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quantconnect--lean/Algorithm.Python/CoarseFineOptionUniverseChainRegressionAlgorithm.py
T
Louis Szeto 6d5f5dce58 pep8 conversion of python algorithms #4 (#7935)
* pep8 conversion

* PEP8 updates/fixes

* Minor update

---------

Co-authored-by: Jhonathan Abreu <jdabreu25@gmail.com>
2024-04-17 19:27:00 -03:00

90 lines
3.6 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 *
### <summary>
### Demonstration of how to chain a coarse and fine universe selection with an option chain universe selection model
### that will add and remove an'OptionChainUniverse' for each symbol selected on fine
### </summary>
class CoarseFineOptionUniverseChainRegressionAlgorithm(QCAlgorithm):
def initialize(self):
'''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
self.set_start_date(2014,6,4) #Set Start Date
self.set_end_date(2014,6,6) #Set End Date
self.universe_settings.resolution = Resolution.MINUTE
self._twx = Symbol.create("TWX", SecurityType.EQUITY, Market.USA)
self._aapl = Symbol.create("AAPL", SecurityType.EQUITY, Market.USA)
self._last_equity_added = None
self._changes = None
self._option_count = 0
universe = self.add_universe(self.coarse_selection_function, self.fine_selection_function)
self.add_universe_options(universe, self.option_filter_function)
def option_filter_function(self, universe):
universe.include_weeklys().front_month()
contracts = list()
for symbol in universe:
if len(contracts) == 5:
break
contracts.append(symbol)
return universe.contracts(contracts)
def coarse_selection_function(self, coarse):
if self.time <= datetime(2014,6,5):
return [ self._twx ]
return [ self._aapl ]
def fine_selection_function(self, fine):
if self.time <= datetime(2014,6,5):
return [ self._twx ]
return [ self._aapl ]
def on_data(self, data):
if self._changes == None or any(security.price == 0 for security in self._changes.added_securities):
return
# liquidate removed securities
for security in self._changes.removed_securities:
if security.invested:
self.liquidate(security.symbol)
for security in self._changes.added_securities:
if not security.symbol.has_underlying:
self._last_equity_added = security.symbol
else:
# options added should all match prev added security
if security.symbol.underlying != self._last_equity_added:
raise ValueError(f"Unexpected symbol added {security.symbol}")
self._option_count += 1
self.set_holdings(security.symbol, 0.05)
self._changes = None
# this event fires whenever we have changes to our universe
def on_securities_changed(self, changes):
if self._changes == None:
self._changes = changes
return
self._changes = self._changes + changes
def on_end_of_algorithm(self):
if self._option_count == 0:
raise ValueError("Option universe chain did not add any option!")