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Is there anyway to return the rank of each fundamental instead of the actual fundamental float?
This code obviously doesn't work, but demonstrates what I want to do:
top_quality = sorted(sortedByDollarVolume, key=lambda x: x.OperationRatios.ROIC.ThreeMonths.rank() + x.OperationRatios.LongTermDebtEquityRatio.ThreeMonths.rank() + (x.ValuationRatios.CashReturn + x.ValuationRatios.FCFYield).rank(), reverse=True)[:self.num_screener]How would I create a panda series in my FineSelectionFunction that wouldc contain the rank of each symbol for each fundamental and then sort based on those rankings rather than the actual fundamental data?
Thanks for your help.
Nathan
I think I found something close - though my experience with panda is limited so I don't really know if it is doing the same thing...
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ROIC = sorted(sortedByDollarVolume, key=lambda x: x.OperationRatios.ROIC.ThreeMonths, reverse=True) LTDER = sorted(sortedByDollarVolume, key=lambda x: x.OperationRatios.LongTermDebtEquityRatio.ThreeMonths, reverse=True) FCFY = sorted(sortedByDollarVolume, key=lambda x: x.ValuationRatios.FCFYield, reverse=True) CR = sorted(sortedByDollarVolume, key=lambda x: x.ValuationRatios.CashReturn, reverse=True) ## Create dictionary to store scores scores = {} ## Assign a score to each stock. for i,ele in enumerate(ROIC): ROIC_rank = i LTDER_rank = LTDER.index(ele) FCFY_rank = FCFY.index(ele) CR_rank = CR.index(ele) scores[ele] = ROIC_rank + LTDER_rank + (FCFY_rank*0.5 + CR_rank*0.5) #Return top quality stocks top_quality = sorted(scores.items(), key=lambda d:d[1],reverse=False)[:self.num_screener]Â
Rahul Chowdhury
Hey Nathan,
That's super close to the behavior I think you're looking for. I think the translation of this line
(x.ValuationRatios.CashReturn + x.ValuationRatios.FCFYield).rank()could have been done better. You want the rank when sorted by the sum of CashReturn and FCFY, not the sum of the ranks.
Instead of sorting separately
FCFY = sorted(sortedByDollarVolume, key=lambda x: x.ValuationRatios.FCFYield, reverse=True) CR = sorted(sortedByDollarVolume, key=lambda x: x.ValuationRatios.CashReturn, reverse=True)you can sort by the sum.
FCFY_CR = sorted(sortedByDollarVolume, key=lambda x: x.ValuationRatios.FCFYield + x.ValuationRatios.CashReturn, reverse=True)Then you can retrieve the rank of the sum.
FCFY_CR_rank = FCFY_CR.index(ele) scores[ele] = ROIC_rank + LTDER_rank + FCFY_CR_RANKÂ
Nathan
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