Jhonathan Abreu
ad6046fea5
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* Add ShortButterflyCall and ShortButterflyPut strategies helper factory methods * Reduce duplication by adding the base OptionStrategyFactoryMethodsBaseAlgorithm algorithm class * Housekeeping
82 lines
4.2 KiB
Python
82 lines
4.2 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 Butterfly Put and Short Butterfly Put strategies.
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### </summary>
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class LongAndShortButterflyPutStrategiesAlgorithm(OptionStrategyFactoryMethodsBaseAlgorithm):
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def ExpectedOrdersCount(self) -> int:
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return 6
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def TradeStrategy(self, chain: OptionChain, option_symbol: Symbol):
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putContracts = (contract for contract in chain if contract.Right == OptionRight.Put)
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for expiry, group in itertools.groupby(putContracts, lambda x: x.Expiry):
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contracts = list(group)
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if len(contracts) < 3:
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continue
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strikes = sorted([contract.Strike for contract in contracts])
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atmStrike = min(strikes, key=lambda strike: abs(strike - chain.Underlying.Price))
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spread = min(atmStrike - strikes[0], strikes[-1] - atmStrike)
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itmStrike = atmStrike + spread
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otmStrike = atmStrike - spread
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if otmStrike in strikes and itmStrike in strikes:
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# Ready to trade
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self._butterfly_put = OptionStrategies.ButterflyPut(option_symbol, itmStrike, atmStrike, otmStrike, expiry)
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self._short_butterfly_put = OptionStrategies.ShortButterflyPut(option_symbol, itmStrike, atmStrike, otmStrike, expiry)
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self.Buy(self._butterfly_put, 2)
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return
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def AssertStrategyPositionGroup(self, positionGroup: IPositionGroup, option_symbol: Symbol):
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positions = list(positionGroup.Positions)
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if len(positions) != 3:
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raise Exception(f"Expected position group to have 3 positions. Actual: {len(positions)}")
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higherStrike = max(leg.Strike for leg in self._butterfly_put.OptionLegs)
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higherStrikePosition = next((position for position in positions
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if position.Symbol.ID.OptionRight == OptionRight.Put and position.Symbol.ID.StrikePrice == higherStrike),
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None)
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if higherStrikePosition.Quantity != 2:
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raise Exception(f"Expected higher strike position quantity to be 2. Actual: {higherStrikePosition.Quantity}")
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lowerStrike = min(leg.Strike for leg in self._butterfly_put.OptionLegs)
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lowerStrikePosition = next((position for position in positions
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if position.Symbol.ID.OptionRight == OptionRight.Put and position.Symbol.ID.StrikePrice == lowerStrike),
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None)
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if lowerStrikePosition.Quantity != 2:
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raise Exception(f"Expected lower strike position quantity to be 2. Actual: {lowerStrikePosition.Quantity}")
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middleStrike = [leg.Strike for leg in self._butterfly_put.OptionLegs if leg.Strike < higherStrike and leg.Strike > lowerStrike][0]
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middleStrikePosition = next((position for position in positions
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if position.Symbol.ID.OptionRight == OptionRight.Put and position.Symbol.ID.StrikePrice == middleStrike),
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None)
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if middleStrikePosition.Quantity != -4:
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raise Exception(f"Expected middle strike position quantity to be -4. Actual: {middleStrikePosition.Quantity}")
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def LiquidateStrategy(self):
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# We should be able to close the position using the inverse strategy (a short butterfly put)
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self.Buy(self._short_butterfly_put, 2);
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