimation period variance (Market-adjusted returns)'
var1= 'Estimation period variance (Market Model)'
var2= 'Estimation period variance (FF Model)'
var3= 'Estimation period variance (Carhart Model)'
cret= 'Cumulative Total Return'
nrets= 'Number of non-missing returns in event window'
nobs= 'Length of the estimation period';
keep permno evtdate alpha1 beta1 cret car0 bhar0 var0 car1 bhar1 var1
car2 bhar2 var2 car3 bhar3 var3 nrets nobs;
format cret alpha1 car0 bhar0 car1 bhar1 car2 bhar2 car3 bhar3 percent7.4
beta1 comma10.3;
run;
/* As an illustration, plot Carhart CAARs and average BHARs in the event window*/
options nodate orientation=landscape; ods pdf file='Carhart_evtrets.pdf';
goptions device=pdfc; /* Plot Saved in Home Directory */
axis1 label=(angle=90 "Cumulative Returns");
axis2 label=("Event time");
symbol interpol=join w=3 l=1;
proc gplot data =FFM_Evtwin;
where evttime>=&start;
Title "Cumulative Total Returns vs. Carhart CAARs and BHARs around the event date";
plot (cretwin_mean car3win_mean bhar3win_mean)*evttime
/overlay legend vaxis=axis1 haxis=axis2;
run;quit; ods pdf close;
/*house cleaning*/
proc sql;
drop table abrets, allcars, allstats, caldates, car, car_evtwin, evtrets, temp,
evtrets_temp,ffm_evtdate, ff_evtdate, ma_evtdate, mm_evtdate, params;
drop view evtrets1, abrets1; quit;
/* ******************************************************************************** */
/* ************* Material Copyright Wharton Research Data Services ************** */
/* ****************************** All Rights Reserved ***************************** */
/* ******************************************************************************** */
All the help is much appreciated!
Thank you very much!
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