wehub-resource-sync
113 lines
4.4 KiB
C#
113 lines
4.4 KiB
C#
/*
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* 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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*/
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using System;
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using System.Linq;
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using QuantConnect.Data.Market;
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using QuantConnect.Indicators;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// In this example we look at the canonical 15/30 day moving average cross. This algorithm
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/// will go long when the 15 crosses above the 30 and will liquidate when the 15 crosses
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/// back below the 30.
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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="moving average cross" />
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/// <meta name="tag" content="strategy example" />
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public class MovingAverageCrossAlgorithm : QCAlgorithm
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{
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private string _symbol = "SPY";
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private DateTime _previous;
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private ExponentialMovingAverage _fast;
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private ExponentialMovingAverage _slow;
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private SimpleMovingAverage[] _ribbon;
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/// <summary>
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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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/// </summary>
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public override void Initialize()
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{
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// set up our analysis span
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SetStartDate(2009, 01, 01);
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SetEndDate(2015, 01, 01);
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// request SPY data with minute resolution
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AddSecurity(SecurityType.Equity, _symbol, Resolution.Minute);
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// create a 15 day exponential moving average
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_fast = EMA(_symbol, 15, Resolution.Daily);
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// create a 30 day exponential moving average
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_slow = EMA(_symbol, 30, Resolution.Daily);
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var ribbonCount = 8;
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var ribbonInterval = 15;
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_ribbon = Enumerable.Range(0, ribbonCount).Select(x => SMA(_symbol, (x + 1)*ribbonInterval, Resolution.Daily)).ToArray();
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}
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/// <summary>
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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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/// </summary>
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/// <param name="data">TradeBars IDictionary object with your stock data</param>
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public void OnData(TradeBars data)
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{
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// a couple things to notice in this method:
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// 1. We never need to 'update' our indicators with the data, the engine takes care of this for us
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// 2. We can use indicators directly in math expressions
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// 3. We can easily plot many indicators at the same time
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// wait for our slow ema to fully initialize
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if (!_slow.IsReady) return;
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// only once per day
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if (_previous.Date == Time.Date) return;
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// define a small tolerance on our checks to avoid bouncing
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const decimal tolerance = 0.00015m;
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var holdings = Portfolio[_symbol].Quantity;
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// we only want to go long if we're currently short or flat
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if (holdings <= 0)
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{
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// if the fast is greater than the slow, we'll go long
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if (_fast > _slow * (1 + tolerance))
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{
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Log("BUY >> " + Securities[_symbol].Price);
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SetHoldings(_symbol, 1.0);
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}
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}
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// we only want to liquidate if we're currently long
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// if the fast is less than the slow we'll liquidate our long
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if (holdings > 0 && _fast < _slow)
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{
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Log("SELL >> " + Securities[_symbol].Price);
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Liquidate(_symbol);
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}
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Plot(_symbol, "Price", data[_symbol].Price);
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// easily plot indicators, the series name will be the name of the indicator
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Plot(_symbol, _fast, _slow);
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Plot("Ribbon", _ribbon);
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_previous = Time;
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}
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}
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} |