Overall Statistics |
Total Trades 3 Average Win 509.46% Average Loss 0% Compounding Annual Return 6138.676% Drawdown 51.300% Expectancy 0 Net Profit 633.087% Sharpe Ratio 2.736 Loss Rate 0% Win Rate 100% Profit-Loss Ratio 0 Alpha 3.247 Beta 30.099 Annual Standard Deviation 1.339 Annual Variance 1.792 Information Ratio 2.725 Tracking Error 1.339 Treynor Ratio 0.122 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(3000) 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))