Overall Statistics
Total Trades
5372
Average Win
0.12%
Average Loss
-0.10%
Compounding Annual Return
-42.680%
Drawdown
29.700%
Expectancy
-0.128
Net Profit
-29.676%
Sharpe Ratio
-3.285
Loss Rate
60%
Win Rate
40%
Profit-Loss Ratio
1.19
Alpha
-0.364
Beta
-1.066
Annual Standard Deviation
0.115
Annual Variance
0.013
Information Ratio
-3.405
Tracking Error
0.115
Treynor Ratio
0.355
Total Fees
$9938.20
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

from clr import AddReference
AddReference("System")
AddReference("QuantConnect.Algorithm")
AddReference("QuantConnect.Common")

from System import *
from QuantConnect import *
from QuantConnect.Algorithm import *
from QuantConnect.Securities import *
from datetime import timedelta
import decimal as d
import numpy as np


class FuturesMomentumAlgorithm(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2016, 1, 1)
        self.SetEndDate(2016, 8, 18)
        self.SetCash(100000)
        fastPeriod = 20
        slowPeriod = 60
        self._tolerance = d.Decimal(1 + 0.001)
        self.IsUpTrend = False
        self.IsDownTrend = False
        self.SetWarmUp(max(fastPeriod, slowPeriod))
        
        self.SetBrokerageModel(BrokerageName.InteractiveBrokersBrokerage)

        # Adds SPY to be used in our EMA indicators
        equity = self.AddEquity("SPY", Resolution.Daily)
        
        ## SP500 Emini futures
        future = self.AddFuture(Futures.Indices.SP500EMini)
        future.SetFilter(timedelta(0), timedelta(90))


    def OnData(self, slice):
        for chain in slice.FuturesChains:
            # find the front contract expiring no earlier than in 30 days
            contracts = list(filter(lambda x: x.Expiry > self.Time + timedelta(30), chain.Value))
            # if there is any contract, trade the front contract
            if len(contracts) == 0: continue
            contract = sorted(contracts, key = lambda x: x.Expiry, reverse=True)[0]
            
            ## VERY arbitrary code: buy every hour on the 15-min, sell 30min later
            if self.Time.minute == 15:
                self.MarketOrder(contract.Symbol, 1)
            if self.Time.minute == 45:
                self.MarketOrder(contract.Symbol, -1)

    def OnOrderEvent(self, orderEvent):
        self.Log(str(orderEvent))