Overall Statistics |
Total Trades 225 Average Win 0.08% Average Loss -0.03% Compounding Annual Return -1.961% Drawdown 1.400% Expectancy -0.025 Net Profit -0.161% Sharpe Ratio -0.408 Loss Rate 72% Win Rate 28% Profit-Loss Ratio 2.43 Alpha -0.06 Beta 0.178 Annual Standard Deviation 0.047 Annual Variance 0.002 Information Ratio -3.574 Tracking Error 0.07 Treynor Ratio -0.108 Total Fees $235.50 |
# # 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 # # REFERENCES # data consolidation - https://github.com/QuantConnect/Lean/blob/master/Algorithm.Python/DataConsolidationAlgorithm.py from clr import AddReference AddReference("System") AddReference("QuantConnect.Algorithm") AddReference("QuantConnect.Indicators") AddReference("QuantConnect.Common") from System import * from QuantConnect import * from QuantConnect.Algorithm import * from QuantConnect.Indicators import * from QuantConnect.Data.Market import * from QuantConnect.Data.Consolidators import * from datetime import timedelta import numpy as np class DataConsolidationAlgorithm(QCAlgorithm): '''Example algorithm giving an introduction into using IDataConsolidators. This is an advanced QC concept and requires a certain level of comfort using C# and its event system. What is an IDataConsolidator? IDataConsolidator is a plugin point that can be used to transform your data more easily. In this example we show one of the simplest consolidators, the TradeBarConsolidator. This type is capable of taking a timespan to indicate how long each bar should be, or an integer to indicate how many bars should be aggregated into one. When a new 'consolidated' piece of data is produced by the IDataConsolidator, an event is fired with the argument of the new data. If you are unfamiliar with C# events, or events in general, you may find this useful. This is Microsoft's overview of events in C# http://msdn.microsoft.com/en-us/library/aa645739%28v=vs.71%29.aspx''' 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(2017,01,01) #Set Start Date self.SetEndDate(2017,01,30) #Set End Date self.spy = self.AddEquity("SPY").Symbol # define our 30 minute trade bar consolidator. we can # access the 30 minute bar from the DataConsolidated events thirtyMinuteConsolidator = TradeBarConsolidator(TimeSpan.FromMinutes(30)) # attach our event handler. the event handler is a function that will # be called each time we produce a new consolidated piece of data. thirtyMinuteConsolidator.DataConsolidated += self.ThirtyMinuteBarHandler # this call adds our 30 minute consolidator to # the manager to receive updates from the engine self.SubscriptionManager.AddConsolidator(self.spy, thirtyMinuteConsolidator) # here we'll define a slightly more complex consolidator. what we're trying to produce is # a 3 day bar. Now we could just use a single TradeBarConsolidator like above and pass in # TimeSpan.FromDays(3), but in reality that's not what we want. For time spans of longer than # a day we'll get incorrect results around weekends and such. What we really want are tradeable # days. So we'll create a daily consolidator, and then wrap it with a 3 count consolidator. # first define a one day trade bar -- this produces a consolidated piece of data after a day has passed oneDayConsolidator = TradeBarConsolidator(TimeSpan.FromDays(1)) # next define our 3 count trade bar -- this produces a consolidated piece of data after it sees 3 pieces of data threeCountConsolidator = TradeBarConsolidator(3) # here we combine them to make a new, 3 day trade bar. The SequentialConsolidator allows composition of # consolidators. It takes the consolidated output of one consolidator (in this case, the oneDayConsolidator) # and pipes it through to the threeCountConsolidator. His output will be a 3 day bar. three_oneDayBar = SequentialConsolidator(oneDayConsolidator, threeCountConsolidator) # attach our handler three_oneDayBar.DataConsolidated += self.ThreeDayBarConsolidatedHandler # this call adds our 3 day to the manager to receive updates from the engine self.SubscriptionManager.AddConsolidator(self.spy, three_oneDayBar) self.__last = None def OnData(self, data): '''We need to declare this method''' pass def OnEndOfDay(self): # close up shop each day and reset our 'last' value so we start tomorrow fresh self.Liquidate(self.spy) self.__last = None def ThirtyMinuteBarHandler(self, sender, bar): '''This is our event handler for our 30 minute trade bar defined above in Initialize(). So each time the consolidator produces a new 30 minute bar, this function will be called automatically. The 'sender' parameter will be the instance of the IDataConsolidator that invoked the event, but you'll almost never need that!''' self.Log("SPY close at {0} = {1}".format(bar.Time, bar.Close)) if self.__last is not None and bar.Close > self.__last.Close: self.Log("{0} >> SPY >> LONG >> 100 >> {1}".format(bar.Time, self.Portfolio[self.spy].Quantity)) self.Order(self.spy, 100) elif self.__last is not None and bar.Close < self.__last.Close: self.Log("{0} >> SPY >> SHORT >> 100 >> {1}".format(bar.Time, self.Portfolio[self.spy].Quantity)) self.Order(self.spy, -100) self.__last = bar def ThreeDayBarConsolidatedHandler(self, sender, bar): ''' This is our event handler for our 3 day trade bar defined above in Initialize(). So each time the consolidator produces a new 3 day bar, this function will be called automatically. The 'sender' parameter will be the instance of the IDataConsolidator that invoked the event, but you'll almost never need that!''' self.Log("{0} >> Plotting!".format(bar.Time)) self.Plot(bar.Symbol.Value, "3HourBar", bar.Close)