Overall Statistics
Total Trades
1
Average Win
0%
Average Loss
0%
Compounding Annual Return
195.727%
Drawdown
49.000%
Expectancy
0
Net Profit
1507.086%
Sharpe Ratio
1.264
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
1.035
Beta
0.037
Annual Standard Deviation
0.821
Annual Variance
0.673
Information Ratio
1.179
Tracking Error
0.827
Treynor Ratio
27.938
Total Fees
$29.84
import numpy as np

### <summary>
### Basic template algorithm simply initializes the date range and cash. This is a skeleton
### framework you can use for designing an algorithm.
### </summary>
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(2015,5,1)  #Set Start Date
        self.SetEndDate(2017,12,1)    #Set End Date
        self.SetCash(10000)           #Set Strategy Cash

        self.SetBrokerageModel(BrokerageName.GDAX)
        self.AddCrypto("LTCUSD", Resolution.Daily)

    def OnData(self, data):
        '''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.

        Arguments:
            data: Slice object keyed by symbol containing the stock data
        '''
        if not self.Portfolio.Invested:
            self.SetHoldings("LTCUSD", 1)