Martin-Molinero
7879795207
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* Default daily precise end times - Enable by default daily precise end times. Updating stats - Minor fix for algorithm manager consolidator updates, adding new regression test asserting behavior and updating others - Minor fix for SubscriptionData creator avoid round down on warmup if not appropiate - Adjust consolidators to emit on daily strict end times if requested daily resolution and setting enabled - Updating regression algorithms * Skip daily data on extended market hours * Some cleanup and self review * Revert unrequired change
65 lines
2.7 KiB
Python
65 lines
2.7 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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### In this algorithm we demonstrate how to use the UniverseSettings
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### to define the data normalization mode (raw)
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### </summary>
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="universes" />
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### <meta name="tag" content="coarse universes" />
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### <meta name="tag" content="fine universes" />
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class RawPricesUniverseRegressionAlgorithm(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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# what resolution should the data *added* to the universe be?
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self.universe_settings.resolution = Resolution.DAILY
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# Use raw prices
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self.universe_settings.data_normalization_mode = DataNormalizationMode.RAW
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self.set_start_date(2014,3,24) #Set Start Date
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self.set_end_date(2014,4,7) #Set End Date
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self.set_cash(50000) #Set Strategy Cash
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# Set the security initializer with zero fees and price initial seed
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securitySeeder = FuncSecuritySeeder(self.GetLastKnownPrices)
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self.set_security_initializer(CompositeSecurityInitializer(
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FuncSecurityInitializer(lambda x: x.set_fee_model(ConstantFeeModel(0))),
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FuncSecurityInitializer(lambda security: securitySeeder.SeedSecurity(security))))
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self.add_universe("MyUniverse", Resolution.DAILY, self.selection_function)
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def selection_function(self, date_time):
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if date_time.day % 2 == 0:
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return ["SPY", "IWM", "QQQ"]
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else:
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return ["AIG", "BAC", "IBM"]
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# this event fires whenever we have changes to our universe
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def on_securities_changed(self, changes):
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# liquidate removed securities
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for security in changes.removed_securities:
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if security.invested:
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self.liquidate(security.symbol)
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# we want 20% allocation in each security in our universe
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for security in changes.added_securities:
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self.set_holdings(security.symbol, 0.2)
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