Overall Statistics
Total Trades
16
Average Win
0.06%
Average Loss
-0.02%
Compounding Annual Return
0.221%
Drawdown
0.100%
Expectancy
1.180
Net Profit
0.221%
Sharpe Ratio
1.008
Probabilistic Sharpe Ratio
50.513%
Loss Rate
38%
Win Rate
62%
Profit-Loss Ratio
2.49
Alpha
0.001
Beta
0.005
Annual Standard Deviation
0.002
Annual Variance
0
Information Ratio
-2.61
Tracking Error
0.056
Treynor Ratio
0.33
Total Fees
$34.40
Estimated Strategy Capacity
$300000000.00
Lowest Capacity Asset
ES WSVU0MELFS3L
 
from AlgorithmImports import *
import datetime


class ThisIsATest(QCAlgorithm):

    def Initialize(self):
        self.SetStartDate(2017, 1, 1)
        self.SetEndDate(2018, 1, 1)
        self.SetCash(500000)
        self._continuousContract = self.AddFuture(Futures.Indices.SP500EMini,
                                                  resolution=Resolution.Minute)
        # self._continuousContract.SetFilter(0, 182)
        self._continuousContract.SetFilter(lambda future_filter_universe: future_filter_universe.FrontMonth())

    def OnData(self, data):

        time_long = datetime.time(23, 30) <= self.Time.time() or self.Time.time() < datetime.time(0, 30)

        if not self.Portfolio.Invested and time_long:
            self.Debug(f"Buy now: {self.Time.time()}")
            self.MarketOrder(self._continuousContract.Mapped, 1)
        elif self.Portfolio.Invested and not time_long:
            self.Debug(f"Liquidate now: {self.Time.time()}")
            self.Liquidate()