126 lines
4.8 KiB
C#
126 lines
4.8 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.Collections.Concurrent;
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using System.Linq;
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using QuantConnect.Data;
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using QuantConnect.Data.UniverseSelection;
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using QuantConnect.Indicators;
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using QuantConnect.Orders;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Basic template algorithm simply initializes the date range and cash
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/// </summary>
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public class UniverseSelectionAlgorithm : QCAlgorithm
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{
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private const int Count = 100;
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private int dataCount = 0;
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private DateTime last;
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private class SelectionData
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{
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public readonly ExponentialMovingAverage EMA50;
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public readonly ExponentialMovingAverage EMA100;
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public SelectionData()
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{
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EMA50 = new ExponentialMovingAverage(50);
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EMA100 = new ExponentialMovingAverage(100);
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}
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public bool Update(DateTime time, decimal value)
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{
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return EMA50.Update(time, value) && EMA100.Update(time, value);
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}
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}
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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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UniverseSettings.Leverage = 2.0m;
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UniverseSettings.Resolution = Resolution.Daily;
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SetStartDate(2001, 01, 01); //Set Start Date
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SetEndDate(2002, 01, 01); //Set End Date
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SetCash(10000000); //Set Strategy Cash
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var averages = new ConcurrentDictionary<Symbol, SelectionData>();
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SetUniverse(coarse =>
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{
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return (from cf in coarse
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let avg = averages.GetOrAdd(cf.Symbol, sym => new SelectionData())
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where avg.Update(cf.EndTime, cf.Price)
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// only pick symbols who have their 50 day ema over their 100 day ema
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where avg.EMA50 > avg.EMA100
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// prefer symbols with a larger delta by percentage between the two averages
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orderby (avg.EMA50 - avg.EMA100)/cf.Price descending
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select cf.Symbol).Take(Count);
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});
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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">Slice object keyed by symbol containing the stock data</param>
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public override void OnData(Slice data)
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{
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dataCount++;
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}
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public override void OnSecuritiesChanged(SecurityChanges changes)
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{
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if (changes.AddedSecurities.Count != 0)
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{
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Log("Security added: " + string.Join(",", changes.AddedSecurities.Select(x => x.Symbol)));
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foreach (var security in changes.AddedSecurities.OrderBy(x => x.Symbol))
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{
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if (!security.HoldStock)
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{
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SetHoldings(security.Symbol, 0.0075);
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}
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}
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}
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if (changes.RemovedSecurities.Count != 0)
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{
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Log("Security removed: " + string.Join(",", changes.RemovedSecurities.Select(x => x.Symbol)));
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foreach (var security in changes.RemovedSecurities.OrderBy(x => x.Symbol))
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{
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var previousOrders = Transactions.GetOrders(x => x.Symbol == security.Symbol).OrderByDescending(x => x.Time);
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if (security.HoldStock && previousOrders.First().Time + TimeSpan.FromDays(30) < Time)
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{
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Log("Liquidating: " + security.Symbol);
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Liquidate(security.Symbol);
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}
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}
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}
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}
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public override void OnOrderEvent(OrderEvent orderEvent)
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{
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}
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public override void OnEndOfAlgorithm()
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{
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Console.WriteLine("SecuritiesCount: " + Securities.Count + " DataCount: " + dataCount);
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}
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}
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} |