Overall Statistics
Total Trades
3797
Average Win
0.05%
Average Loss
-0.07%
Compounding Annual Return
10.896%
Drawdown
13.100%
Expectancy
0.169
Net Profit
20.904%
Sharpe Ratio
0.875
Loss Rate
36%
Win Rate
64%
Profit-Loss Ratio
0.81
Alpha
0.213
Beta
-7.448
Annual Standard Deviation
0.103
Annual Variance
0.011
Information Ratio
0.716
Tracking Error
0.103
Treynor Ratio
-0.012
Total Fees
$4295.04
 
class CoarseFineFundamentalComboAlgorithm(QCAlgorithm):

    def Initialize(self):

        self.SetStartDate(2017,1,1)  
        self.SetEndDate(2018,11,1)    
        self.SetCash(500000)           
        self.UniverseSettings.Resolution = Resolution.Daily
        self.AddEquity("SPY", Resolution.Minute)
        self.do_update_fundamentals = 0
        self.do_update_signals = 0 
        self.AddUniverse(self.CoarseSelectionFunction, self.FineSelectionFunction)
        self.Schedule.On(self.DateRules.Every(DayOfWeek.Monday, DayOfWeek.Monday), self.TimeRules.At(0, 0), Action(self.UpdateFundamentals))
        self.Schedule.On(self.DateRules.Every(DayOfWeek.Monday, DayOfWeek.Monday), self.TimeRules.AfterMarketOpen("SPY", 37), Action(self.UpdateSignals))
        self.long = None
    def CoarseSelectionFunction(self, coarse):
        if self.do_update_fundamentals:
            sortedByDollarVolume = sorted(coarse, key=lambda x: x.DollarVolume, reverse=True)
            return [ x.Symbol for x in sortedByDollarVolume[:100] ]
        else:
            return []

    def FineSelectionFunction(self, fine):
        if self.do_update_fundamentals:
            sortedByPeRatio = sorted(fine, key=lambda x: x.ValuationRatios.PriceChange1M, reverse=True)
            self.do_update_fundamentals = 0
            self.long = [ x.Symbol for x in sortedByPeRatio[:40]]
            for i in self.long:
                self.AddEquity(i.Value, Resolution.Daily)
            return self.long 
        else:
            return []

    def OnData(self, data):
        if self.do_update_signals and self.long:
            invested = [x.Key for x in self.Portfolio if x.Value.Invested]
            for i in invested:
                if i not in self.long:
                    self.Liquidate(i)
            for i in self.long:
                self.SetHoldings(i, 0.8/(len(self.long)))
            self.do_update_signals = 0
    
    def UpdateFundamentals(self):
        self.do_update_fundamentals = 1
        
    def UpdateSignals(self):
        self.do_update_signals = 1