Louis Szeto
020cf013df
* CustomDataRegressionAlgorithm * DescendingCustomDataObjectStoreRegressionAlgorithm * CustomDataPropertiesRegressionAlgorithm * DateTime -> should be datetime * KerasNeuralNetworkAlgorithm * OptionIndicatorsMirrorContractsRegressionAlgorithm * BybitCustomDataCryptoRegressionAlgorithm * DropboxBaseDataUniverseSelectionAlgorithm * UserDefinedUniverseAlgorithm * CompleteOrderTagUpdateAlgorithm * BasicTemplateOptionEquityStrategyAlgorithm hint * ETFConstituentUniverseFrameworkRegressionAlgorithm * FutureStopMarketOrderOnExtendedHoursRegressionAlgorithm * SecurityDynamicPropertyPythonClassAlgorithm * hint * hinting * CallbackCommandRegressionAlgorithm * CustomWarmUpPeriodIndicatorAlgorithm * CrunchDAOSignalExportDemonstrationAlgorithm * ExpiryHelperAlphaModelFrameworkAlgorithm * ClassicRenkoConsolidatorAlgorithm * SmaCrossUniverseSelectionAlgorithm * PEP8 Fix: Assigning to a Method * SliceGetByTypeRegressionAlgorithm * MarketOnCloseOrderBufferExtendedMarketHoursRegressionAlgorithm * MarketOnCloseOrderBufferRegressionAlgorithm * CustomIndicatorAlgorithm * ScheduledQueuingAlgorithm * ComboOrdersFillModelAlgorithm * CustomIndicatorWithExtensionAlgorithm * IndicatorWithRenkoBarsRegressionAlgorithm * CoarseFineOptionUniverseChainRegressionAlgorithm * NumeraiSignalExportDemonstrationAlgorithm * DropboxUniverseSelectionAlgorithm * WeeklyUniverseSelectionRegressionAlgorithm * AutoRegressiveIntegratedMovingAverageRegressionAlgorithm * DropboxBaseDataUniverseSelectionAlgorithm * IronCondorStrategyAlgorithm * LongAndShortButterflyPutStrategiesAlgorithm * FutureStopMarketOrderOnExtendedHoursRegressionAlgorithm * LongAndShortCallCalendarSpreadStrategiesAlgorithm * KerasNeuralNetworkAlgorithm * LongAndShortPutCalendarSpreadStrategiesAlgorithm * OptionPriceModelForOptionStylesBaseRegressionAlgorithm * TensorFlowNeuralNetworkAlgorithm * MarketOnCloseOrderBufferRegressionAlgorithm * MarketOnCloseOrderBufferExtendedMarketHoursRegressionAlgorithm * typing * ComboOrderTicketDemoAlgorithm * PytorchNeuralNetworkAlgorithm * MultipleSymbolConsolidationAlgorithm * fixes * revert getattr mypy syntax * address peer review * Addresses Peer-Review --------- Co-authored-by: Alexandre Catarino <AlexCatarino@users.noreply.github.com>
65 lines
3.5 KiB
Python
65 lines
3.5 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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import itertools
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from OptionStrategyFactoryMethodsBaseAlgorithm import *
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### <summary>
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### This algorithm demonstrate how to use OptionStrategies helper class to batch send orders for common strategies.
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### In this case, the algorithm tests the Put Calendar Spread and Short Put Calendar Spread strategies.
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### </summary>
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class LongAndShortPutCalendarSpreadStrategiesAlgorithm(OptionStrategyFactoryMethodsBaseAlgorithm):
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def expected_orders_count(self) -> int:
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return 4
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def trade_strategy(self, chain: OptionChain, option_symbol: Symbol) -> None:
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put_contracts = sorted((contract for contract in chain if contract.right == OptionRight.PUT),
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key=lambda x: abs(x.strike - chain.underlying.value))
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for strike, group in itertools.groupby(put_contracts, lambda x: x.strike):
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contracts = sorted(group, key=lambda x: x.expiry)
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if len(contracts) < 2:
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continue
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self._near_expiration = contracts[0].expiry
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self._far_expiration = contracts[1].expiry
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self._put_calendar_spread = OptionStrategies.put_calendar_spread(option_symbol, strike, self._near_expiration, self._far_expiration)
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self._short_put_calendar_spread = OptionStrategies.short_put_calendar_spread(option_symbol, strike, self._near_expiration, self._far_expiration)
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self.buy(self._put_calendar_spread, 2)
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return
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def assert_strategy_position_group(self, position_group: IPositionGroup, option_symbol: Symbol) -> None:
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positions = list(position_group.positions)
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if len(positions) != 2:
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raise AssertionError(f"Expected position group to have 2 positions. Actual: {len(positions)}")
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near_expiration_position = next((position for position in positions
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if position.symbol.id.option_right == OptionRight.PUT and position.symbol.id.date == self._near_expiration),
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None)
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if not near_expiration_position or near_expiration_position.quantity != -2:
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raise AssertionError(f"Expected near expiration position to be -2. Actual: {near_expiration_position.quantity}")
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far_expiration_position = next((position for position in positions
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if position.symbol.id.option_right == OptionRight.PUT and position.symbol.id.date == self._far_expiration),
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None)
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if not far_expiration_position or far_expiration_position.quantity != 2:
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raise AssertionError(f"Expected far expiration position to be 2. Actual: {far_expiration_position.quantity}")
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def liquidate_strategy(self) -> None:
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# We should be able to close the position using the inverse strategy (a short put calendar spread)
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self.buy(self._short_put_calendar_spread, 2)
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