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 -21.597 Tracking Error 0.111 Treynor Ratio 0 Total Fees $0.00 Estimated Strategy Capacity $0 Lowest Capacity Asset Portfolio Turnover 0% |
# region imports from AlgorithmImports import * import xgboost as xgb import joblib # endregion class XGBoostExampleAlgorithm(QCAlgorithm): def Initialize(self): self.SetStartDate(2022, 7, 4) self.SetEndDate(2022, 7, 8) self.SetCash(100000) self.AddUniverse(self.CoarseFilterFunction) self.u_symbols = [i.Value for i in self.ActiveSecurities.Keys] self.df = self.History(self.u_symbols, 30) def CoarseFilterFunction(self, coarse: List[CoarseFundamental]) -> List[Symbol]: sorted_by_dollar_volume = sorted(coarse, key=lambda x: x.DollarVolume, reverse=True) return [c.Symbol for c in sorted_by_dollar_volume[:10]] def OnData(self, slice: Slice) -> None: keys = [key for key in self.ActiveSecurities.Keys] data = self.History(keys, 5, Resolution.Minute) self.Log(data) def OnEndOfAlgorithm(self): self.ObjectStore.Save("price-models/history", self.df.sort_index().to_csv())