I can't figure out how to implement the following for this dataset:
ID and datenr_ are: identifier and time index (daily)
The variable shock_ROLL is either 0 or 1 (it is 1 in about 1% of the cases).
If shock_ROLL is 1 at t=n then I need to check whether the sum of 21 days of excess return (meaning until t=20) have been positive, starting at t=n-1 (the day before the shock_ROLL is 1). In this case the variable LLS should have a value of 1.
I also need to check the number of such LLS within a quarter and count the number per quarter, which could be shown in a new variable with the counting result as a value for each datenr_ in a quarter.
The story behind: in a case of a large stock price drop (like BP oil spill or such a thing) I want to see if the stock price recovers to the level before the shock within 21 trading days using the excess returns (this is stock return minus market return).
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input float(ID datenr excessreturn shock_ROLL LLS TRS) int qdate float Date 1 1 . 0 0 0 160 14612 1 2 .024564743 0 0 0 160 14613 1 3 -.013171673 0 0 0 160 14614 1 4 .03032541 0 0 0 160 14615 1 5 -.04618168 0 0 0 160 14616 1 6 -.00510788 0 0 0 160 14619 1 7 -.0045223236 0 0 0 160 14620 1 8 .009564877 0 0 0 160 14621 1 9 .06696749 0 0 0 160 14622 1 10 -.030753136 0 0 0 160 14623 1 11 -.10425854 0 0 0 160 14626 1 12 .026067734 0 0 0 160 14627 1 13 -.0019803047 0 0 0 160 14628 1 14 -.0030441284 0 0 0 160 14629 1 15 .01700306 0 0 0 160 14630 end format %tq!Qq-CCYY qdate format %td Date
ID and datenr_ are: identifier and time index (daily)
The variable shock_ROLL is either 0 or 1 (it is 1 in about 1% of the cases).
If shock_ROLL is 1 at t=n then I need to check whether the sum of 21 days of excess return (meaning until t=20) have been positive, starting at t=n-1 (the day before the shock_ROLL is 1). In this case the variable LLS should have a value of 1.
I also need to check the number of such LLS within a quarter and count the number per quarter, which could be shown in a new variable with the counting result as a value for each datenr_ in a quarter.
The story behind: in a case of a large stock price drop (like BP oil spill or such a thing) I want to see if the stock price recovers to the level before the shock within 21 trading days using the excess returns (this is stock return minus market return).
