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
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
0
Beta
0
Annual Standard Deviation
0
Annual Variance
0
Information Ratio
0
Tracking Error
0
Treynor Ratio
0
Total Fees
$0.00
 
import numpy as np
import datetime
from scipy import stats 

class Algorithm(QCAlgorithm):
    def Initialize(self):
        self.SetStartDate(2012,1,1)  #Set Start Date
        self.SetEndDate(2012,2,5)    #Set End Date
        self.SetCash(100000)    
        #Set Strategy Cash
        # Find more symbols here: http://quantconnect.com/data
        self.atr_window = 20
        self.symbols = ['ABT', 'ACN', 'ACE', 'ADBE','SPY']
        self.atrDict = {}
        for symbol in self.symbols:
            self.AddEquity(symbol, Resolution.Daily) 
            self.atrDict[symbol]=self.ATR(symbol, self.atr_window )
        self.Schedule.On(self.DateRules.MonthStart("SPY"), 
                         self.TimeRules.AfterMarketOpen("SPY", 60), 
                         Action(self.Rebalance))
    def Rebalance(self):
        if not self.atrDict['ABT'].IsReady:
            self.Debug("not IsReady")
            return
        self.Debug("Ready")
        for symbol in self.symbols:
             averageTrueRange = self.atrDict[symbol].Current.Value
             self.Log(averageTrueRange)