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I'm looking to create an algorithm that returns a list of companies that meet the following 5 criteria:
1. 20% revenue growth over the next 3 years
2. Cash > short term debt
3. PEG ratio not above 1.5
4. Within 3% of the 50dma or 200dma
5. Free cash flow positive
I've completed the boot camp and have been following the tutorials on universe selection but I'm new to all of this. I'm finding plenty of help with returning a list sorted by some value (dollar volume for example) but I need a list of companies that meet these criteria not a ranked list.
Here's the code I edited from the Stock Selection Strategy Based On Fundamental Factors Algorithm found in the strategy library. I would include a backtest but it won't even build. The issue is clearly in the FineSelectionFunction().
class StockSelectionStrategyBasedOnFundamentalFactorsAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2009, 1, 2) # Set Start Date
self.SetEndDate(2017, 5, 2) # Set End Date
self.SetCash(50000) # Set Strategy Cash
self.current_month = -1
self.coarse_count = 300
self.fine_count = 10
self.AddUniverse(self.CoarseSelectionFunction, self.FineSelectionFunction)
self.SetAlpha(ConstantAlphaModel(InsightType.Price, InsightDirection.Up, timedelta(30)))
self.SetPortfolioConstruction(EqualWeightingPortfolioConstructionModel(lambda time:None))
def CoarseSelectionFunction(self, coarse):
if self.current_month == self.Time.month:
return Universe.Unchanged
self.current_month = self.Time.month
sortedByDollarVolume = sorted([x for x in coarse if x.HasFundamentalData],
key=lambda x: x.DollarVolume, reverse=True)[:self.coarse_count]
return [i.Symbol for i in sortedByDollarVolume]
def FineSelectionFunction(self, fine):
fine = [x for x in fine if x.FinancialStatements.BalanceSheet.Cash.OneMonth > x.FinancialStatements.BalanceSheet.CurrentLiabilities.OneMonth
and x.ValuationRatios.PEGRatio < 1.5
and x.FinancialStatements.CashFlowStatement.FreeCashFlow.OneMonth > 0
and x.ValuationRatios.SecondYearEstimatedEPSGrowth > 0.12
sortedByfactor1 = sorted(fine, key=lambda x: x.FinancialStatements.BalanceSheet.Cash.OneMonth > x.FinancialStatements.BalanceSheet.CurrentLiabilities.OneMonth)
sortedByfactor2 = sorted(fine, key=lambda x: x.ValuationRatios.PEGRatio < 1.5)
sortedByfactor3 = sorted(fine, key=lambda x: x.FinancialStatements.CashFlowStatement.FreeCashFlow.OneMonth > 0)
sortedByfactor4 = sorted(fine, key=lambda x: x.ValuationRatios.SecondYearEstimatedEPSGrowth > 0.12)
stock_dict = {}
for rank1, ele in enumerate(sortedByfactor1):
rank2 = sortedByfactor2.index(ele)
rank3 = sortedByfactor3.index(ele)
rank4 = sortedByfactor4.index(ele)
stock_dict[ele] = rank1 + rank2 + rank3 + rank4
sorted_stock = sorted(stock_dict.items(),
key=lambda d:d[1], reverse=True)[:self.fine_count]
return [x[0].Symbol for x in sorted_stock]Any help with this would be greatly appreciated. I think these are good criteria to trade on.
Shile Wen
Hi Tom,
The issue is that line 36 was missing the closing square bracket for the list comprehension. Furthermore, it appears the filter criteria in lines 33-36 is too strict, and thus doesn't result in anything in the list, which means no stocks will be invested in, so I'd suggest loosening the filters.
Best,
Shile Wen
Tom Penrose
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