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 -0.734 Tracking Error 0.335 Treynor Ratio 0 Total Fees $0.00 Estimated Strategy Capacity $0 Lowest Capacity Asset |
#https://www.quantconnect.com/project/8573135#code-tab-main_py # Sybols #CURE DFEN DPST DRN FAS LABU NAIL PILL RETL TECL UTSL #weights #1 -0.609022204 0.063329879 -1.402526494 -0.076014761 0.121880258 -0.161395148 -1.880186944 0.36683371 -1.632101489 1.980848122 import numpy as np import time import gc gc.enable() class SlowBacktest(QCAlgorithm): def Initialize(self): self.SetStartDate(2020, 1, 1) self.SetEndDate(2020, 12, 30) self.SetCash(100000) self.AddEquity("SPY", Resolution.Minute) self.tickers = ['CURE', 'DFEN', 'DPST', 'DRN', 'FAS', 'LABU', 'NAIL', 'PILL', 'RETL', 'TECL', 'UTSL'] #create symbols self.symbols = [] for ticker in self.tickers: self.symbols.append(Symbol.Create(ticker, SecurityType.Equity, Market.USA)) self.SetUniverseSelection(ManualUniverseSelectionModel(self.symbols)) self.eod =0 self.Schedule.On( self.DateRules.EveryDay("SPY"), self.TimeRules.BeforeMarketClose("SPY", 5), self.get_data ) def get_data(self): #now get latest prices T=self.Time price_list = [] for symbol in self.symbols: price_list.append(self.Securities[symbol.Value].Price) self.Debug(str(T) + ' ' + str(price_list)) def OnData(self, data): T = self.Time if T == self.eod: price_list = [] for symbol in self.symbols: price_list.append(self.Securities[symbol.Value].Price) ''' def get_data2(self, data): #now get latest prices T=self.Time price_list = [] for kvp in data.Bars: symbol = kvp.Key p = kvp.Value.Close price_list.append(p) self.Debug(str(T) + ' ' +str(price_list)) def get_data3(self): T=self.Time self.eod = T '''