Michael Handschuh
fdc866fda0
We didn't experience the expected performance improvements. Locally under unit test there was aboout an order of magnitude throughput increase, but when run against the history benchmark, this new approach was 60% slower. We're reverting this for now to perform further analysis and better understand the performance profiling of the python history stack.
101 lines
4.5 KiB
Python
101 lines
4.5 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 clr import AddReference
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AddReference("System")
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AddReference("QuantConnect.Algorithm")
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AddReference("QuantConnect.Common")
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from System import *
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from QuantConnect import *
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from QuantConnect.Algorithm import *
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from QuantConnect.Data import *
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from datetime import timedelta
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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.SetStartDate(2013,10,7) #Set Start Date
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self.SetEndDate(2013,10,11) #Set End Date
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self.SetCash(100000) #Set Strategy Cash
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# Find more symbols here: http://quantconnect.com/data
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self.AddEquity("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.DateRules.On(2013, 10, 7), self.TimeRules.At(13, 0), self.SpecificTime)
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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.DateRules.EveryDay("SPY"), self.TimeRules.AfterMarketOpen("SPY", 10), self.EveryDayAfterMarketOpen)
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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.DateRules.EveryDay("SPY"), self.TimeRules.BeforeMarketClose("SPY", 10), self.EveryDayAfterMarketClose)
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# schedule an event to fire on certain days of the week
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self.Schedule.On(self.DateRules.Every(DayOfWeek.Monday, DayOfWeek.Friday), self.TimeRules.At(12, 0), self.EveryMonFriAtNoon)
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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.DateRules.EveryDay(), self.TimeRules.Every(timedelta(minutes=10)), self.LiquidateUnrealizedLosses)
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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.DateRules.MonthStart("SPY"), self.TimeRules.AfterMarketOpen("SPY"), self.RebalancingCode)
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def OnData(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.SetHoldings("SPY", 1)
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def SpecificTime(self):
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self.Log("SpecificTime: Fired at : {0}".format(self.Time))
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def EveryDayAfterMarketOpen(self):
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self.Log("EveryDay.SPY 10 min after open: Fired at: {0}".format(self.Time))
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def EveryDayAfterMarketClose(self):
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self.Log("EveryDay.SPY 10 min before close: Fired at: {0}".format(self.Time))
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def EveryMonFriAtNoon(self):
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self.Log("Mon/Fri at 12pm: Fired at: {0}".format(self.Time))
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def LiquidateUnrealizedLosses(self):
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''' if we have over 1000 dollars in unrealized losses, liquidate'''
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if self.Portfolio.TotalUnrealizedProfit < -1000:
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self.Log("Liquidated due to unrealized losses at: {0}".format(self.Time))
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self.Liquidate()
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def RebalancingCode(self):
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''' Good spot for rebalancing code?'''
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pass |