Hi there,

I have a strategy that uses pre-defined price data for various futures contracts that works fine, but when I update the algorithm to use the Quantconnect continuous futures, the algorithm gives an error about leverage:

Runtime Error: Futures do not allow specifying a leveraged target, since they are traded using margin which already is leveraged. Possible target buying power goes from -1 to 1, target provided is: -1.597480554358317825 in FutureMarginModel.cs:line 118

Here's the code:

  1. from math import ceil
  2. from AlgorithmImports import *
  4. class ReturnsSignalMomentum(QCAlgorithm):
  6.     def Initialize(self):
  7.         self.SetStartDate(2022, 1, 1)
  8.         self.SetCash(100000)
  10.         self.ES_contract = self.AddFuture(Futures.Indices.SP500EMini,
  11.                                           dataNormalizationMode = DataNormalizationMode.BackwardsRatio,
  12.                                           dataMappingMode = DataMappingMode.OpenInterest,
  13.                                           contractDepthOffset = 0)
  14.         self.GC_contract = self.AddFuture(Futures.Metals.Gold,
  15.                                           dataNormalizationMode = DataNormalizationMode.BackwardsRatio,
  16.                                           dataMappingMode = DataMappingMode.OpenInterest,
  17.                                           contractDepthOffset = 0)
  18.         self.CL_contract = self.AddFuture(Futures.Energies.CrudeOilWTI,
  19.                                           dataNormalizationMode = DataNormalizationMode.BackwardsRatio,
  20.                                           dataMappingMode = DataMappingMode.OpenInterest,
  21.                                           contractDepthOffset = 0)
  23.         self.symbols = [
  24.                         self.ES_contract.Symbol,
  25.                         self.GC_contract.Symbol,
  26.                         self.CL_contract.Symbol
  27.                        ]
  29.         #self.symbols = [
  30.         #                "CME_AD1",      # Australian Dollar Futures, Continuous Contract #1
  31.         #                "CME_BP1",      # British Pound Futures, Continuous Contract #1
  32.         #                "CME_EC1",      # Euro FX Futures, Continuous Contract #1
  33.         #                "CME_JY1",      # Japanese Yen Futures, Continuous Contract #1
  35.         #                "ICE_DX1",      # US Dollar Index Futures, Continuous Contract #1
  36.         #                "CME_NQ1",      # E-mini NASDAQ 100 Futures, Continuous Contract #1
  37.         #                "EUREX_FDAX1",  # DAX Futures, Continuous Contract #1
  38.         #                "CME_ES1",      # E-mini S&P 500 Futures, Continuous Contract #1
  40.         #                "CME_GC1",      # Gold Futures, Continuous Contract
  41.         #                "CME_SI1",      # Silver Futures, Continuous Contract
  43.         #                "ICE_CC1",      # Cocoa Futures, Continuous Contract 
  44.         #                "ICE_KC1",      # Coffee C Futures, Continuous Contract
  45.         #                "ICE_SB1",      # Sugar No. 11 Futures, Continuous Contract
  46.                         
  47.         #                "CME_S1",       # Soybean Futures, Continuous Contract
  48.         #                "CME_W1",       # Wheat Futures, Continuous Contract
  49.         #                "CME_C1",       # Corn Futures, Continuous Contract
  51.         #                "CME_LC1",      # Live Cattle Futures, Continuous Contract
  52.         #                "CME_FC1",      # Feeder Cattle Futures, Continuous Contract
  54.         #                "CME_ZB1",
  55.         #                "CME_ZQ1",
  57.         #                "CME_NG1",      # Natural Gas (Henry Hub) Physical Futures, Continuous Contract
  58.         #                "CME_CL1",      
  59.         #                "ICE_O1"        # Heating Oil Futures, Continuous Contract
  60.         #                ]
  61.         
  62.         period = 100
  63.         self.SetWarmUp(period)
  64.         self.dch = {}
  65.         self.atr = {}
  67.         for symbol in self.symbols:
  68.             #data = self.AddData(QuantpediaFutures, symbol, Resolution.Daily)
  69.             data = self.History(symbol, 252, Resolution.Daily)
  70.             #data.SetFeeModel(CustomFeeModel())
  71.             #data.SetLeverage(10)
  72.             
  73.             self.dch[symbol] = self.DCH(symbol, period, Resolution.Daily)
  74.             self.atr[symbol] = self.ATR(symbol, 10, Resolution.Daily)
  75.             
  76.     def OnData(self, data):
  77.         if self.IsWarmingUp: return
  78.         
  79.         dollar_pos_size = {}
  80.         equity = self.Portfolio.TotalPortfolioValue
  81.         
  82.         long = []
  83.         short = []
  84.         for symbol in self.symbols:
  85.             if self.Securities[symbol].GetLastData() and (self.Time.date() - self.Securities[symbol].GetLastData().Time.date()).days >= 5:
  86.                 continue
  88.             if symbol not in data or not data[symbol]: continue
  89.             if not self.dch[symbol].IsReady or not self.atr[symbol].IsReady: continue
  90.         
  91.             price = data[symbol].Price
  92.             atr = self.atr[symbol].Current.Value
  94.             upper_band = self.dch[symbol].UpperBand.Current.Value
  95.             lower_band = self.dch[symbol].LowerBand.Current.Value
  96.             
  97.             # Close position.
  98.             if self.Portfolio[symbol].IsLong:
  99.                 if price < lower_band:
  100.                 #if price < (upper_band - 2*atr):
  101.                     self.Liquidate(symbol)
  102.             if self.Portfolio[symbol].IsShort:
  103.                 if price > upper_band:
  104.                 #if price > (lower_band + 2*atr):
  105.                     self.Liquidate(symbol)
  106.             
  107.             # Calculate positon size.
  108.             #unit_size = (equity * 0.1 * 0.02) / (atr*4)
  109.             unit_size = (equity * 0.1 * 0.02) / (atr)
  110.             
  111.             if price > upper_band:
  112.                 if not self.Portfolio[symbol].IsLong:
  113.                     long.append(symbol)
  114.                     dollar_pos_size[symbol] = unit_size * price
  115.             elif price < lower_band:
  116.                 if not self.Portfolio[symbol].IsShort:
  117.                     short.append(symbol)
  118.                     dollar_pos_size[symbol] = unit_size * price
  119.                 
  120.         # Rebalance opened positions and open new ones.
  121.         for symbol in long + short:
  122.             percentage = dollar_pos_size[symbol] / equity
  123.             if symbol in long: self.SetHoldings(symbol, percentage)
  124.             if symbol in short: self.SetHoldings(symbol, -percentage)
  125.         
  126. # Custom fee model.
  127. class CustomFeeModel(FeeModel):
  128.     def GetOrderFee(self, parameters):
  129.         fee = parameters.Security.Price * parameters.Order.AbsoluteQuantity * 0.00005
  130.         return OrderFee(CashAmount(fee, "USD"))
+ Expand

Besides changing the data source, I also changed the method to access the data from AddData to History:

  1. #data = self.AddData(QuantpediaFutures, symbol, Resolution.Daily)
  2. data = self.History(symbol, 252, Resolution.Daily)

Just wondering, if there is a difference between how price data is returned from AddData versus History.

Please advise.

David

Author

David Lelong

July 2022