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.
89 lines
3.6 KiB
Python
89 lines
3.6 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 QuantConnect.Data.Market import *
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from QuantConnect.Orders import *
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### <summary>
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### Demonstration of using the Delisting event in your algorithm. Assets are delisted on their last day of trading, or when their contract expires.
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### This data is not included in the open source project.
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### </summary>
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### <meta name="tag" content="using data" />
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### <meta name="tag" content="data event handlers" />
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### <meta name="tag" content="delisting event" />
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class DelistingEventsAlgorithm(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(2007, 5, 16) #Set Start Date
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self.SetEndDate(2007, 5, 25) #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("AAA", Resolution.Daily)
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self.AddEquity("SPY", Resolution.Daily)
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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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Arguments:
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data: Slice object keyed by symbol containing the stock data
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'''
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if self.Transactions.OrdersCount == 0:
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self.SetHoldings("AAA", 1)
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self.Debug("Purchased stock")
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for kvp in data.Bars:
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symbol = kvp.Key
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value = kvp.Value
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self.Log("OnData(Slice): {0}: {1}: {2}".format(self.Time, symbol, value.Close))
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# the slice can also contain delisting data: data.Delistings in a dictionary string->Delisting
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aaa = self.Securities["AAA"]
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if aaa.IsDelisted and aaa.IsTradable:
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raise Exception("Delisted security must NOT be tradable")
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if not aaa.IsDelisted and not aaa.IsTradable:
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raise Exception("Securities must be marked as tradable until they're delisted or removed from the universe")
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for kvp in data.Delistings:
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symbol = kvp.Key
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value = kvp.Value
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if value.Type == DelistingType.Warning:
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self.Log("OnData(Delistings): {0}: {1} will be delisted at end of day today.".format(self.Time, symbol))
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# liquidate on delisting warning
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self.SetHoldings(symbol, 0)
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if value.Type == DelistingType.Delisted:
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self.Log("OnData(Delistings): {0}: {1} has been delisted.".format(self.Time, symbol))
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# fails because the security has already been delisted and is no longer tradable
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self.SetHoldings(symbol, 1)
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def OnOrderEvent(self, orderEvent):
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self.Log("OnOrderEvent(OrderEvent): {0}: {1}".format(self.Time, orderEvent)) |