wehub-resource-sync
76 lines
3.5 KiB
Python
76 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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from QuantConnect.Securities.Positions import IPositionGroup
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### <summary>
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### This base algorithm demonstrates how to use OptionStrategies helper class to batch send orders for common strategies.
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### </summary>
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class OptionStrategyFactoryMethodsBaseAlgorithm(QCAlgorithm):
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def initialize(self):
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self.set_start_date(2015, 12, 24)
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self.set_end_date(2015, 12, 24)
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self.set_cash(1000000)
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option = self.add_option("GOOG")
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self._option_symbol = option.symbol
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option.set_filter(lambda u: u.standards_only().strikes(-2, +2).expiration(0, 180))
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self.set_benchmark("GOOG")
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def on_data(self, slice):
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if not self.portfolio.invested:
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chain = slice.option_chains.get(self._option_symbol)
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if chain is not None:
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self.trade_strategy(chain, self._option_symbol)
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else:
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# Verify that the strategy was traded
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position_group = list(self.portfolio.positions.groups)[0]
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buying_power_model = position_group.buying_power_model
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if not isinstance(buying_power_model, OptionStrategyPositionGroupBuyingPowerModel):
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raise AssertionError("Expected position group buying power model type: OptionStrategyPositionGroupBuyingPowerModel. "
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f"Actual: {type(position_group.buying_power_model).__name__}")
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self.assert_strategy_position_group(position_group, self._option_symbol)
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# Now we should be able to close the position
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self.liquidate_strategy()
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# We can quit now, no more testing required
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self.quit()
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def on_end_of_algorithm(self):
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if self.portfolio.invested:
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raise AssertionError("Expected no holdings at end of algorithm")
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orders_count = len(list(self.transactions.get_orders(lambda order: order.status == OrderStatus.FILLED)))
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if orders_count != self.expected_orders_count():
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raise AssertionError(f"Expected {self.expected_orders_count()} orders to have been submitted and filled, "
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f"half for buying the strategy and the other half for the liquidation. Actual {orders_count}")
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def expected_orders_count(self) -> int:
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raise NotImplementedError("ExpectedOrdersCount method is not implemented")
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def trade_strategy(self, chain: OptionChain, option_symbol: Symbol) -> None:
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raise NotImplementedError("TradeStrategy method is not implemented")
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def assert_strategy_position_group(self, position_group: IPositionGroup, option_symbol: Symbol) -> None:
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raise NotImplementedError("AssertStrategyPositionGroup method is not implemented")
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def liquidate_strategy(self) -> None:
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raise NotImplementedError("LiquidateStrategy method is not implemented")
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