Hi all,
I want to limit a Z-score to 2.5 std (I want to reduce the effect of outliers). As I am calculating the Z-score for the whole universe at each sector, I am having some trouble to limit the variables to those limits.
I know that I can use winsorize to get rid of the outliers, but I want to have a cut of based on std than on the percentiles. I want to add more factors and do some math with the Zscores.
Any ideas how can I limit the variable to -2.5 to 2.5 std?
Thank you!!!!
Not sure if this is what you had in mind, but maybe something like this?
bp_rank = bp.zscore(mask = base_universe, groupby=Sector())
# Create filter for zscores between -2.5 and 2.5
bp_rank_limit_filter = (bp_rank > -2.5) & (bp_rank < 2.5)
# <----> FINAL <---->
combined_rank = bp_rank
# Use a mask to eliminate outliers
longs = combined_rank.top(10, mask=bp_rank_limit_filter)
shorts = combined_rank.bottom(10, mask=bp_rank_limit_filter)
It's a bit clunky, but you could put both factors into a single custom factor, do the factor combination within the factor, and then apply your z-score clipping there, before the custom factor output. I'm sure someone can provide a more elegant approach, but if you are stuck, this should work.
Thank you very much guys.
The problem is that if I filter out the ouliers I will take them out. And my plan is too keep them (I just want to limit their std value). I am planning to add some momentum factors and combine both Zscores (Value and Momentum signals) to select the best stocks. That way I will get the best stock (in std) for both Value and Momentum for each sector of the universe.
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