| Overall Statistics |
|
Total Trades 81 Average Win 5.29% Average Loss -2.17% Compounding Annual Return 8.551% Drawdown 18.700% Expectancy 1.060 Net Profit 155.077% Sharpe Ratio 0.829 Probabilistic Sharpe Ratio 24.489% Loss Rate 40% Win Rate 60% Profit-Loss Ratio 2.43 Alpha 0.035 Beta 0.371 Annual Standard Deviation 0.112 Annual Variance 0.012 Information Ratio -0.424 Tracking Error 0.145 Treynor Ratio 0.249 Total Fees $429.53 |
class MovingAverageCrossAlgorithm(QCAlgorithm):
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(2009, 1, 1) #Set Start Date
self.SetEndDate(2020, 5, 28) #Set End Date
self.SetCash(100000) #Set Strategy Cash
# Find more symbols here: http://quantconnect.com/data
self.AddEquity("SPY")
# create a 15 day exponential moving average
self.fast = self.EMA("SPY", 15, Resolution.Daily)
# create a 30 day exponential moving average
self.slow = self.EMA("SPY", 30, Resolution.Daily)
self.previous = None
def OnData(self, data):
'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''
# a couple things to notice in this method:
# 1. We never need to 'update' our indicators with the data, the engine takes care of this for us
# 2. We can use indicators directly in math expressions
# 3. We can easily plot many indicators at the same time
# wait for our slow ema to fully initialize
if not self.slow.IsReady:
return
# only once per day
if self.previous is not None and self.previous.date() == self.Time.date():
return
# define a small tolerance on our checks to avoid bouncing
tolerance = 0.00015
holdings = self.Portfolio["SPY"].Quantity
# we only want to go long if we're currently short or flat
if holdings <= 0:
# if the fast is greater than the slow, we'll go long
if self.fast.Current.Value > self.slow.Current.Value *(1 + tolerance):
self.Log("BUY >> {0}".format(self.Securities["SPY"].Price))
self.SetHoldings("SPY", 1.0)
# we only want to liquidate if we're currently long
# if the fast is less than the slow we'll liquidate our long
if holdings > 0 and self.fast.Current.Value < self.slow.Current.Value:
self.Log("SELL >> {0}".format(self.Securities["SPY"].Price))
self.Liquidate("SPY")
self.previous = self.Time