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.
68 lines
2.7 KiB
Python
68 lines
2.7 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.Indicators")
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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.Indicators import *
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from QuantConnect.Parameters import *
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import decimal as d
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### <summary>
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### Demonstration of the parameter system of QuantConnect. Using parameters you can pass the values required into C# algorithms for optimization.
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### </summary>
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### <meta name="tag" content="optimization" />
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### <meta name="tag" content="using quantconnect" />
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class ParameterizedAlgorithm(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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# Receive parameters from the Job
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ema_fast = self.GetParameter("ema-fast")
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ema_slow = self.GetParameter("ema-slow")
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# The values 100 and 200 are just default values that only used if the parameters do not exist
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fast_period = 100 if ema_fast is None else int(ema_fast)
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slow_period = 200 if ema_slow is None else int(ema_slow)
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self.fast = self.EMA("SPY", fast_period)
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self.slow = self.EMA("SPY", slow_period)
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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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# wait for our indicators to ready
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if not self.fast.IsReady or not self.slow.IsReady:
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return
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fast = self.fast.Current.Value
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slow = self.slow.Current.Value
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if fast > slow * d.Decimal(1.001):
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self.SetHoldings("SPY", 1)
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elif fast < slow * d.Decimal(0.999):
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self.Liquidate("SPY") |