# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals. # Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from AlgorithmImports import * import itertools from OptionStrategyFactoryMethodsBaseAlgorithm import * ### ### This algorithm demonstrate how to use OptionStrategies helper class to batch send orders for common strategies. ### In this case, the algorithm tests the Butterfly Call and Short Butterfly Call strategies. ### class LongAndShortButterflyCallStrategiesAlgorithm(OptionStrategyFactoryMethodsBaseAlgorithm): def ExpectedOrdersCount(self) -> int: return 6 def TradeStrategy(self, chain: OptionChain, option_symbol: Symbol): callContracts = (contract for contract in chain if contract.Right == OptionRight.Call) for expiry, group in itertools.groupby(callContracts, lambda x: x.Expiry): contracts = list(group) if len(contracts) < 3: continue strikes = sorted([contract.Strike for contract in contracts]) atmStrike = min(strikes, key=lambda strike: abs(strike - chain.Underlying.Price)) spread = min(atmStrike - strikes[0], strikes[-1] - atmStrike) itmStrike = atmStrike - spread otmStrike = atmStrike + spread if otmStrike in strikes and itmStrike in strikes: # Ready to trade self._butterfly_call = OptionStrategies.ButterflyCall(option_symbol, otmStrike, atmStrike, itmStrike, expiry) self._short_butterfly_call = OptionStrategies.ShortButterflyCall(option_symbol, otmStrike, atmStrike, itmStrike, expiry) self.Buy(self._butterfly_call, 2) return def AssertStrategyPositionGroup(self, positionGroup: IPositionGroup, option_symbol: Symbol): positions = list(positionGroup.Positions) if len(positions) != 3: raise Exception(f"Expected position group to have 3 positions. Actual: {len(positions)}") higherStrike = max(leg.Strike for leg in self._butterfly_call.OptionLegs) higherStrikePosition = next((position for position in positions if position.Symbol.ID.OptionRight == OptionRight.Call and position.Symbol.ID.StrikePrice == higherStrike), None) if higherStrikePosition.Quantity != 2: raise Exception(f"Expected higher strike position quantity to be 2. Actual: {higherStrikePosition.Quantity}") lowerStrike = min(leg.Strike for leg in self._butterfly_call.OptionLegs) lowerStrikePosition = next((position for position in positions if position.Symbol.ID.OptionRight == OptionRight.Call and position.Symbol.ID.StrikePrice == lowerStrike), None) if lowerStrikePosition.Quantity != 2: raise Exception(f"Expected lower strike position quantity to be 2. Actual: {lowerStrikePosition.Quantity}") middleStrike = [leg.Strike for leg in self._butterfly_call.OptionLegs if leg.Strike < higherStrike and leg.Strike > lowerStrike][0] middleStrikePosition = next((position for position in positions if position.Symbol.ID.OptionRight == OptionRight.Call and position.Symbol.ID.StrikePrice == middleStrike), None) if middleStrikePosition.Quantity != -4: raise Exception(f"Expected middle strike position quantity to be -4. Actual: {middleStrikePosition.Quantity}") def LiquidateStrategy(self): # We should be able to close the position using the inverse strategy (a short butterfly call) self.Buy(self._short_butterfly_call, 2)