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
-1.476
Tracking Error
0.166
Treynor Ratio
0
Total Fees
$0.00
 
# ScipyStatsLinearRegression

from scipy import stats

class ScipyStatsLinearRegression(QCAlgorithm):

    def Initialize(self):
        
        self.SetStartDate(2020, 8, 23)     
        self.SetEndDate(2020, 12, 24)        
        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])