Overall Statistics
Total Trades
32
Average Win
25.85%
Average Loss
-2.83%
Compounding Annual Return
121.434%
Drawdown
24.800%
Expectancy
6.610
Net Profit
992.386%
Sharpe Ratio
1.675
Loss Rate
25%
Win Rate
75%
Profit-Loss Ratio
9.15
Alpha
0.004
Beta
44.335
Annual Standard Deviation
0.367
Annual Variance
0.135
Information Ratio
1.637
Tracking Error
0.367
Treynor Ratio
0.014
Total Fees
$4649.16
 
from QuantConnect.Indicators import *


class BollingerMomentum(QCAlgorithm):

    def Initialize(self):

        self.SetStartDate(2016, 1, 1)  #Set Start Date
        self.SetEndDate(2019, 1, 1)    #Set End Date
        self.SetCash(10000)           #Set Strategy Cash
        self.SetBrokerageModel(BrokerageName.GDAX,AccountType.Cash)
        self.AddCrypto("BTCUSD", Resolution.Daily)
        
        ## Set Boilinger Bands
        self.bband = self.BB("BTCUSD", 20, 2, MovingAverageType.Simple, Resolution.Daily)

        # Set WarmUp period
        self.SetWarmUp(20)
        

    def OnData(self, data):
        
        price = self.Securities["BTCUSD"].Close
        
        ## BUY if price is larger than upper band
        if not self.Portfolio['BTCUSD'].Invested and price > self.bband.UpperBand.Current.Value:
                self.SetHoldings("BTCUSD",1)

        ## Liquidate if price is less than middle band        
        if self.Portfolio['BTCUSD'].Invested and price < self.bband.MiddleBand.Current.Value:
                self.Liquidate()