Overall Statistics |
Total Trades 0 Average Win 0% Average Loss 0% Compounding Annual Return 0% Drawdown 0% Expectancy 0 Net Profit 0% Sharpe Ratio 0 Probabilistic Sharpe Ratio 0% Loss Rate 0% Win Rate 0% Profit-Loss Ratio 0 Alpha 0 Beta 0 Annual Standard Deviation 0 Annual Variance 0 Information Ratio -0.381 Tracking Error 0.176 Treynor Ratio 0 Total Fees $0.00 Estimated Strategy Capacity $0 Lowest Capacity Asset |
# region imports from AlgorithmImports import * # endregion class FocusedMagentaDogfish(QCAlgorithm): def Initialize(self): self.SetStartDate(2010, 9, 20) self.SetEndDate(2011, 12, 16) self.SetCash(100000) future = self.AddFuture(Futures.Energies.CrudeOilWTI, Resolution.Minute, fillDataForward=True, extendedMarketHours = True, dataNormalizationMode = DataNormalizationMode.Raw, dataMappingMode = DataMappingMode.LastTradingDay, contractDepthOffset = 0) future.SetFilter(0, 365) self.future_symbol = future.Symbol self.not_missing_chain_count = 0 self.missing_chain_count = 0 def OnData(self, slice: Slice) -> None: chain = slice.FuturesChains.get(self.future_symbol) if chain: self.not_missing_chain_count += 1 else: self.missing_chain_count += 1 def OnEndOfAlgorithm(self): self.Debug(f"Missing FuturesChains: {self.missing_chain_count}; Not missing: {self.not_missing_chain_count}")