Scheduling Trading Events by Date, Market Time, and Interval
Article Strategy library · Author: QuantConnect
Summary
This QuantConnect example demonstrates scheduling callbacks with date rules and time rules. It shows one-time events, daily callbacks timed relative to a security’s market open or close, weekday schedules, recurring intervals, and a month-start event. The algorithm also holds SPY and includes a scheduled check that liquidates the portfolio if unrealized losses cross a stated threshold.
The example teaches how scheduled actions can handle tasks such as logging, periodic risk checks, and rebalancing independently of incoming data callbacks. It is an API demonstration rather than a tested trading strategy: the sample spans only a few days, provides no performance analysis, and leaves the rebalancing function empty. Its loss threshold is illustrative and is not calibrated to account size or market conditions.
Key ideas
- Date rules choose the dates on which scheduled callbacks can run.
- Time rules can use clock times, recurring intervals, or times relative to a security’s market hours.
- Scheduled callbacks can be used for periodic portfolio checks and month-start rebalancing.
- The example holds SPY and liquidates when unrealized losses pass its stated threshold.
- The document demonstrates scheduling mechanics and provides no strategy performance evidence.
Tags
Full text
# ScheduledEventsAlgorithm
# ScheduledEventsAlgorithm
Demonstration of the Scheduled Events features available in QuantConnect.
## Source (Apache-2.0)
```python
# QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
# Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from AlgorithmImports import *
### <summary>
### Demonstration of the Scheduled Events features available in QuantConnect.
### </summary>
### <meta name="tag" content="scheduled events" />
### <meta name="tag" content="date rules" />
### <meta name="tag" content="time rules" />
class ScheduledEventsAlgorithm(QCAlgorithm):
def initialize(self):
'''Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.'''
self.set_start_date(2013,10,7) #Set Start Date
self.set_end_date(2013,10,11) #Set End Date
self.set_cash(100000) #Set Strategy Cash
# Find more symbols here: http://quantconnect.com/data
self.add_equity("SPY")
# events are scheduled using date and time rules
# date rules specify on what dates and event will fire
# time rules specify at what time on thos dates the event will fire
# schedule an event to fire at a specific date/time
self.schedule.on(self.date_rules.on(2013, 10, 7), self.time_rules.at(13, 0), self.specific_time)
# schedule an event to fire every trading day for a security the
# time rule here tells it to fire 10 minutes after SPY's market open
self.schedule.on(self.date_rules.every_day("SPY"), self.time_rules.after_market_open("SPY", 10), self.every_day_after_market_open)
# schedule an event to fire every trading day for a security the
# time rule here tells it to fire 10 minutes before SPY's market close
self.schedule.on(self.date_rules.every_day("SPY"), self.time_rules.before_market_close("SPY", 10), self.every_day_after_market_close)
# schedule an event to fire on a single day of the week
self.schedule.on(self.date_rules.every(DayOfWeek.WEDNESDAY), self.time_rules.at(12, 0), self.every_wed_at_noon)
# schedule an event to fire on certain days of the week
self.schedule.on(self.date_rules.every(DayOfWeek.MONDAY, DayOfWeek.FRIDAY), self.time_rules.at(12, 0), self.every_mon_fri_at_noon)
# the scheduling methods return the ScheduledEvent object which can be used for other things here I set
# the event up to check the portfolio value every 10 minutes, and liquidate if we have too many losses
self.schedule.on(self.date_rules.every_day(), self.time_rules.every(timedelta(minutes=10)), self.liquidate_unrealized_losses)
# schedule an event to fire at the beginning of the month, the symbol is optional
# if specified, it will fire the first trading day for that symbol of the month,
# if not specified it will fire on the first day of the month
self.schedule.on(self.date_rules.month_start("SPY"), self.time_rules.after_market_open("SPY"), self.rebalancing_code)
def on_data(self, data):
'''OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.'''
if not self.portfolio.invested:
self.set_holdings("SPY", 1)
def specific_time(self):
self.log(f"SpecificTime: Fired at : {self.time}")
def every_day_after_market_open(self):
self.log(f"EveryDay.SPY 10 min after open: Fired at: {self.time}")
def every_day_after_market_close(self):
self.log(f"EveryDay.SPY 10 min before close: Fired at: {self.time}")
def every_wed_at_noon(self):
self.log(f"Wed at 12pm: Fired at: {self.time}")
def every_mon_fri_at_noon(self):
self.log(f"Mon/Fri at 12pm: Fired at: {self.time}")
def liquidate_unrealized_losses(self):
''' if we have over 1000 dollars in unrealized losses, liquidate'''
if self.portfolio.total_unrealized_profit < -1000:
self.log(f"Liquidated due to unrealized losses at: {self.time}")
self.liquidate()
def rebalancing_code(self):
''' Good spot for rebalancing code?'''
pass
```Shown in full with attribution under the source's licence. Licence: Apache-2.0
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.