Overall Statistics
Total Trades
1
Average Win
0%
Average Loss
0%
Compounding Annual Return
-98.121%
Drawdown
5.800%
Expectancy
0
Net Profit
-5.127%
Sharpe Ratio
-9.527
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
0
Beta
-189.459
Annual Standard Deviation
0.229
Annual Variance
0.052
Information Ratio
-9.573
Tracking Error
0.229
Treynor Ratio
0.011
Total Fees
$1.74
 
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(2018,10, 7)  #Set Start Date
        self.SetEndDate(2018,10,11)    #Set End Date
        self.SetCash(100000)           #Set Strategy Cash
        # Find more symbols here: http://quantconnect.com/data
        self.AddOption("SPY", Resolution.Second)
        self.Debug("numpy test >>> print numpy.pi: " + str(np.pi))

    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("SPY", 1)