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* Implement ShortableProviderPythonWrapper.cs - Modify AllShortableSymbolsCoarseSelectionRegressionAlgorithm.cs and ShortableProviderOrdersRejectedRegressionAlgorithm.cs to use ShortableProvider from Security and not from the Brokerage model - Add SetShortableProvider() overload method in Security.cs to set a custom shortable provider from Python - Remove AllShortableSymbols() method from LocalDiskShortableProvider.cs - Remove DefaultShortableProvider class - Add regresion algorithms in C# to cover the changes done * Revert "Merge process" This reverts commit 775a4b8ec18e0f1562b72c27203ec0df84c8f675, reversing changes made to bcc3e790f66fe744ea6f4cb2083c3e9d1881ea2f. * Revert "Revert "Merge process"" This reverts commit aa18fb40eec2aa551ab7a81310ba4515270d6c1a. * Solve bug - Add new constructor overload in OpenInterestFutureUniverseSelectionModel.cs that accepts future chain symbol selector as PyObject - Add a private static method in OpenInterestFutureUniverseSelectionModel that converts Python lambda function to Func<DateTime, IEnumerable<Symbol>> - Add a regression algorithm in Python to cover changes. In these case, add Python version of OpenInterestFuturesRegressionAlgorithm.cs * Nit changes * Nit change * Minor docs tweak --------- Co-authored-by: Martin-Molinero <martin@quantconnect.com>
45 lines
2.1 KiB
Python
45 lines
2.1 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 AlgorithmImports import *
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### <summary>
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### Futures framework algorithm that uses open interest to select the active contract.
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### </summary>
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### <meta name="tag" content="regression test" />
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### <meta name="tag" content="futures" />
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="filter selection" />
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class OpenInterestFuturesRegressionAlgorithm(QCAlgorithm):
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expected_expiry_dates = {datetime(2013, 12, 27), datetime(2014,2,26)}
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def Initialize(self):
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self.UniverseSettings.Resolution = Resolution.Tick
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self.SetStartDate(2013,10,8)
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self.SetEndDate(2013,10,11)
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self.SetCash(10000000)
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# set framework models
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universe = OpenInterestFutureUniverseSelectionModel(self, lambda date_time: [Symbol.Create(Futures.Metals.Gold, SecurityType.Future, Market.COMEX)], None, len(self.expected_expiry_dates))
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self.SetUniverseSelection(universe)
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def OnData(self,data):
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if self.Transactions.OrdersCount == 0 and data.HasData:
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matched = list(filter(lambda s: not (s.ID.Date in self.expected_expiry_dates), data.Keys))
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if len(matched) != 0:
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raise Exception(f"{len(matched)}/{len(slice.Keys)} were unexpected expiry date(s): " + ", ".join(list(map(lambda x: x.ID.Date, matched))))
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for symbol in data.Keys:
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self.MarketOrder(symbol, 1)
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elif any(p.Value.Invested for p in self.Portfolio):
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self.Liquidate()
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