chore: import upstream snapshot with attribution
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# 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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### Demonstration of the Scheduled Events features available in QuantConnect.
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### </summary>
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### <meta name="tag" content="scheduled events" />
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### <meta name="tag" content="date rules" />
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### <meta name="tag" content="time rules" />
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class ScheduledEventsAlgorithm(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(100000) #Set Strategy Cash
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# Find more symbols here: http://quantconnect.com/data
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self.add_equity("SPY")
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# events are scheduled using date and time rules
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# date rules specify on what dates and event will fire
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# time rules specify at what time on thos dates the event will fire
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# schedule an event to fire at a specific date/time
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self.schedule.on(self.date_rules.on(2013, 10, 7), self.time_rules.at(13, 0), self.specific_time)
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# schedule an event to fire every trading day for a security the
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# time rule here tells it to fire 10 minutes after SPY's market open
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self.schedule.on(self.date_rules.every_day("SPY"), self.time_rules.after_market_open("SPY", 10), self.every_day_after_market_open)
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# schedule an event to fire every trading day for a security the
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# time rule here tells it to fire 10 minutes before SPY's market close
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self.schedule.on(self.date_rules.every_day("SPY"), self.time_rules.before_market_close("SPY", 10), self.every_day_after_market_close)
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# schedule an event to fire on a single day of the week
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self.schedule.on(self.date_rules.every(DayOfWeek.WEDNESDAY), self.time_rules.at(12, 0), self.every_wed_at_noon)
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# schedule an event to fire on certain days of the week
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self.schedule.on(self.date_rules.every(DayOfWeek.MONDAY, DayOfWeek.FRIDAY), self.time_rules.at(12, 0), self.every_mon_fri_at_noon)
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# the scheduling methods return the ScheduledEvent object which can be used for other things here I set
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# the event up to check the portfolio value every 10 minutes, and liquidate if we have too many losses
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self.schedule.on(self.date_rules.every_day(), self.time_rules.every(timedelta(minutes=10)), self.liquidate_unrealized_losses)
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# schedule an event to fire at the beginning of the month, the symbol is optional
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# if specified, it will fire the first trading day for that symbol of the month,
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# if not specified it will fire on the first day of the month
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self.schedule.on(self.date_rules.month_start("SPY"), self.time_rules.after_market_open("SPY"), self.rebalancing_code)
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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 not self.portfolio.invested:
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self.set_holdings("SPY", 1)
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def specific_time(self):
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self.log(f"SpecificTime: Fired at : {self.time}")
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def every_day_after_market_open(self):
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self.log(f"EveryDay.SPY 10 min after open: Fired at: {self.time}")
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def every_day_after_market_close(self):
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self.log(f"EveryDay.SPY 10 min before close: Fired at: {self.time}")
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def every_wed_at_noon(self):
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self.log(f"Wed at 12pm: Fired at: {self.time}")
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def every_mon_fri_at_noon(self):
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self.log(f"Mon/Fri at 12pm: Fired at: {self.time}")
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def liquidate_unrealized_losses(self):
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''' if we have over 1000 dollars in unrealized losses, liquidate'''
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if self.portfolio.total_unrealized_profit < -1000:
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self.log(f"Liquidated due to unrealized losses at: {self.time}")
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self.liquidate()
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def rebalancing_code(self):
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''' Good spot for rebalancing code?'''
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pass
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