Files
quantconnect--lean/Algorithm.CSharp/AddRemoveSecurityRegressionAlgorithm.cs
T
Michael Handschuh 8402b6f01e Update factor files to 2018.06.04
It's important that we keep the factor files consistent with respect to
the date that they were generated. This enables us to run the regression
algorithms in the cloud and get the same results by using the factor files
from the correct date.
2018-06-07 12:16:45 -04:00

130 lines
5.2 KiB
C#

/*
* 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 QuantConnect.Data.Market;
using QuantConnect.Orders;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// This algorithm demonstrates the runtime addition and removal of securities from your algorithm.
/// With LEAN it is possible to add and remove securities after the initialization.
/// </summary>
/// <meta name="tag" content="using data" />
/// <meta name="tag" content="assets" />
/// <meta name="tag" content="regression test" />
public class AddRemoveSecurityRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private DateTime lastAction;
private Symbol _spy = QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA);
private Symbol _aig = QuantConnect.Symbol.Create("AIG", SecurityType.Equity, Market.USA);
private Symbol _bac = QuantConnect.Symbol.Create("BAC", SecurityType.Equity, Market.USA);
/// <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()
{
SetStartDate(2013, 10, 07); //Set Start Date
SetEndDate(2013, 10, 11); //Set End Date
SetCash(100000); //Set Strategy Cash
AddSecurity(SecurityType.Equity, "SPY");
}
/// <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 void OnData(TradeBars data)
{
if (lastAction.Date == Time.Date) return;
if (!Portfolio.Invested)
{
SetHoldings(_spy, 0.5);
lastAction = Time;
}
if (Time.DayOfWeek == DayOfWeek.Tuesday)
{
AddSecurity(SecurityType.Equity, "AIG");
AddSecurity(SecurityType.Equity, "BAC");
lastAction = Time;
}
else if (Time.DayOfWeek == DayOfWeek.Wednesday)
{
SetHoldings(_aig, .25);
SetHoldings(_bac, .25);
lastAction = Time;
}
else if (Time.DayOfWeek == DayOfWeek.Thursday)
{
RemoveSecurity(_bac);
RemoveSecurity(_aig);
lastAction = Time;
}
}
/// <summary>
/// Order events are triggered on order status changes. There are many order events including non-fill messages.
/// </summary>
/// <param name="orderEvent">OrderEvent object with details about the order status</param>
public override void OnOrderEvent(OrderEvent orderEvent)
{
if (orderEvent.Status == OrderStatus.Submitted)
{
Debug(Time + ": Submitted: " + Transactions.GetOrderById(orderEvent.OrderId));
}
if (orderEvent.Status.IsFill())
{
Debug(Time + ": Filled: " + Transactions.GetOrderById(orderEvent.OrderId));
}
}
/// <summary>
/// This is used by the regression test system to indicate which languages this algorithm is written in.
/// </summary>
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Trades", "5"},
{"Average Win", "0.49%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "306.735%"},
{"Drawdown", "1.400%"},
{"Expectancy", "0"},
{"Net Profit", "1.810%"},
{"Sharpe Ratio", "6.474"},
{"Loss Rate", "0%"},
{"Win Rate", "100%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0.003"},
{"Beta", "82.451"},
{"Annual Standard Deviation", "0.141"},
{"Annual Variance", "0.02"},
{"Information Ratio", "6.399"},
{"Tracking Error", "0.141"},
{"Treynor Ratio", "0.011"},
{"Total Fees", "$26.45"}
};
}
}