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