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
57 lines
2.3 KiB
Python
57 lines
2.3 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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### Algorithm used for regression tests purposes
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### </summary>
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### <meta name="tag" content="regression test" />
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class RegressionAlgorithm(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(2013,10,7) #Set Start Date
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self.set_end_date(2013,10,11) #Set End Date
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self.set_cash(10000000) #Set Strategy Cash
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# Find more symbols here: http://quantconnect.com/data
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self.add_equity("SPY", Resolution.TICK)
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self.add_equity("BAC", Resolution.MINUTE)
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self.add_equity("AIG", Resolution.HOUR)
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self.add_equity("IBM", Resolution.DAILY)
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self.__last_trade_ticks = self.start_date
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self.__last_trade_trade_bars = self.__last_trade_ticks
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self.__trade_every = timedelta(minutes=1)
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def on_data(self, data):
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'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''
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if self.time - self.__last_trade_trade_bars < self.__trade_every:
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return
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self.__last_trade_trade_bars = self.time
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for kvp in data.bars:
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bar = kvp.Value
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if bar.is_fill_forward:
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continue
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symbol = kvp.key
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holdings = self.portfolio[symbol]
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if not holdings.invested:
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self.market_order(symbol, 10)
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else:
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self.market_order(symbol, -holdings.quantity)
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