I have been wondering about the What Worked Lately approach to screen selection and I am hoping to test the following:
Find the stocks over the past X periods that produced the highest return with the lowest variance in screen picks. That is, find good screens that made their gains from multiple stocks - not just one stock. My reasoning is that I think such screens were more than lucky.
The only way I can think of to test this is to run each screen for its 1st, 2nd, 3rd, 4th...nth rank and the post-process the data.
Does anyone have another approach?
Thanks
knigit
concept: Lowest variance in screen picks
Hi knigit,
My name is mariopapas ;
What do you mean by :: running several runs of the same screening program with ranks 1st, 2nd, 3rd, 4th, etc... ?
re: concept: Lowest variance in screen picks
Hello mariopapas-
Here is an example of what I am doing to get the results for this calculation:
Run 193404 shows the returns for the #1 pick for the screen GSX.
Run 193403 shows the returns for the #2 pick, and so on.
This method requires a new run on the backtester for each rank. I was hoping to minimize the load on the backtester, but I think this will work out OK.
Thanks for the reply,
knigit
I will assume you are
I will assume you are looking for some kind of measure of variance of returns for picks in a given period? E.g. if you are running a top 5 screen, you want to measure the statistics for individual returns when selling and somehow generate an aggregate number from this, possibly mean/median/min/max/sd? If we can agree upon measures which makes sense might try to put something like that into the backtester.
Reply
Keelix-
Thank you for the response.
Yes, your description is precisely what I am after. I was planning on calculating the sd once I gathered all the data into Excel. Another metric may be better - I do not know - but sd should allow me to achieve the goal.
If it would be possible to implement, I would greatly appreciate it.
Thoughts?