| 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 Probabilistic 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 7.122 Tracking Error 0.097 Treynor Ratio 0 Total Fees $0.00 |
class MovingAverageCrossAlgorithm(QCAlgorithm):
'''In this example we look at the canonical 15/30 day moving average cross. This algorithm
will go long when the 15 crosses above the 30 and will liquidate when the 15 crosses
back below the 30.'''
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(2020, 12, 8) #Set Start Date
self.SetEndDate(2020, 12, 10) #Set End Date
self.SetCash(10000) #Set Strategy Cash
# Find more symbols here: http://quantconnect.com/data
#self.SetBrokerageModel(BrokerageName.OandaBrokerage)
self.AddForex("USDAUD",Resolution.Minute, Market.Oanda)
# create a 15 day exponential moving average
self.fast = self.EMA("USDAUD", 7, Resolution.Minute)
# create a 30 day exponential moving average
self.slow = self.EMA("USDAUD", 20, Resolution.Minute)
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["USDAUD"].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.Forex["USDAUD"].Price))
self.SetHoldings("USDAUD", 10.0)
# 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.Forex["USDAUD"].Price))
self.Liquidate("USDAUD")
self.previous = self.Time