Quantconnect Continuous Futures Error

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:

from math import ceil
from AlgorithmImports import *

class ReturnsSignalMomentum(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2022, 1, 1)
        self.SetCash(100000)

        self.ES_contract = self.AddFuture(Futures.Indices.SP500EMini,
                                          dataNormalizationMode = DataNormalizationMode.BackwardsRatio,
                                          dataMappingMode = DataMappingMode.OpenInterest,
                                          contractDepthOffset = 0)
        self.GC_contract = self.AddFuture(Futures.Metals.Gold,
                                          dataNormalizationMode = DataNormalizationMode.BackwardsRatio,
                                          dataMappingMode = DataMappingMode.OpenInterest,
                                          contractDepthOffset = 0)
        self.CL_contract = self.AddFuture(Futures.Energies.CrudeOilWTI,
                                          dataNormalizationMode = DataNormalizationMode.BackwardsRatio,
                                          dataMappingMode = DataMappingMode.OpenInterest,
                                          contractDepthOffset = 0)

        self.symbols = [
                        self.ES_contract.Symbol,
                        self.GC_contract.Symbol,
                        self.CL_contract.Symbol
                       ]

        #self.symbols = [
        #                "CME_AD1",      # Australian Dollar Futures, Continuous Contract #1
        #                "CME_BP1",      # British Pound Futures, Continuous Contract #1
        #                "CME_EC1",      # Euro FX Futures, Continuous Contract #1
        #                "CME_JY1",      # Japanese Yen Futures, Continuous Contract #1

        #                "ICE_DX1",      # US Dollar Index Futures, Continuous Contract #1
        #                "CME_NQ1",      # E-mini NASDAQ 100 Futures, Continuous Contract #1
        #                "EUREX_FDAX1",  # DAX Futures, Continuous Contract #1
        #                "CME_ES1",      # E-mini S&P 500 Futures, Continuous Contract #1

        #                "CME_GC1",      # Gold Futures, Continuous Contract
        #                "CME_SI1",      # Silver Futures, Continuous Contract

        #                "ICE_CC1",      # Cocoa Futures, Continuous Contract 
        #                "ICE_KC1",      # Coffee C Futures, Continuous Contract
        #                "ICE_SB1",      # Sugar No. 11 Futures, Continuous Contract
                        
        #                "CME_S1",       # Soybean Futures, Continuous Contract
        #                "CME_W1",       # Wheat Futures, Continuous Contract
        #                "CME_C1",       # Corn Futures, Continuous Contract

        #                "CME_LC1",      # Live Cattle Futures, Continuous Contract
        #                "CME_FC1",      # Feeder Cattle Futures, Continuous Contract

        #                "CME_ZB1",
        #                "CME_ZQ1",

        #                "CME_NG1",      # Natural Gas (Henry Hub) Physical Futures, Continuous Contract
        #                "CME_CL1",      
        #                "ICE_O1"        # Heating Oil Futures, Continuous Contract
        #                ]
        
        period = 100
        self.SetWarmUp(period)
        self.dch = {}
        self.atr = {}

        for symbol in self.symbols:
            #data = self.AddData(QuantpediaFutures, symbol, Resolution.Daily)
            data = self.History(symbol, 252, Resolution.Daily)
            #data.SetFeeModel(CustomFeeModel())
            #data.SetLeverage(10)
            
            self.dch[symbol] = self.DCH(symbol, period, Resolution.Daily)
            self.atr[symbol] = self.ATR(symbol, 10, Resolution.Daily)
            
    def OnData(self, data):
        if self.IsWarmingUp: return
        
        dollar_pos_size = {}
        equity = self.Portfolio.TotalPortfolioValue
        
        long = []
        short = []
        for symbol in self.symbols:
            if self.Securities[symbol].GetLastData() and (self.Time.date() - self.Securities[symbol].GetLastData().Time.date()).days >= 5:
                continue

            if symbol not in data or not data[symbol]: continue
            if not self.dch[symbol].IsReady or not self.atr[symbol].IsReady: continue
        
            price = data[symbol].Price
            atr = self.atr[symbol].Current.Value

            upper_band = self.dch[symbol].UpperBand.Current.Value
            lower_band = self.dch[symbol].LowerBand.Current.Value
            
            # Close position.
            if self.Portfolio[symbol].IsLong:
                if price < lower_band:
                #if price < (upper_band - 2*atr):
                    self.Liquidate(symbol)
            if self.Portfolio[symbol].IsShort:
                if price > upper_band:
                #if price > (lower_band + 2*atr):
                    self.Liquidate(symbol)
            
            # Calculate positon size.
            #unit_size = (equity * 0.1 * 0.02) / (atr*4)
            unit_size = (equity * 0.1 * 0.02) / (atr)
            
            if price > upper_band:
                if not self.Portfolio[symbol].IsLong:
                    long.append(symbol)
                    dollar_pos_size[symbol] = unit_size * price
            elif price < lower_band:
                if not self.Portfolio[symbol].IsShort:
                    short.append(symbol)
                    dollar_pos_size[symbol] = unit_size * price
                
        # Rebalance opened positions and open new ones.
        for symbol in long + short:
            percentage = dollar_pos_size[symbol] / equity
            if symbol in long: self.SetHoldings(symbol, percentage)
            if symbol in short: self.SetHoldings(symbol, -percentage)
        
# Custom fee model.
class CustomFeeModel(FeeModel):
    def GetOrderFee(self, parameters):
        fee = parameters.Security.Price * parameters.Order.AbsoluteQuantity * 0.00005
        return OrderFee(CashAmount(fee, "USD"))

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

#data = self.AddData(QuantpediaFutures, symbol, Resolution.Daily)
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