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