Dear All,
I am simply trying to test whether the return of dependent variable increases/decreases after the sample end date (December 2001). For example, my dependent variable is L_S (long-short portfolio) of stock i at time t and the independent variable is post sample dummy for stock i at time t. Post sample dummy is equal to one if the date is after 2001, else zero.
L_S(it) = alphai + beta1 post sampel dummy(it) + e(it)
Can you please help me how to run the regression test for changes in returns relative to the sample end date (December 2001)? I have provided sample data too.
data have;
infile cards expandtabs truncover;
input stock date : yymmn6. L_S post_sample ;
format Date yymmn6.;
cards;
14 199901 14.0238 0
15 199901 11.9454 0
16 199901 9.0066 0
14 199902 1.5165 0
15 199902 -1.9619 0
16 199902 0.3936 0
14 199903 1.9127 0
15 199903 -0.2142 0
16 199903 -6.9887 0
14 199904 1.9835 0
15 199904 1.1102 0
16 199904 1.1719 0
14 199905 1.771 0
15 199905 3.2528 0
16 199905 -0.7609 0
14 199906 0.2883 0
15 199906 1.174 0
16 199906 -0.3383 0
14 199907 3.1988 0
15 199907 2.2924 0
16 199907 -2.6332 0
14 199908 0.3939 0
15 199908 -0.1062 0
16 199908 -2.1077 0
14 199909 2.2333 0
15 199909 2.3855 0
16 199909 -0.9922 0
14 199910 0.0906 0
15 199910 -1.7595 0
16 199910 1.8265 0
14 199911 12.0945 0
15 199911 13.1003 0
16 199911 11.7012 0
14 199912 13.1348 0
15 199912 13.0311 0
16 199912 5.6075 0
14 200001 16.5104 0
15 200001 13.4878 0
16 200001 1.6201 0
14 200002 24.751 0
15 200002 22.8749 0
16 200002 9.1362 0
14 200003 -7.1384 0
15 200003 -5.9835 0
16 200003 -7.9094 0
14 200004 -13.1302 0
15 200004 -12.6789 0
16 200004 -12.3907 0
14 200005 -7.179 0
15 200005 -8.9204 0
16 200005 -12.4663 0
14 200006 9.8039 0
15 200006 10.4251 0
16 200006 4.0955 0
14 200007 -6.7036 0
15 200007 -6.3405 0
16 200007 -2.261 0
14 200008 1.7284 0
15 200008 2.8166 0
16 200008 -0.1966 0
14 200009 -6.1185 0
15 200009 -6.2332 0
16 200009 -8.9549 0
14 200010 -9.5955 0
15 200010 -8.6117 0
16 200010 -7.8711 0
14 200011 -15.9693 0
15 200011 -14.1019 0
16 200011 -17.3939 0
14 200012 -11.7599 0
15 200012 -11.0496 0
16 200012 -16.0614 0
14 200101 28.428 1
15 200101 24.3161 1
16 200101 24.8696 1
14 200102 -10.0572 1
15 200102 -9.8009 1
16 200102 -14.7445 1
14 200103 -8.1778 1
15 200103 -6.6534 1
16 200103 -12.8975 1
14 200104 3.5659 1
15 200104 4.775 1
16 200104 7.0148 1
14 200105 3.0865 1
15 200105 3.0205 1
16 200105 2.6813 1
14 200106 -3.0407 1
15 200106 -1.0529 1
16 200106 6.5331 1
14 200107 -7.8688 1
15 200107 -6.0558 1
16 200107 -6.5671 1
14 200108 -5.2509 1
15 200108 -4.9021 1
16 200108 -4.7708 1
14 200109 -6.6907 1
15 200109 -7.7812 1
16 200109 -6.3164 1
14 200110 8.0976 1
15 200110 10.2051 1
16 200110 6.8036 1
14 200111 4.6386 1
15 200111 4.0607 1
16 200111 9.7786 1
14 200112 2.4793 1
15 200112 3.2357 1
16 200112 6.4167 1
14 200201 0.3871 1
15 200201 0.1048 1
16 200201 -3.0061 1
14 200202 -7.5435 1
15 200202 -7.1932 1
16 200202 -10.9996 1
14 200203 1.1006 1
15 200203 3.6903 1
16 200203 -2.3129 1
14 200204 -6.706 1
15 200204 -4.6423 1
16 200204 -7.2183 1
14 200205 -3.319 1
15 200205 -3.5954 1
16 200205 -4.587 1
14 200206 -5.9677 1
15 200206 -6.8817 1
16 200206 -4.1095 1
14 200207 -4.3103 1
15 200207 -5.4936 1
16 200207 -1.6184 1
14 200208 -0.783 1
15 200208 -1.9367 1
16 200208 -3.7291 1
14 200209 -6.8038 1
15 200209 -4.4041 1
16 200209 -4.2089 1
14 200210 4.7228 1
15 200210 4.2958 1
16 200210 6.1159 1
14 200211 14.8031 1
15 200211 11.6538 1
16 200211 9.2207 1
14 200212 -7.44 1
15 200212 -5.6201 1
16 200212 -6.7057 1
14 200301 2.7663 1
15 200301 1.9519 1
16 200301 0.2942 1
14 200302 -0.5867 1
15 200302 -0.6244 1
16 200302 -3.116 1
14 200303 0.8218 1
15 200303 0.8057 1
16 200303 0.8502 1
14 200304 5.9883 1
15 200304 4.1283 1
16 200304 8.4368 1
14 200305 13.8637 1
15 200305 11.1063 1
16 200305 4.3414 1
14 200306 4.0383 1
15 200306 4.8102 1
16 200306 -0.4886 1
14 200307 4.8519 1
15 200307 4.2237 1
16 200307 3.1779 1
14 200308 2.7659 1
15 200308 3.2586 1
16 200308 -0.6638 1
14 200309 5.2582 1
15 200309 3.2569 1
16 200309 -0.4464 1
14 200310 2.961 1
15 200310 3.1561 1
16 200310 1.5347 1
14 200311 0.5451 1
15 200311 1.0336 1
16 200311 -4.545 1
14 200312 0.6783 1
15 200312 -0.7552 1
16 200312 -5.7656 1
run;
Thanks in advance for your help.
Best Regards,
Cheema
Assuming that e(it) is iid normal:
proc glm data=have;
class stock post_sample;
model l_s = stock|post_sample / ss3;
output out=res r=l_s_res;
run; quit;
proc univariate data=res normal;
var l_s_res;
probplot / normal(mu=0) square;
run;
Thanks for it, but it seems bit different than what I am looking for. I might not have explained it well. Please find the attached Table from one of the paper from Journal of Finance, I want to run the similar regression. Thanks for your help.
Sorry. I can not help you. Maybe you should take a look at PROC PANEL
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