Dear Community,
As I am a greenhorn in Stata, I hope you can help me out with the following. I use Stata 12 on a Windows 10 computer. The dataset is a panel dataset with 30+ companies over a multi-year period (5 years). It might be important to mention, that each company can have multiple observations in the same second; however each company also can have not one single observation for several months. (I did not set the dataset as a panel data set, as this did not work due to multiple observations at the same time for certain companies).
My intention is to mark observations of a panel data set that lie in between a specific absulute value increase of a specific variable over a specific rolling time period/window for a specific company.
So basically it´s about identifying peaks: periods that show a strong increase of one variable value within a given time period.
My preferred methodology would be like this:
Array
Below I also included a structure of my dataset. However the real dataset includes observations for several companies!
Thanks a lot.
As I am a greenhorn in Stata, I hope you can help me out with the following. I use Stata 12 on a Windows 10 computer. The dataset is a panel dataset with 30+ companies over a multi-year period (5 years). It might be important to mention, that each company can have multiple observations in the same second; however each company also can have not one single observation for several months. (I did not set the dataset as a panel data set, as this did not work due to multiple observations at the same time for certain companies).
My intention is to mark observations of a panel data set that lie in between a specific absulute value increase of a specific variable over a specific rolling time period/window for a specific company.
So basically it´s about identifying peaks: periods that show a strong increase of one variable value within a given time period.
My preferred methodology would be like this:
- Look at rolling x-days windows...
- …and identify the maximum and minimum within this rolling window.
- If the absolute difference between the maximum and minimum is equal or larger than threshold x...
- …set a dummy_variable=1 for all observations that lie in between (time perspective) the minimum and maximum observation and also include further relevant observations at the same day of the minimum and maximum observation.
- If possible the window moves forward on the shortest possible basis. However a daily moving window would be fine, as it might need less calculation time.
- Dummy variables have to be calculated for each company individually.
Array
Below I also included a structure of my dataset. However the real dataset includes observations for several companies!
Code:
* Example generated by -dataex-. To install: ssc install dataex clear input str36 CompanyID double time float Ratio "Company_1" 1551191502000 .9409 "Company_1" 1551263205000 .8935 "Company_1" 1551263205000 .8935 "Company_1" 1551264008000 .8935 "Company_1" 1551264007000 .8935 "Company_1" 1551264209000 .8935 "Company_1" 1551264209000 .8935 "Company_1" 1551350618000 .9409 "Company_1" 1551350618000 .9409 "Company_1" 1551350895000 .9409 "Company_1" 1551350895000 .9409 "Company_1" 1551351179000 .9409 "Company_1" 1551351179000 .9409 "Company_1" 1551358929000 .9409 "Company_1" 1551358928000 .9409 "Company_1" 1551362331000 .9409 "Company_1" 1551362666000 .9409 "Company_1" 1551607702000 1.0198001 "Company_1" 1551608391000 1.0198001 "Company_1" 1551614962000 1.0198001 "Company_1" 1551614962000 1.0198001 "Company_1" 1551694001000 1.0345 "Company_1" 1551694001000 1.0345 "Company_1" 1551695534000 1.0345 "Company_1" 1551695534000 1.0345 "Company_1" 1551696853000 1.0345 "Company_1" 1551696853000 1.0345 "Company_1" 1551791952000 .9874 "Company_1" 1551791952000 .9874 "Company_1" 1551867074000 1.1290001 "Company_1" 1551867073000 1.1290001 "Company_1" 1551867299000 1.1290001 "Company_1" 1551867299000 1.1290001 "Company_1" 1551954787000 1.1287 "Company_1" 1551954875000 1.1287 "Company_1" 1551955159000 1.1287 "Company_1" 1552212120000 1.1285 "Company_1" 1552212276000 1.1285 "Company_1" 1552217153000 1.1285 "Company_1" 1552217059000 1.1285 "Company_1" 1552217153000 1.1285 "Company_1" 1552232444000 1.1285 "Company_1" 1552297735000 1.1755999 "Company_1" 1552298051000 1.1755999 "Company_1" 1552298552000 1.1755999 "Company_1" 1552318978000 1.1755999 "Company_1" 1552387492000 1.1757 "Company_1" 1552472652000 1.2939 "Company_1" 1552474844000 1.2939 "Company_1" 1552474843000 1.2939 "Company_1" 1552474844000 1.2939 "Company_1" 1552475163000 1.2939 "Company_1" 1552558072000 1.3174 "Company_1" 1552564328000 1.3174 "Company_1" 1552817103000 1.2494 "Company_1" 1552817276000 1.2494 "Company_1" 1552817515000 1.2494 "Company_1" 1552817862000 1.2494 "Company_1" 1552826589000 1.2494 "Company_1" 1552826589000 1.2494 "Company_1" 1552826644000 1.2494 "Company_1" 1552826644000 1.2494 "Company_1" 1552826926000 1.2494 "Company_1" 1552827022000 1.2494 "Company_1" 1552837923000 1.2494 "Company_1" 1552903166000 1.3457 "Company_1" 1552903370000 1.3457 "Company_1" 1552903369000 1.3457 "Company_1" 1552903681000 1.3457 "Company_1" 1552903681000 1.3457 "Company_1" 1552903966000 1.3457 "Company_1" 1552903966000 1.3457 "Company_1" 1552905847000 1.3457 "Company_1" 1552905846000 1.3457 "Company_1" 1552905846000 1.3457 "Company_1" 1552905846000 1.3457 "Company_1" 1552910050000 1.3053 "Company_1" 1552910175000 1.3053 "Company_1" 1552910582000 1.3053 "Company_1" 1552915864000 1.3457 "Company_1" 1552986683000 1.3997 "Company_1" 1552986851000 1.3997 "Company_1" 1552986851000 1.3997 "Company_1" 1552992306000 1.3997 "Company_1" 1552994397000 1.3997 "Company_1" 1552994396000 1.3997 "Company_1" 1552994397000 1.3997 "Company_1" 1553075883000 1.3053 "Company_1" 1553079281000 1.3053 "Company_1" 1553079281000 1.3053 "Company_1" 1553079281000 1.3053 "Company_1" 1553166721000 1.2823 "Company_1" 1553166884000 1.2823 "Company_1" 1553167016000 1.2823 "Company_1" 1553167160000 1.2823 "Company_1" 1553167160000 1.2823 "Company_1" 1553421702000 1.2512 "Company_1" 1553435166000 1.2512 "Company_1" 1553505928000 1.1889 "Company_1" 1553505928000 1.1889 "Company_1" 1553506077000 1.1889 "Company_1" 1553511875000 1.1889 "Company_1" 1553511875000 1.1889 "Company_1" 1553511875000 1.1889 "Company_1" 1553519526000 1.1889 "Company_1" 1553590588000 1.2768 "Company_1" 1553590834000 1.2768 "Company_1" 1553590834000 1.2768 "Company_1" 1553599378000 1.2768 "Company_1" 1553599377000 1.2768 "Company_1" 1553599377000 1.2768 "Company_1" 1553685683000 1.209 "Company_1" 1553685683000 1.209 end format %tc tradetime
Thanks a lot.