Overall Statistics
Total Trades
205
Average Win
16.07%
Average Loss
-3.51%
Compounding Annual Return
120.366%
Drawdown
45.300%
Expectancy
1.079
Net Profit
1567.261%
Sharpe Ratio
1.367
Probabilistic Sharpe Ratio
81.214%
Loss Rate
63%
Win Rate
37%
Profit-Loss Ratio
4.58
Alpha
0.671
Beta
-0.129
Annual Standard Deviation
0.481
Annual Variance
0.232
Information Ratio
1.125
Tracking Error
0.495
Treynor Ratio
-5.116
Total Fees
$62621.30
from QuantConnect.Indicators import *
import decimal as d

### <summary>
### In this example we are looking for price to breakout above the bollinger bands
### and look to buy when we see that. We hold our position until price touches the 
### middle band of the bollinger bands.
###

class BollingerBreakoutAlgorithm(QCAlgorithm):

    def Initialize(self):

        self.SetStartDate(2016, 6, 1)  #Set Start Date
        #self.SetEndDate(2017, 7, 1)    #Set End Date
        self.SetCash(10000)             #Set Strategy Cash
        self.SetBrokerageModel(BrokerageName.GDAX, AccountType.Cash )
        
        # define crypto we want to trade on
        # ETHUSD, LTCUSD or BTCUSD
        self.target_crypto = "BTCUSD"
        
        self.AddCrypto(self.target_crypto, Resolution.Daily)
        
        # create a bollinger band
        self.Bolband = self.BB(self.target_crypto, 3, 0.1, MovingAverageType.Exponential, Resolution.Daily)

        # Plot Bollinger band
        self.PlotIndicator(
            "Indicators",
            self.Bolband.LowerBand,
            self.Bolband.MiddleBand,
            self.Bolband.UpperBand,
        )
 
        # create a momentum indicator over 3 days
        self.mom = self.MOM(self.target_crypto, 5)
        
        # Plot Momentum
        self.PlotIndicator(
            "Indicators",
            self.mom
        )

        # set warmup period
        self.SetWarmUp(20)
        

    def OnData(self, data):
        #if self.Time == (2018, 8, 10):
            
        holdings = self.Portfolio[self.target_crypto].Quantity
        price = self.Securities[self.target_crypto].Close
        mom = self.mom.Current.Value
        
        # buy if price closes above upper bollinger band
        if holdings <= 0:
             if price > self.Bolband.LowerBand.Current.Value and mom > 0:
                    self.SetHoldings(self.target_crypto, 1.0)
        
        # sell if price closes below middle bollinger band
        if holdings > 0 and price < self.Bolband.MiddleBand.Current.Value and mom < 0:
                self.Liquidate()