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quantconnect--lean/Algorithm.Python/OptionPriceModelForUnsupportedAmericanOptionRegressionAlgorithm.py
Jhonathan Abreu e68ee853db
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Implement indicator-based option price model (#9237)
* Implement indicator-based option price model

This model uses IV and Greeks indicators to implement Lean's own option pricing model

* Minor fixes

* Address peer review

* Minor tests fixes

* Make the indicator based price model the default for options

* Address peer review

* Cleanup and minor changes

* Support indicators configuration for new pricing model

* Some cleanup

* Add QL option price model example algorithm

* Return lean models from static helpers

* Minor tests fixes

* Minor test fixes

* Address peer review

* Cleanup

* Fix unit tests

* Move QL models to OptionPriceModels.QuantLib.*

* Add forward tree helper method
2026-02-19 15:15:25 -04:00

35 lines
1.7 KiB
Python

# 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 *
from OptionPriceModelForOptionStylesBaseRegressionAlgorithm import OptionPriceModelForOptionStylesBaseRegressionAlgorithm
### <summary>
### Regression algorithm exercising an equity covered American style option, using an option price model
### that supports American style options and asserting that the option price model is used.
### </summary>
class OptionPriceModelForUnsupportedAmericanOptionRegressionAlgorithm(OptionPriceModelForOptionStylesBaseRegressionAlgorithm):
def initialize(self):
self.set_start_date(2014, 6, 9)
self.set_end_date(2014, 6, 9)
option = self.add_option("AAPL", Resolution.MINUTE)
option.set_filter(lambda u: u.standards_only().strikes(-1, 1).expiration(0, 35))
# BlackSholes model does not support American style options
option.price_model = OptionPriceModels.QuantLib.black_scholes()
self.set_warmup(2, Resolution.DAILY)
self.init(option, option_style_is_supported=False)