wehub-resource-sync
103 lines
5.6 KiB
Python
103 lines
5.6 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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### <summary>
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### Regression algorithm asserting the behavior of auxiliary data history requests
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### </summary>
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class HistoryAuxiliaryDataRegressionAlgorithm(QCAlgorithm):
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def initialize(self):
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'''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
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self.set_start_date(2021, 1, 1)
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self.set_end_date(2021, 1, 5)
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aapl = self.add_equity("AAPL", Resolution.DAILY).symbol
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# multi symbol request
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spy = Symbol.create("SPY", SecurityType.EQUITY, Market.USA)
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multi_symbol_request = self.history(Dividend, [ aapl, spy ], 360, Resolution.DAILY)
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if len(multi_symbol_request) != 12:
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raise ValueError(f"Unexpected multi symbol dividend count: {len(multi_symbol_request)}")
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# continuous future mapping requests
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sp500 = Symbol.create(Futures.Indices.SP_500_E_MINI, SecurityType.FUTURE, Market.CME)
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continuous_future_open_interest_mapping = self.history(SymbolChangedEvent, sp500, datetime(2007, 1, 1), datetime(2012, 1, 1), data_mapping_mode = DataMappingMode.OPEN_INTEREST)
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if len(continuous_future_open_interest_mapping) != 9:
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raise ValueError(f"Unexpected continuous future mapping event count: {len(continuous_future_open_interest_mapping)}")
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continuous_future_last_trading_day_mapping = self.history(SymbolChangedEvent, sp500, datetime(2007, 1, 1), datetime(2012, 1, 1), data_mapping_mode = DataMappingMode.LAST_TRADING_DAY)
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if len(continuous_future_last_trading_day_mapping) != 9:
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raise ValueError(f"Unexpected continuous future mapping event count: {len(continuous_future_last_trading_day_mapping)}")
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dividend = self.history(Dividend, aapl, 360)
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self.debug(str(dividend))
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if len(dividend) != 6:
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raise ValueError(f"Unexpected dividend count: {len(dividend)}")
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for distribution in dividend.distribution:
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if distribution == 0:
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raise ValueError(f"Unexpected distribution: {distribution}")
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split = self.history(Split, aapl, 360)
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self.debug(str(split))
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if len(split) != 2:
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raise ValueError(f"Unexpected split count: {len(split)}")
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for splitfactor in split.splitfactor:
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if splitfactor == 0:
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raise ValueError(f"Unexpected splitfactor: {splitfactor}")
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symbol = Symbol.create("BTCUSD", SecurityType.CRYPTO_FUTURE, Market.BINANCE)
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margin_interest = self.history(MarginInterestRate, symbol, 24 * 3, Resolution.HOUR)
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self.debug(str(margin_interest))
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if len(margin_interest) != 8:
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raise ValueError(f"Unexpected margin interest count: {len(margin_interest)}")
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for interestrate in margin_interest.interestrate:
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if interestrate == 0:
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raise ValueError(f"Unexpected interestrate: {interestrate}")
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# last trading date on 2007-05-18
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delisted_symbol = Symbol.create("AAA.1", SecurityType.EQUITY, Market.USA)
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delistings = self.history(Delisting, delisted_symbol, datetime(2007, 5, 15), datetime(2007, 5, 21))
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self.debug(str(delistings))
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if len(delistings) != 2:
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raise ValueError(f"Unexpected delistings count: {len(delistings)}")
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if delistings.iloc[0].type != DelistingType.WARNING:
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raise ValueError(f"Unexpected delisting: {delistings.iloc[0]}")
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if delistings.iloc[1].type != DelistingType.DELISTED:
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raise ValueError(f"Unexpected delisting: {delistings.iloc[1]}")
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# get's remapped:
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# 2008-09-30 spwr -> spwra
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# 2011-11-17 spwra -> spwr
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remapped_symbol = Symbol.create("SPWR", SecurityType.EQUITY, Market.USA)
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symbol_changed_events = self.history(SymbolChangedEvent, remapped_symbol, datetime(2007, 1, 1), datetime(2012, 1, 1))
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self.debug(str(symbol_changed_events))
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if len(symbol_changed_events) != 2:
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raise ValueError(f"Unexpected SymbolChangedEvents count: {len(symbol_changed_events)}")
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first_event = symbol_changed_events.iloc[0]
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if first_event.oldsymbol != "SPWR" or first_event.newsymbol != "SPWRA" or symbol_changed_events.index[0][1] != datetime(2008, 9, 30):
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raise ValueError(f"Unexpected SymbolChangedEvents: {first_event}")
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second_event = symbol_changed_events.iloc[1]
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if second_event.newsymbol != "SPWR" or second_event.oldsymbol != "SPWRA" or symbol_changed_events.index[1][1] != datetime(2011, 11, 17):
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raise ValueError(f"Unexpected SymbolChangedEvents: {second_event}")
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def on_data(self, data):
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'''on_data event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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Arguments:
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data: Slice object keyed by symbol containing the stock data
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'''
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if not self.portfolio.invested:
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self.set_holdings("AAPL", 1)
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