Overall Statistics
Total Trades
1
Average Win
0%
Average Loss
0%
Compounding Annual Return
8.602%
Drawdown
18.800%
Expectancy
0
Net Profit
25.027%
Sharpe Ratio
0.561
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
0.206
Beta
-5.431
Annual Standard Deviation
0.174
Annual Variance
0.03
Information Ratio
0.446
Tracking Error
0.174
Treynor Ratio
-0.018
Total Fees
$17.30
 
from QuantConnect.Indicators import *

class BasicTemplateAlgorithm(QCAlgorithm):
    '''Basic template algorithm simply initializes the date range and cash'''

    def Initialize(self):
        '''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''

        self.SetStartDate(2015,9,1)  #Set Start Date
        self.SetEndDate(2018,5,15)    #Set End Date
        self.SetCash(100000)           #Set Strategy Cash
        # Find more symbols here: http://quantconnect.com/data
        self.AddEquity("PFE", Resolution.Daily)
        self.Strength = self.RSI("PFE",14,MovingAverageType.Simple,Resolution.Daily)
        self.SetWarmUp(20)
        self.SetBenchmark("SPY")

    def OnData(self, data):
        rsi = self.Strength.Current.Value
        current = data["PFE"].Close

        #need to check when to go long
        if not self.Portfolio.Invested:
            if rsi < 40:
                self.SetHoldings("PFE", 1)
                self.current = self.Time
            
        if self.Portfolio.Invested:
            if (self.Time - self.current).days == 5:
                    self.Liquidate("PFE")