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Hi there,
I try to write a pairs trading strategy based on co-integration. This is supposed to be fun project to learn qc datastructur etc.. Unfortunately I do run into various troubles all the time. Maybe someone could help me with this one. In the current algo, I have created two rolling windows. Data should be only added if both assets are present in the onData dataset. If the Windows are ready, cointegration would be estimated. However, this never happens. Any thoughs on that? Note: the SPY position is only for testing since I am also not able to get any log messages to work.
Gurumeher Sawhney
Thanks for sending the code! Since the event handler OnData(self, data) was lowercase in the code, QCAlgorithm was actually not able to find the method. As a result, the algorithm did not run any other code after initializing. In OnData there were some minor errors in the conditional statements. It is important to note that IsReady is a property of the RollingWindow, not a callable function. Now the RollingWindow is being populated and the strategy portion of the algorithm is running. The code below should get you started. In the files, I noticed a PortfolioConstructionModel and AlphaModel. That is part of QuantConnect's algorithm framework and if they are used the algorithm will need to extend from QCAlgorithmFramework, not QCAlgorithm. The link below will have more documentation on using the framework you end up going in that direction.
class LongShortCointegrationPairs(QCAlgorithm): def Initialize(self): self.asset1 = 'SPY' self.asset2 = 'IWM' self.periods = 10 self.SetStartDate(2002, 1, 1) #Set Start Date self.SetEndDate(2005, 12, 31) #Set End Date self.SetCash(10000) #Set Strategy Cash for sym in [self.asset1, self.asset2]: self.AddEquity(sym, Resolution.Daily) self.p1 = RollingWindow[float](self.periods) self.p2 = RollingWindow[float](self.periods) self.weights = None def OnData(self, data): # check if prices for both asset are present if data[self.asset1] and data[self.asset2]: self.p1.Add(data[self.asset1].Close) self.p2.Add(data[self.asset2].Close) else: return None if self.p1.IsReady and self.p2.IsReady and self.weights is None: self.Debug("enter strategy") arr = np.matrix([self.p1[:], self.p2[:]]).T self.weights = calculate_cointegration_weights(arr) self.SetHoldings("SPY", 1)Sebastian Groß
Hi, thanks for fixing my bugs. I would have not be able to find the lower case by myself. I will most certainly use the Framework more extensively in the future, but am still not familiar enough with all the classes and functions required. Thus I wanted to implemt a more simplistic version.
Sebastian Groß
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