Jhonathan Abreu
e29bb2c5e0
API Tests / build (push) Has been cancelled
Benchmarks / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
Regression Tests / build (push) Has been cancelled
Report Generator Tests / build (push) Has been cancelled
Research Regression Tests / build (push) Has been cancelled
Python Virtual Environments / build (push) Has been cancelled
* Initial options universe with greeks implementation * Options universe improvements * Address peer review * File based options universe fixes and improvements. - Adjust OptionUniverse start-end times and period. - Adapt unit tests and some algorithms to pass with new options universe selection. * Updated options regression algorithms stats for new universe data * Updated options regression algorithms stats for new universe data * Updated options regression algorithms stats for new universe data * Updated options regression algorithms stats for new universe data * Updated options regression algorithms stats for new universe data * Option chain provider with new options universe * Allow canonical option history requests * Address peer review * Address peer review * Fix symbols parsing in OptionUniverse * Fix universe selection subscriptions start time to not include extended market hours * Minor changes * Minor changes * Peer recommended changes and fixes * Update regression algorithm stats * Update regression algorithms stats and minor fixes * Fix option chain provider history request * Round option indicators values * Added option universe csv header property * Update regression algorithms stats * Update regression algorithms stats * Data fixes and regression algos stats update * Unit test fixes * Minor changes * Option chain handling in live trading data feed * Minor changes * Added processed data provider * Fix thread-safety violation in Slice class * Minor change * Update options filter universe API to use OptionUniverse data Add new filter methods for greeks, IV and open interest * Option filter universe api updates * Add OptionUniverse history regression algorithms * Add regression algorithms for new options filter universe api methods * Added options greeks data and updated regression algorithms * Address peer review * Address peer review * Add more assertions to new options filter api regression algorithms * Minor performance improvement. Reduce greeks binomial model steps to 140 * Minor tests updates * Greeks numerical models performance improvements * Greeks numerical models performance improvements * Revert array pool change for option pricing numerical models * Update default dividend yield provider depending on option type * [TEST] * Add helper method con calculate time till expiration * Use double in price option numerical models * Implied volatility calculation improvements - Adjust root finding method accuracy as a factor of the option price - Use BSM to get a first guess * Cleanup * Some regression algorithms and unit tests cleanup * Regression tests updates after rebasing from master * Add universe files * Self review and cleanup * Minor regression tests updates after rebase * Fix: set data time zone to same as exchange tz for options universes * Minor change * Minor change * Fix for live trading options universe selection * Keep underlying when aggregating collections in BaseDataCollectionAggregatorEnumerator * Update index options regression algorithms stats * Minor change * Address peer review * Memory usage improvements * Minor build fix * Minor changes and test fixes * Cache symbols in OptionUniverse * Cleanup * Fix index option creation in OptionUniverse * Use cached underlying SID when parsing from string * Abstract symbols cache to BaseDataCollection * Return actual underlying symbol when mapping decomposing ICO ticker * Address peer review * Minor performance improvements reduce garbage * Limit Symbols and SIDs cache size to help with memory usage * Minor fix in symbols and sid cache cleanup * Build fix * Lazily parse greeks on individual access * Cleanup and tests * Address peer review * Minor greeks fix --------- Co-authored-by: Martin Molinero <martin.molinero1@gmail.com>
58 lines
3.1 KiB
Python
58 lines
3.1 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>
|
|
### Regression algorithm illustrating how to request history data for different data normalization modes.
|
|
### </summary>
|
|
class HistoryWithDifferentDataNormalizationModeRegressionAlgorithm(QCAlgorithm):
|
|
|
|
def initialize(self):
|
|
self.set_start_date(2013, 10, 7)
|
|
self.set_end_date(2014, 1, 1)
|
|
self.aapl_equity_symbol = self.add_equity("AAPL", Resolution.DAILY).symbol
|
|
self.es_future_symbol = self.add_future(Futures.Indices.SP_500_E_MINI, Resolution.DAILY).symbol
|
|
|
|
def on_end_of_algorithm(self):
|
|
equity_data_normalization_modes = [
|
|
DataNormalizationMode.RAW,
|
|
DataNormalizationMode.ADJUSTED,
|
|
DataNormalizationMode.SPLIT_ADJUSTED
|
|
]
|
|
self.check_history_results_for_data_normalization_modes(self.aapl_equity_symbol, self.start_date, self.end_date, Resolution.DAILY,
|
|
equity_data_normalization_modes)
|
|
|
|
future_data_normalization_modes = [
|
|
DataNormalizationMode.RAW,
|
|
DataNormalizationMode.BACKWARDS_RATIO,
|
|
DataNormalizationMode.BACKWARDS_PANAMA_CANAL,
|
|
DataNormalizationMode.FORWARD_PANAMA_CANAL
|
|
]
|
|
self.check_history_results_for_data_normalization_modes(self.es_future_symbol, self.start_date, self.end_date, Resolution.DAILY,
|
|
future_data_normalization_modes)
|
|
|
|
def check_history_results_for_data_normalization_modes(self, symbol, start, end, resolution, data_normalization_modes):
|
|
history_results = [self.history([symbol], start, end, resolution, data_normalization_mode=x) for x in data_normalization_modes]
|
|
history_results = [x.droplevel(0, axis=0) for x in history_results] if len(history_results[0].index.levels) == 3 else history_results
|
|
history_results = [x.loc[symbol].close for x in history_results]
|
|
|
|
if any(x.size == 0 or x.size != history_results[0].size for x in history_results):
|
|
raise Exception(f"History results for {symbol} have different number of bars")
|
|
|
|
# Check that, for each history result, close prices at each time are different for these securities (AAPL and ES)
|
|
for j in range(history_results[0].size):
|
|
close_prices = set(history_results[i][j] for i in range(len(history_results)))
|
|
if len(close_prices) != len(data_normalization_modes):
|
|
raise Exception(f"History results for {symbol} have different close prices at the same time")
|