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
 
#
#   QuantConnect Basic Template:
#	Fundamentals to using a QuantConnect algorithm.
#
#	You can view the QCAlgorithm base class on Github: 
#	https://github.com/QuantConnect/Lean/tree/master/Algorithm
#

import numpy as np

class BasicTemplateAlgorithm(QCAlgorithm):

	def Initialize(self):
		self.SetCash(100000)
		
		self.SetStartDate(2016,1,5)
		self.SetEndDate(2017,1,1)
		
		self.AddSecurity(SecurityType.Equity, "IBM", Resolution.Daily)
		self.AddSecurity(SecurityType.Equity, "GOOG", Resolution.Daily)
		self._count = 0


	def OnData(self, slice):
		if not self._count: 
			self.SetHoldings(self.Securities["IBM"].Symbol, 0.5)
			self.Liquidate(self.Securities["IBM"].Symbol)
			self._count+=1