Overall Statistics
Total Trades
0
Average Win
0%
Average Loss
0%
Compounding Annual Return
0%
Drawdown
0%
Expectancy
0
Net Profit
0%
Sharpe Ratio
0
Loss Rate
0%
Win Rate
0%
Profit-Loss Ratio
0
Alpha
0
Beta
0
Annual Standard Deviation
0
Annual Variance
0
Information Ratio
0
Tracking Error
0
Treynor Ratio
0
Total Fees
$0.00
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(2018,9, 18)  #Set Start Date
        self.SetEndDate(2018,10,18)    #Set End Date
        self.SetCash(100000)           #Set Strategy Cash
        
        self.Debug("numpy test >>> print numpy.pi: " + str(np.pi))
        
        # Find more symbols here: http://quantconnect.com/data
        eurusd = self.AddForex("EURUSD", Resolution.Daily, Market.Oanda)
        
        self.resolution = Resolution.Daily
        self.donch_period = 7
        self.donchian = self.DCH(eurusd.Symbol, self.donch_period, self.resolution)
        self.RegisterIndicator(eurusd.Symbol, self.donchian, self.resolution)

    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
        '''
        self.Log("High: "+str(data["EURUSD"].High)+" | Donchian IsReady: "+str(self.donchian.IsReady)+" | Donchian Upper: "+str(self.donchian.UpperBand) )