9ee61f425c
A mechanical refactoring was performed to make algorithms currently used in regression algorithms to implement IRegressionAlgorithmDefinition, which allows algorithms to define their own expected statistics and what languages should be run as part of regression. The type name of the C# type is used to determine the file/model name for python. This was for simplicity, but if needed, could later be refactored to expose more information, but for now the convention of keeping names the same makes sense and just works easily.
129 lines
5.2 KiB
C#
129 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", "307.853%"},
|
|
{"Drawdown", "1.400%"},
|
|
{"Expectancy", "0"},
|
|
{"Net Profit", "1.814%"},
|
|
{"Sharpe Ratio", "6.474"},
|
|
{"Loss Rate", "0%"},
|
|
{"Win Rate", "100%"},
|
|
{"Profit-Loss Ratio", "0"},
|
|
{"Alpha", "0.004"},
|
|
{"Beta", "82.594"},
|
|
{"Annual Standard Deviation", "0.141"},
|
|
{"Annual Variance", "0.02"},
|
|
{"Information Ratio", "6.4"},
|
|
{"Tracking Error", "0.141"},
|
|
{"Treynor Ratio", "0.011"},
|
|
{"Total Fees", "$25.20"}
|
|
};
|
|
}
|
|
} |