Jared Broad
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, 07) #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") |