/* * QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals. * Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation. * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. */ using System; using System.Collections.Generic; using System.Linq; using QuantConnect.Data.Fundamental; using QuantConnect.Data.Market; using QuantConnect.Data.UniverseSelection; namespace QuantConnect.Algorithm.CSharp { /// /// Demonstration of how to define a universe /// as a combination of use the coarse fundamental data and fine fundamental data /// /// /// /// /// public class CoarseFineFundamentalRegressionAlgorithm : QCAlgorithm { private const int NumberOfSymbolsFine = 2; // initialize our changes to nothing private SecurityChanges _changes = SecurityChanges.None; public override void Initialize() { UniverseSettings.Resolution = Resolution.Daily; SetStartDate(2014, 04, 01); SetEndDate(2014, 04, 30); SetCash(50000); // this add universe method accepts two parameters: // - coarse selection function: accepts an IEnumerable and returns an IEnumerable // - fine selection function: accepts an IEnumerable and returns an IEnumerable AddUniverse(CoarseSelectionFunction, FineSelectionFunction); } // return a list of three fixed symbol objects public IEnumerable CoarseSelectionFunction(IEnumerable coarse) { if (Time.Date < new DateTime(2014, 4, 5)) { return new List { QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, "usa"), QuantConnect.Symbol.Create("AIG", SecurityType.Equity, "usa"), QuantConnect.Symbol.Create("IBM", SecurityType.Equity, "usa") }; } return new List { QuantConnect.Symbol.Create("BAC", SecurityType.Equity, "usa"), QuantConnect.Symbol.Create("GOOG", SecurityType.Equity, "usa"), QuantConnect.Symbol.Create("SPY", SecurityType.Equity, "usa") }; } // sort the data by P/E ratio and take the top 'NumberOfSymbolsFine' public IEnumerable FineSelectionFunction(IEnumerable fine) { // sort descending by P/E ratio var sortedByPeRatio = fine.OrderByDescending(x => x.ValuationRatios.PERatio); // take the top entries from our sorted collection var topFine = sortedByPeRatio.Take(NumberOfSymbolsFine); // we need to return only the symbol objects return topFine.Select(x => x.Symbol); } //Data Event Handler: New data arrives here. "TradeBars" type is a dictionary of strings so you can access it by symbol. public void OnData(TradeBars data) { // if we have no changes, do nothing if (_changes == SecurityChanges.None) return; // liquidate removed securities foreach (var security in _changes.RemovedSecurities) { if (security.Invested) { Liquidate(security.Symbol); Debug("Liquidated Stock: " + security.Symbol.Value); } } // we want 50% allocation in each security in our universe foreach (var security in _changes.AddedSecurities) { SetHoldings(security.Symbol, 0.5m); Debug("Purchased Stock: " + security.Symbol.Value); } _changes = SecurityChanges.None; } // this event fires whenever we have changes to our universe public override void OnSecuritiesChanged(SecurityChanges changes) { _changes = changes; if (changes.AddedSecurities.Count > 0) { Debug("Securities added: " + string.Join(",", changes.AddedSecurities.Select(x => x.Symbol.Value))); } if (changes.RemovedSecurities.Count > 0) { Debug("Securities removed: " + string.Join(",", changes.RemovedSecurities.Select(x => x.Symbol.Value))); } } } }