Hi all,
After looking at previous ES/CAR threads and a popular Princeton link (https://dss.princeton.edu/online_hel...study.html#car) I am still struggling to create my event study. What I am looking to achieve is to assess if there are CAR regarding events where the final column "ecbannouncement" equals 1. The data are for two indexes, or equivalently 2 firms if you prefer. There are multiple events. I have price data, and % change from one price to the next. I only want to measure the change on the day of the event. One of the key issues I have is that my events are randomly scattered, and so I cannot use an estimation window 'rule'.
I am working in Stata 13.0. Observations 5000.
Any help would be much appreciated.
After looking at previous ES/CAR threads and a popular Princeton link (https://dss.princeton.edu/online_hel...study.html#car) I am still struggling to create my event study. What I am looking to achieve is to assess if there are CAR regarding events where the final column "ecbannouncement" equals 1. The data are for two indexes, or equivalently 2 firms if you prefer. There are multiple events. I have price data, and % change from one price to the next. I only want to measure the change on the day of the event. One of the key issues I have is that my events are randomly scattered, and so I cannot use an estimation window 'rule'.
I am working in Stata 13.0. Observations 5000.
Any help would be much appreciated.
Code:
input str10 date float(iboxx iboxx_1d_percent_change eurostoxx eurostx_1d_percent_change) byte ecbannouncement "05/06/2018" 390.5586 .3450298 386.89 -.31 0 "04/06/2018" 389.2157 -.32660925 388.11 .31 0 "01/06/2018" 390.4911 .244412 386.91 1.01 0 "31/05/2018" 389.539 .16564375 383.06 -.63 0 "30/05/2018" 388.8948 -.50721276 385.49 .27 0 "29/05/2018" 390.8774 .4338071 384.47 -1.37 0 "25/05/2018" 389.1891 .3527581 391.08 .14 0 "24/05/2018" 387.821 .2287407 390.54 -.52 0 "23/05/2018" 386.9359 .3488361 392.58 -1.1 0 "22/05/2018" 385.59085 -.2346069 396.94 .27 0 "21/05/2018" 386.4976 -.4132477 395.87 .3 0 "18/05/2018" 388.1014 .21049033 394.67 -.28 0 "17/05/2018" 387.2862 -.1688323 395.79 .66 0 "16/05/2018" 387.9412 .3571809 393.21 .21 0 "15/05/2018" 386.5605 .24801083 392.37 .05 0 "14/05/2018" 385.6041 -.07222659 392.19 -.05 0 "11/05/2018" 385.8828 -.10083818 392.4 .11 0 "10/05/2018" 386.2723 -.6410539 391.97 -.12 0 "09/05/2018" 388.7645 .07585402 392.44 .63 0 "08/05/2018" 388.46985 .4058572 390 .13 0 "04/05/2018" 386.8996 -.14886068 387.03 .63 0 "03/05/2018" 387.4764 .07181849 384.62 -.73 0 "02/05/2018" 387.1983 -.14353397 387.44 .63 0 "01/05/2018" 387.7549 -.24312073 385.03 -.08 0 "30/04/2018" 388.6999 .2201802 385.32 .18 0 "27/04/2018" 387.8459 -.6185774 384.64 .23 0 "26/04/2018" 390.26 .664869 383.75 .94 1
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