| Overall Statistics |
|
Total Trades 3 Average Win 152.84% Average Loss 0% Compounding Annual Return 701.520% Drawdown 24.200% Expectancy 0 Net Profit 172.676% Sharpe Ratio 2.625 Loss Rate 0% Win Rate 100% Profit-Loss Ratio 0 Alpha 1.312 Beta 22.675 Annual Standard Deviation 0.619 Annual Variance 0.383 Information Ratio 2.603 Tracking Error 0.619 Treynor Ratio 0.072 Total Fees $5.55 |
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 numpy as np
### <summary>
### EMA cross with SP500 E-mini futures
### In this example, we demostrate how to trade futures contracts using
### a equity to generate the trading signals
### It also shows how you can prefilter contracts easily based on expirations.
### It also shows how you can inspect the futures chain to pick a specific contract to trade.
### </summary>
### <meta name="tag" content="using data" />
### <meta name="tag" content="futures" />
### <meta name="tag" content="indicators" />
### <meta name="tag" content="strategy example" />
class FuturesMomentumAlgorithm(QCAlgorithm):
def Initialize(self):
self.SetStartDate(2019, 1, 1)
self.SetEndDate(2019, 6, 25)
self.SetCash(10000)
fastPeriod = 10
slowPeriod = 22
self._tolerance = 1 + 0.001
self.IsUpTrend = False
self.IsDownTrend = False
self.SetWarmUp(max(fastPeriod, slowPeriod))
# Adds SPY to be used in our EMA indicators
equity = self.AddEquity("SPY", Resolution.Daily)
self._fast = self.EMA(equity.Symbol, fastPeriod, Resolution.Daily)
self._slow = self.EMA(equity.Symbol, slowPeriod, Resolution.Daily)
# Adds the future that will be traded and
# set our expiry filter for this futures chain
future = self.AddFuture(Futures.Indices.SP500EMini)
future.SetFilter(timedelta(0), timedelta(182))
def OnData(self, slice):
if self._slow.IsReady and self._fast.IsReady:
self.IsUpTrend = self._fast.Current.Value > self._slow.Current.Value * self._tolerance
self.IsDownTrend = self._fast.Current.Value < self._slow.Current.Value * self._tolerance
if (not self.Portfolio.Invested) and self.IsUpTrend:
for chain in slice.FuturesChains:
# find the front contract expiring no earlier than in 90 days
contracts = list(filter(lambda x: x.Expiry > self.Time + timedelta(90), 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]
self.MarketOrder(contract.Symbol , 1)
if self.Portfolio.Invested and self.IsDownTrend:
self.Liquidate()
def OnEndOfDay(self):
if self.IsUpTrend:
self.Plot("Indicator Signal", "EOD",1)
elif self.IsDownTrend:
self.Plot("Indicator Signal", "EOD",-1)
elif self._slow.IsReady and self._fast.IsReady:
self.Plot("Indicator Signal", "EOD",0)
def OnOrderEvent(self, orderEvent):
self.Log(str(orderEvent))