Overall Statistics
Total Trades
166
Average Win
1.67%
Average Loss
-0.67%
Compounding Annual Return
25.301%
Drawdown
28.900%
Expectancy
1.928
Net Profit
129.303%
Sharpe Ratio
0.98
Probabilistic Sharpe Ratio
39.821%
Loss Rate
16%
Win Rate
84%
Profit-Loss Ratio
2.50
Alpha
0.253
Beta
-0.075
Annual Standard Deviation
0.247
Annual Variance
0.061
Information Ratio
0.301
Tracking Error
0.323
Treynor Ratio
-3.209
Total Fees
$969.04
class SiegfriedsRework(QCAlgorithm):
    
    def Initialize(self):
        self.SetStartDate(2009, 1, 1)
        self.SetEndDate(2012, 9, 4)
        self.SetCash(100000)
        self.UniverseSettings.Resolution = Resolution.Daily
        self.SetUniverseSelection(FineFundamentalUniverseSelectionModel(self.SelectCoarse, self.SelectFine))
        self.AddEquity("SPY")
        self.Schedule.On(self.DateRules.MonthStart("SPY"), self.TimeRules.AfterMarketOpen("SPY", 120), self.Rebalance)
        self.num_symb_coarse = 8000
        self.monthly_rebalance = False 
        self.new_symbols = []
        self.invested_stocks = []
        self.min_market_cap = 5
        self.min_roic = 0.7
        self.max_roic = 20 # max ROIC at purcahse only. if stock has roic intially below this threshold, but rises while in holdings, stock won't be liquidated
        self.min_volume = 200000 # minimum trading volume
        self.max_peg = 100 # max PB at purcahse only. if stock has PB intially below this threshold, but rises while in holdings, stock won't be liquidated
        
        # security.Fundamentals - only available if fine selection implemented
    
    # Universe Selection, OnSecuritiesChanged, OnData are all called midnight
    
    # All on same time stamp
    # Pick Universe -> Handle Changes -> Receive Data
    # 1. UniverseSelection(Coarse/Fine) -> 2. OnSecuritiesChanged -> 3. OnData
    
    # coarse/fine universe selection runs everyday at midnight
    def SelectCoarse(self, coarse):
        
        if self.monthly_rebalance == False:
            return Universe.Unchanged # if selectcoarse returns universe.unchanged, selectfine is not called
        
        self.monthly_rebalance = False
        
        filtered_coarse = [x for x in coarse if x.HasFundamentalData and x.Price > 0] # removing ETFs, ETNs
        # sorted_coarse = sorted(filtered_coarse, key=lambda k:k.DollarVolume, reverse=True)
        sorted_coarse = [x for x in filtered_coarse if x.DollarVolume > self.min_volume]
        top_liquid_coarse = sorted_coarse[:self.num_symb_coarse]
        
        return [i.Symbol for i in top_liquid_coarse]
         
    
    def SelectFine(self, fine):
        
        filtered_fine = [x for x in fine if x.CompanyReference.CountryId == "USA"
                            and x.AssetClassification.MorningstarSectorCode != MorningstarSectorCode.Energy
                            and x.AssetClassification.MorningstarSectorCode != MorningstarSectorCode.FinancialServices
                            and x.MarketCap/1000000 > self.min_market_cap
                            and x.FinancialStatements.BalanceSheet.InvestedCapital.TwelveMonths > 0
                            and x.FinancialStatements.IncomeStatement.EBIT.TwelveMonths/x.FinancialStatements.BalanceSheet.InvestedCapital.TwelveMonths > self.min_roic
                            and x.FinancialStatements.IncomeStatement.EBIT.TwelveMonths/x.FinancialStatements.BalanceSheet.InvestedCapital.TwelveMonths < self.max_roic
                            and x.ValuationRatios.NormalizedPEGatio > 0
                            and x.ValuationRatios.NormalizedPEGatio < self.max_peg]
        
        sorted_fine = sorted(filtered_fine, key=lambda x:x.ValuationRatios.NormalizedPEGatio, reverse = False)
        
        triptile = 1 if len(sorted_fine)/4 <= 0 else int(round((len(sorted_fine)/4)))
        bottom_triptile = sorted_fine[:triptile]
        
        # self.Debug(f"filtered_fine: {[str(i.Symbol) for i in filtered_fine]}")
        self.new_symbols = [i.Symbol for i in bottom_triptile]
        # self.Debug(f"chosen_fine: {[str(i) for i in self.new_symbols]}")
        
        # self.new_symbols = [i.Symbol for i in sorted_fine]
        
        return self.new_symbols # new symbols to add to our watchlist
    
    
    # this is called each time a security is added or removed from our universe
    def OnSecuritiesChanged(self, changes):

        # liquidate securities based on their fundamentals, remove from watchlist
        for symbol in self.Portfolio.Keys:
            
            # we only care about securities we are invested in
            if not self.Portfolio[symbol].Invested:
                continue
            
            security = self.Securities[symbol]
                                 
            # liquidate stocks that go below min ROIC
            if security.Fundamentals.FinancialStatements.IncomeStatement.EBIT.TwelveMonths/security.Fundamentals.FinancialStatements.BalanceSheet.InvestedCapital.TwelveMonths < self.min_roic \
                    or security.Fundamentals.MarketCap/1000000 < self.min_market_cap \
                    or security.Price <= 0:
                self.invested_stocks.remove(security.Symbol)
                self.Liquidate(security.Symbol)
                self.Debug(f"!!!Selling {security} @ {security.Price}," \
                                 + f" ROIC is {security.Fundamentals.FinancialStatements.IncomeStatement.EBIT.TwelveMonths/security.Fundamentals.FinancialStatements.BalanceSheet.InvestedCapital.TwelveMonths}," \
                                 + f" PEG is {security.Fundamentals.ValuationRatios.NormalizedPEGatio}," \
                                 + f" MarketCap is {security.Fundamentals.MarketCap/1000000}" \
                                 + f" and Volume is {security.Fundamentals.DollarVolume/1000000}")
            
        if len(self.new_symbols) > 0: 
            
            for security in changes.AddedSecurities:
                if security.Fundamentals == None: # i.e. is an ETF/is SPY
                    continue
                
                # AAPL gets added universe, we buy AAPL, AAPL removed from universe, AAPL readded*** (duplicate entry in invested_stocks)
                if security.Symbol not in self.invested_stocks:
                    self.invested_stocks.append(security.Symbol) # add new securities to watchlist
                
        if len(self.invested_stocks) > 0:
            
            # for symbol in self.invested_stocks:
            #     security = self.Securities[symbol]
            #     self.SetHoldings(security.Symbol, 0.9/len(self.invested_stocks)) #0.9 to keep cash buffer
            #     self.Debug(f"Buying {security.Symbol} @ {security.Price}," \
            #                     + f" ROIC is {security.Fundamentals.FinancialStatements.IncomeStatement.EBIT.TwelveMonths/security.Fundamentals.FinancialStatements.BalanceSheet.InvestedCapital.TwelveMonths}," \
            #                     + f" PEG is {security.Fundamentals.ValuationRatios.NormalizedPEGatio}," \
            #                     + f" MarketCap is {security.Fundamentals.MarketCap/1000000}" \
            #                     + f" and Volume is {security.Fundamentals.DollarVolume/1000000}")
            
            for symbol in self.invested_stocks:
                security = self.Securities[symbol]
                self.SetHoldings([PortfolioTarget(security.Symbol, (0.9/len(self.invested_stocks)))]) #0.9 to keep cash buffer
                self.Debug(f"Buying {security.Symbol} @ {security.Price}," \
                                + f" ROIC is {security.Fundamentals.FinancialStatements.IncomeStatement.EBIT.TwelveMonths/security.Fundamentals.FinancialStatements.BalanceSheet.InvestedCapital.TwelveMonths}," \
                                + f" PEG is {security.Fundamentals.ValuationRatios.NormalizedPEGatio}," \
                                + f" MarketCap is {security.Fundamentals.MarketCap/1000000}" \
                                + f" and Volume is {security.Fundamentals.DollarVolume/1000000}")            
    
    # daily data is received at midnight
    def OnData(self, data):
        pass
        
    # this is called according to Schedule.On in Initialize
    def Rebalance(self):
        self.monthly_rebalance = True