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 -0.848 Tracking Error 0.223 Treynor Ratio 0 Total Fees $0.00 Estimated Strategy Capacity $0 Lowest Capacity Asset |
# QC DEMA Rolling Window from AlgorithmImports import * STOCK = 'SPY'; PERIOD = 50; WINDOW = 10; class DemaRollingWindow(QCAlgorithm): def Initialize(self): self.SetStartDate(2020, 1, 31) self.SetEndDate(2021, 10, 20) self.SetWarmUp(5*PERIOD + WINDOW, Resolution.Daily) self.stock = self.AddEquity(STOCK, Resolution.Daily).Symbol self.dema_window = RollingWindow[IndicatorDataPoint](WINDOW) self.DEMA(self.stock, PERIOD).Updated += (lambda sender, updated: self.dema_window.Add(updated)) def OnData(self, data): if self.IsWarmingUp or not self.dema_window.IsReady: return self.Plot("Indicator","DEMA last", self.dema_window[0]) self.Plot("Indicator", "DEMA first", self.dema_window[WINDOW-1]) self.Plot("Indicator", "DEMA mid", self.dema_window[WINDOW//2-1])