Overall Statistics |
Total Trades 460 Average Win 0.02% Average Loss -0.04% Compounding Annual Return -3.626% Drawdown 4.800% Expectancy -0.416 Net Profit -4.721% Sharpe Ratio -4.604 Probabilistic Sharpe Ratio 0.000% Loss Rate 61% Win Rate 39% Profit-Loss Ratio 0.51 Alpha -0.029 Beta -0.004 Annual Standard Deviation 0.006 Annual Variance 0 Information Ratio -0.537 Tracking Error 0.259 Treynor Ratio 8.397 Total Fees $640.46 |
class CalibratedUncoupledCoreWave(QCAlgorithm): def Initialize(self): self.SetStartDate(2019,1, 1) # Set Start Date #self.SetEndDate(2016, 12, 12) # Set End Date self.SetCash(100000) # Set Strategy Cash # Set the resolution of your data self.UniverseSettings.Resolution = Resolution.Minute # Add the universes self.AddUniverse(self.SelectCoarse,self.SelectFine) # Liquidate all positions before the market close each day self.Schedule.On(self.DateRules.Every(DayOfWeek.Monday, DayOfWeek.Tuesday,DayOfWeek.Wednesday, DayOfWeek.Thursday,DayOfWeek.Friday), self.TimeRules.At(15, 30), self.ClosePositions) # Store yesterday's close in a dictionary for reference in the SelectFine Function self.coarseclose={} # Store yesterday's close on fine filtered stocks to reference them in the OnData function self.fineclose={} # Ensure only 1 trade per day per stock self.traded={} # Ensure each level of profit taking is only executed once per stock per day self.pt1={} self.pt2={} self.pt3={} self.pt4={} # Only enter a trade if today's price is above yesterday's close * self.targetentry self.targetentry=2.00 def SelectCoarse(self, coarse): # Penny Stock filter myuniverse = [x for x in coarse if x.HasFundamentalData and x.DollarVolume > 1000000 \ and x.DollarVolume < 5000000 and x.Price > 0 and x.Price <= 5.0] stocks = {x.Symbol: x for x in myuniverse} # Clear the dictionary each day before re-populating it self.coarseclose.clear() # Load the dictionary with yesterday's close for each filtered stock for c in myuniverse: self.coarseclose[c.Symbol] = c.AdjustedPrice # Return filtered stocks for further filtering by the SelecFine function return list(stocks.keys()) def SelectFine(self,fine): ''' This function takes the stock of the CoarceFundamental function and narrow the list adding specific fundamental filters Largely to ensure that only common stock is traded and not EG Preference Shares or ETFs ''' fine_filter = [x.Symbol for x in fine if x.SecurityReference.IsPrimaryShare == 1 and x.SecurityReference.SecurityType == 'ST00000001' and x.CompanyReference.IsLimitedPartnership == 0 and x.SecurityReference.IsDepositaryReceipt == 0 ] self.fineclose.clear() self.traded.clear() self.pt1.clear() self.pt2.clear() self.pt3.clear() self.pt4.clear() self.pt1={k: 0 for k in fine_filter} self.pt2={k: 0 for k in fine_filter} self.pt3={k: 0 for k in fine_filter} self.pt4={k: 0 for k in fine_filter} self.fineclose = {k: self.coarseclose[k] for k in fine_filter} self.traded = {k: 0 for k in fine_filter} return fine_filter def OnData(self, data): '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here. Arguments: data: Slice object keyed by symbol containing the stock data ''' for kvp in data.Bars: symbol = kvp.Key close = kvp.Value.Close dollarvolume=kvp.Value.Close*kvp.Value.Volume if kvp.Key in self.fineclose.keys(): target =self.fineclose[kvp.Key]*self.targetentry if self.Portfolio[symbol].Quantity == 0.0: if kvp.Key in self.traded.keys(): if self.traded[symbol] == 0: if close>=target: if self.Time.hour <= 10 and self.Time.minute <=29: if dollarvolume >= 50000: self.traded[symbol]=1 #self.SetHoldings(symbol, (min(1/len(self.traded),0.01))) self.SetHoldings(symbol,0.01 ) if self.Portfolio[symbol].Invested: cost = round(self.Portfolio[symbol].AveragePrice,3) profittarget1 = cost * 1.05 profittarget2 = cost * 1.10 profittarget3 = cost * 1.15 profittarget4 = cost * 1.20 stoploss = cost * 0.95 quantity=self.Portfolio[symbol].Quantity if self.Time.hour <= 15 and self.Time.minute <=29: if close>= profittarget1 and self.pt1[symbol] == 0: self.MarketOrder(symbol, -(quantity*0.25)) self.pt1[symbol] = 1 if close>= profittarget2 and self.pt2[symbol] == 0: self.MarketOrder(symbol, -(quantity*0.33)) self.pt2[symbol] = 1 if close>= profittarget3 and self.pt3[symbol] == 0: self.MarketOrder(symbol, -(quantity*0.50)) self.pt3[symbol] = 1 if close>= profittarget4 and self.pt4[symbol] == 0: self.Liquidate() self.pt4[symbol] = 1 if self.Time.hour <= 15 and self.Time.minute <=29: if (close <= stoploss):self.Liquidate() def ClosePositions(self): if self.Portfolio.Invested: self.Liquidate()