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 -1.938 Tracking Error 0.147 Treynor Ratio 0 Total Fees $0.00 Estimated Strategy Capacity $0 Lowest Capacity Asset |
# ScipyStatsLinearRegression v2 from scipy import stats class ScipyStatsLinearRegression(QCAlgorithm): def Initialize(self): self.SetStartDate(2020, 8, 23) self.SetEndDate(2021, 5, 27) self.cap = 100000 self.SetCash(self.cap) self.PERIOD = 42 self.OFFSET = 5 self.STK = self.AddEquity('QQQ', Resolution.Daily).Symbol self.SetWarmUp(self.PERIOD + 1) def OnData(self, data): prices = self.History(self.STK, self.PERIOD, Resolution.Daily)['close'] y = [float(data) for data in prices] x = [range(len(y))] slope, intercept = stats.linregress(x, y)[0], stats.linregress(x, y)[1] linreg = (intercept + slope*(self.PERIOD - 1 - self.OFFSET)) self.Plot('Indicator', 'linreg', round(linreg, 4)) self.Plot('Indicator', 'prices', prices.iloc[-1])