wehub-resource-sync
62 lines
3.0 KiB
Python
62 lines
3.0 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 queue import Queue
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class ScheduledQueuingAlgorithm(QCAlgorithm):
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def initialize(self) -> None:
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self.set_start_date(2020, 9, 1)
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self.set_end_date(2020, 9, 2)
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self.set_cash(100000)
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self.__number_of_symbols = 2000
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self.__number_of_symbols_fine = 1000
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self.set_universe_selection(FineFundamentalUniverseSelectionModel(self.coarse_selection_function, self.fine_selection_function, None))
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self.set_portfolio_construction(EqualWeightingPortfolioConstructionModel())
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self.set_execution(ImmediateExecutionModel())
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self._queue = Queue()
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self._dequeue_size = 100
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self.add_equity("SPY", Resolution.MINUTE)
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self.schedule.on(self.date_rules.every_day("SPY"), self.time_rules.at(0, 0), self.fill_queue)
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self.schedule.on(self.date_rules.every_day("SPY"), self.time_rules.every(timedelta(minutes=60)), self.take_from_queue)
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def coarse_selection_function(self, coarse: list[CoarseFundamental]) -> list[Symbol]:
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has_fundamentals = [security for security in coarse if security.has_fundamental_data]
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sorted_by_dollar_volume = sorted(has_fundamentals, key=lambda x: x.dollar_volume, reverse=True)
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return [ x.symbol for x in sorted_by_dollar_volume[:self.__number_of_symbols] ]
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def fine_selection_function(self, fine: list[FineFundamental]) -> list[Symbol]:
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sorted_by_pe_ratio = sorted(fine, key=lambda x: x.valuation_ratios.pe_ratio, reverse=True)
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return [ x.symbol for x in sorted_by_pe_ratio[:self.__number_of_symbols_fine] ]
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def fill_queue(self) -> None:
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securities = [security for security in self.active_securities.values() if security.fundamentals]
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# Fill queue with symbols sorted by PE ratio (decreasing order)
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self._queue.queue.clear()
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sorted_by_pe_ratio = sorted(securities, key=lambda x: x.fundamentals.valuation_ratios.pe_ratio, reverse=True)
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for security in sorted_by_pe_ratio:
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self._queue.put(security.symbol)
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def take_from_queue(self) -> None:
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symbols = [self._queue.get() for _ in range(min(self._dequeue_size, self._queue.qsize()))]
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self.history(symbols, 10, Resolution.DAILY)
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self.log(f"Symbols at {self.time}: {[str(symbol) for symbol in symbols]}")
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