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.
95 lines
4.5 KiB
Python
95 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.Algorithm.Framework")
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AddReference("QuantConnect.Common")
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AddReference("QuantConnect.Indicators")
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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.Algorithm.Framework import QCAlgorithmFrameworkBridge
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from QuantConnect.Algorithm.Framework.Alphas import *
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from QuantConnect.Indicators import *
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from datetime import timedelta
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### <summary>
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### Demonstration algorithm showing how to easily convert an old algorithm into the framework.
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###
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### 1. Make class derive from QCAlgorithmFrameworkBridge instead of QCAlgorithm.
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### 2. When making orders, also create insights for the correct direction (up/down), can also set insight prediction period/magnitude/direction
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### 3. Profit :)
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### </summary>
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### <meta name="tag" content="indicators" />
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### <meta name="tag" content="indicator classes" />
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### <meta name="tag" content="plotting indicators" />
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class ConvertToFrameworkAlgorithm(QCAlgorithmFrameworkBridge): # 1. Derive from QCAlgorithmFrameworkBridge
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'''Demonstration algorithm showing how to easily convert an old algorithm into the framework.'''
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FastEmaPeriod = 12
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SlowEmaPeriod = 26
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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(2004, 1, 1)
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self.SetEndDate(2015, 1, 1)
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self.symbol = self.AddSecurity(SecurityType.Equity, 'SPY', Resolution.Daily).Symbol
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# define our daily macd(12,26) with a 9 day signal
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self.macd = self.MACD(self.symbol, self.FastEmaPeriod, self.SlowEmaPeriod, 9, MovingAverageType.Exponential, 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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Args:
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data: Slice object with your stock data'''
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# wait for our indicator to be ready
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if not self.macd.IsReady or data[self.symbol] is None: return
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holding = self.Portfolio[self.symbol]
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signalDeltaPercent = float(self.macd.Current.Value - self.macd.Signal.Current.Value) / float(self.macd.Fast.Current.Value)
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tolerance = 0.0025
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# if our macd is greater than our signal, then let's go long
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if holding.Quantity <= 0 and signalDeltaPercent > tolerance:
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# 2. Call EmitInsights with insights created in correct direction, here we're going long
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# The EmitInsights method can accept multiple insights separated by commas
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self.EmitInsights(
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# Creates an insight for our symbol, predicting that it will move up within the fast ema period number of days
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Insight.Price(self.symbol, timedelta(self.FastEmaPeriod), InsightDirection.Up)
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)
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# longterm says buy as well
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self.SetHoldings(self.symbol, 1)
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# if our macd is less than our signal, then let's go short
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elif holding.Quantity >= 0 and signalDeltaPercent < -tolerance:
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# 2. Call EmitInsights with insights created in correct direction, here we're going short
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# The EmitInsights method can accept multiple insights separated by commas
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self.EmitInsights(
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# Creates an insight for our symbol, predicting that it will move down within the fast ema period number of days
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Insight.Price(self.symbol, timedelta(self.FastEmaPeriod), InsightDirection.Down)
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)
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self.SetHoldings(self.symbol, -1)
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# plot both lines
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self.Plot("MACD", self.macd, self.macd.Signal)
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self.Plot(self.symbol.Value, self.macd.Fast, self.macd.Slow)
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self.Plot(self.symbol.Value, "Open", data[self.symbol].Open) |