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IndexUniverseDefinitions.cs
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/*
* 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 QuantConnect.Data.UniverseSelection;
using System;
using System.Collections.Generic;
using System.Linq;
namespace QuantConnect.Algorithm
{
/// <summary>
/// Provides helpers for defining universes based on index definitions
/// </summary>
public class IndexUniverseDefinitions
{
private readonly QCAlgorithm _algorithm;
/// <summary>
/// Initializes a new instance of the <see cref="IndexUniverseDefinitions"/> class
/// </summary>
/// <param name="algorithm">The algorithm instance, used for obtaining the default <see cref="UniverseSettings"/></param>
public IndexUniverseDefinitions(QCAlgorithm algorithm)
{
_algorithm = algorithm;
}
/// <summary>
/// Creates a new fine universe that contains the constituents of QC500 index based onthe company fundamentals
/// The algorithm creates a default tradable and liquid universe containing 500 US equities
/// which are chosen at the first trading day of each month.
/// </summary>
/// <returns>A new coarse universe for the top count of stocks by dollar volume</returns>
public Universe QC500
{
get
{
var lastMonth = -1;
var numberOfSymbolsCoarse = 1000;
var numberOfSymbolsFine = 500;
var dollarVolumeBySymbol = new Dictionary<Symbol, decimal>();
var symbol = Symbol.Create("qc-500", SecurityType.Equity, Market.USA);
var coarseUniverse = new CoarseFundamentalUniverse(
symbol,
_algorithm.UniverseSettings,
_algorithm.SecurityInitializer,
coarse =>
{
if (_algorithm.Time.Month == lastMonth)
{
return Universe.Unchanged;
}
// The stocks must have fundamental data
// The stock must have positive previous-day close price
// The stock must have positive volume on the previous trading day
var sortedByDollarVolume =
(from x in coarse
where x.HasFundamentalData && x.Volume > 0 && x.Price > 0
orderby x.DollarVolume descending
select x).Take(numberOfSymbolsCoarse).ToList();
dollarVolumeBySymbol.Clear();
foreach (var x in sortedByDollarVolume)
{
dollarVolumeBySymbol[x.Symbol] = x.DollarVolume;
}
// If no security has met the QC500 criteria, the universe is unchanged.
// A new selection will be attempted on the next trading day as lastMonth is not updated
if (dollarVolumeBySymbol.Count == 0)
{
return Universe.Unchanged;
}
return dollarVolumeBySymbol.Keys;
});
return new FineFundamentalFilteredUniverse(
coarseUniverse,
fine =>
{
// The company's headquarter must in the U.S.
// The stock must be traded on either the NYSE or NASDAQ
// At least half a year since its initial public offering
// The stock's market cap must be greater than 500 million
var filteredFine =
(from x in fine
where x.CompanyReference.CountryId == "USA" &&
(x.CompanyReference.PrimaryExchangeID == "NYS" || x.CompanyReference.PrimaryExchangeID == "NAS") &&
(_algorithm.Time - x.SecurityReference.IPODate).Days > 180 &&
x.MarketCap > 500000000m
select x).ToList();
var count = filteredFine.Count;
// If no security has met the QC500 criteria, the universe is unchanged.
// A new selection will be attempted on the next trading day as lastMonth is not updated
if (count == 0)
{
return Universe.Unchanged;
}
// Update _lastMonth after all QC500 criteria checks passed
lastMonth = _algorithm.Time.Month;
var percent = numberOfSymbolsFine / (double)count;
// select stocks with top dollar volume in every single sector
var topFineBySector =
(from x in filteredFine
// Group by sector
group x by x.CompanyReference.IndustryTemplateCode into g
let y = from item in g
orderby dollarVolumeBySymbol[item.Symbol] descending
select item
let c = (int)Math.Ceiling(y.Count() * percent)
select new { g.Key, Value = y.Take(c) }
).ToDictionary(x => x.Key, x => x.Value);
return topFineBySector.SelectMany(x => x.Value)
.OrderByDescending(x => dollarVolumeBySymbol[x.Symbol])
.Take(numberOfSymbolsFine)
.Select(x => x.Symbol);
});
}
}
}
}