Overall Statistics
Total Trades
0
Average Win
0%
Average Loss
0%
Compounding Annual Return
0%
Drawdown
0%
Expectancy
0
Net Profit
0%
Sharpe Ratio
0
Probabilistic Sharpe Ratio
0%
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
0
Beta
0
Annual Standard Deviation
0
Annual Variance
0
Information Ratio
0
Tracking Error
0
Treynor Ratio
0
Total Fees
$0.00
Estimated Strategy Capacity
$0
Lowest Capacity Asset
from AlgorithmImports import *
from Selection.FundamentalUniverseSelectionModel import FundamentalUniverseSelectionModel
from itertools import groupby
#functools


class UpgradedFluorescentPinkZebra(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2021, 11, 4)  # Set Start Date
        self.SetCash(2000000)  # Set Strategy Cash
        self.AddUniverse(self.Coarse, self.Fine)
        self.longTotal = 40
        self.shortTotal = 40
        self.longStocks = []
        self.shortStocks = []

    def OnData(self, data):
        pass
        # portfolioTargets = []
        # for stock in self.longStocks:
        #     portfolioTargets.append(PortfolioTarget(stock, ))
    
    def OnSecuritiesChanged(self, changes):
        pass
    
    def Coarse(self, coarse):
        filtered = [x for x in coarse if x.HasFundamentalData and x.Price > 0 and x.Volume > 0]
        self.dollarVolumeBySymbol = {}
        return [x.Symbol for x in filtered]
    
    def Fine(self, fine):
        self.metrics = {}
        rankinglist = []
        allFine = [x for x in fine]
        for security in fine:
            symbol = security.Symbol
            roic = security.OperationRatios.ROIC.ThreeMonths
            earning_yield = security.ValuationRatios.EarningYield
            pe = security.ValuationRatios.NormalizedPERatio
            ps = security.ValuationRatios.PSRatio
            pb = security.ValuationRatios.PBRatio
            self.metrics[security] = [roic, earning_yield, pe, ps, pb]
            rankinglist.append(security)
            
        '''Rank Securities'''
        self.rankings = {}
        ranking1 = sorted(rankinglist, key = lambda x: self.metrics[x][0], reverse=False)
        ranking2 = sorted(rankinglist, key = lambda x: self.metrics[x][1], reverse=False)
        ranking3 = sorted(rankinglist, key = lambda x: self.metrics[x][2], reverse=False)
        ranking4 = sorted(rankinglist, key = lambda x: self.metrics[x][3], reverse=False)
        ranking5 = sorted(rankinglist, key = lambda x: self.metrics[x][4], reverse=False)

        '''Convert their rankings to numerical values and sum a stocks rankings'''
        for stock in rankinglist:
            rank1 = ranking1.index(stock)
            rank2 = ranking2.index(stock)
            rank3 = ranking3.index(stock)
            rank4 = ranking4.index(stock)
            rank5 = ranking5.index(stock)
            total = (rank1 + rank2 + rank3 + rank4 + rank5)
            
            self.rankings[stock] = total
            
        finalSecurities = []
        sectorCodes = [MorningstarSectorCode.Technology, MorningstarSectorCode.FinancialServices, MorningstarSectorCode.RealEstate, MorningstarSectorCode.Healthcare]
        
        sector1 = [x for x in allFine if x.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.Technology]
        sector2 = [x for x in allFine if x.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.FinancialServices]
        sector3 = [x for x in allFine if x.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.RealEstate]
        sector4 = [x for x in allFine if x.AssetClassification.MorningstarSectorCode == MorningstarSectorCode.Healthcare]
        sectors = [sector1,sector2,sector3,sector4]
        for sector in sectors:
            y = sorted(sector, key = lambda x: self.rankings[x], reverse = True)
            finalSecurities.extend(y[0:10]) #Top 10
            finalSecurities.extend(y[-10:]) #Bottom 1010
            self.longStocks.extend([x.Symbol.Value for x in y[0:10]])
            self.shortStocks.extend([x.Symbol.Value for x in y[-10:]])
        
        #         for code, g in groupby(allFine, lambda x: x.AssetClassification.MorningstarSectorCode):
        #   if code not in sectorCodes: continue
        #   y = sorted(g, key = lambda x: self.rankings[x], reverse = True)
        #   finalSecurities.extend(y[0:10]) #Top 10
        #   finalSecurities.extend(y[-10:]) #Bottom 1010
            
        finalSymbols = [x.Symbol for x in finalSecurities]
        finalTickers = [x.Value for x in finalSymbols]
        self.Debug("LongStocks")
        self.Debug(self.longStocks)
        self.Debug("ShortStocks")
        self.Debug(self.shortStocks)
        return finalSymbols