Aaron Janeiro Stone
7d70698c9a
* Cleans history for ArimaIndicator/TimeSeriesIndicator. -- removes commits from a tracked, already merged branch -- removes artifacts from debugging sessions * Removes AR/MA method as a user-specifiable method. -- Prevents need to reference dll for MathNet in Tests (and potentially elsewhere). -- Wrapper can be implemented around this functionality. * Removes AR/MA method as a user-specifiable method. -- Prevents need to reference dll for MathNet in Tests (and potentially elsewhere). -- Wrapper can be implemented around this functionality. * Better adherence to established code style * Makes _intercept = true by default in constructor where it is not parameter * WIP -- addressing reviews * Passing tests following prior refactor * Rearranged code, access modifiers adjusted * Fixed indexing of _mafits, adds example algorithm * Adds regression algo in python + addresses some refactors * Addresses review * Adds regression stats * Fixes missing value signs * Removes redundant code * style changes * style changes * style: "err" -> "error" * Minor tweaks * Fixes python arima regression test * Refactors AutoregressiveIntegratedMovingAverageTests.cs Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>
52 lines
2.3 KiB
Python
52 lines
2.3 KiB
Python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from clr import AddReference
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AddReference("System")
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AddReference("QuantConnect.Algorithm")
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AddReference("QuantConnect.Common")
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from System import *
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from QuantConnect import *
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from QuantConnect.Algorithm import *
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# <summary>
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# Regression algorithm to test the behaviour of ARMA versus AR models at the same order of differencing.
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# In particular, an ARIMA(1,1,1) and ARIMA(1,1,0) are instantiated while orders are placed if their difference
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# is sufficiently large (which would be due to the inclusion of the MA(1) term).
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# </summary>
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class AutoRegressiveIntegratedMovingAverageRegressionAlgorithm(QCAlgorithm):
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def Initialize(self):
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'''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
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self.SetStartDate(2013, 1, 7)
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self.SetEndDate(2013, 12, 11)
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self.EnableAutomaticIndicatorWarmUp = True
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self.AddEquity("SPY", Resolution.Daily)
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self.arima = self.ARIMA("SPY", 1, 1, 1, 50)
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self.ar = self.ARIMA("SPY", 1, 1, 0, 50)
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def OnData(self, data):
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'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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Arguments:
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data: Slice object keyed by symbol containing the stock data
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'''
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if self.arima.IsReady:
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if abs(self.arima.Current.Value - self.ar.Current.Value) > 1:
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if self.arima.Current.Value > self.last:
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self.MarketOrder("SPY", 1)
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else:
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self.MarketOrder("SPY", -1)
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self.last = self.arima.Current.Value
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