Files
quantconnect--lean/Algorithm.CSharp/TimeInForceAlgorithm.cs
T
2018-07-19 11:52:40 +02:00

175 lines
7.4 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;
using QuantConnect.Orders;
using QuantConnect.Interfaces;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Demonstration algorithm of time in force order settings.
/// </summary>
/// <meta name="tag" content="using data" />
/// <meta name="tag" content="using quantconnect" />
/// <meta name="tag" content="trading and orders" />
public class TimeInForceAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private Symbol _symbol;
private OrderTicket _gtcOrderTicket1, _gtcOrderTicket2;
private OrderTicket _dayOrderTicket1, _dayOrderTicket2;
private OrderTicket _gtdOrderTicket1, _gtdOrderTicket2;
private readonly Dictionary<int, OrderStatus> _expectedOrderStatuses = new Dictionary<int, OrderStatus>();
/// <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);
SetEndDate(2013, 10, 11);
SetCash(100000);
// The default time in force setting for all orders is GoodTilCancelled (GTC),
// uncomment this line to set a different time in force.
// We currently only support GTC, DAY, GTD.
// DefaultOrderProperties.TimeInForce = TimeInForce.Day;
_symbol = AddEquity("SPY", Resolution.Minute).Symbol;
}
/// <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)
{
if (_gtcOrderTicket1 == null)
{
// These GTC orders will never expire and will not be canceled automatically.
DefaultOrderProperties.TimeInForce = TimeInForce.GoodTilCanceled;
// this order will not be filled before the end of the backtest
_gtcOrderTicket1 = LimitOrder(_symbol, 10, 100m);
_expectedOrderStatuses.Add(_gtcOrderTicket1.OrderId, OrderStatus.Submitted);
// this order will be filled before the end of the backtest
_gtcOrderTicket2 = LimitOrder(_symbol, 10, 160m);
_expectedOrderStatuses.Add(_gtcOrderTicket2.OrderId, OrderStatus.Filled);
}
if (_dayOrderTicket1 == null)
{
// These DAY orders will expire at market close,
// if not filled by then they will be canceled automatically.
DefaultOrderProperties.TimeInForce = TimeInForce.Day;
// this order will not be filled before market close and will be canceled
_dayOrderTicket1 = LimitOrder(_symbol, 10, 150m);
_expectedOrderStatuses.Add(_dayOrderTicket1.OrderId, OrderStatus.Canceled);
// this order will be filled before market close
_dayOrderTicket2 = LimitOrder(_symbol, 10, 180m);
_expectedOrderStatuses.Add(_dayOrderTicket2.OrderId, OrderStatus.Filled);
}
if (_gtdOrderTicket1 == null)
{
// These GTD orders will expire on October 10th at market close,
// if not filled by then they will be canceled automatically.
DefaultOrderProperties.TimeInForce = TimeInForce.GoodTilDate(new DateTime(2013, 10, 10));
// this order will not be filled before expiry and will be canceled
_gtdOrderTicket1 = LimitOrder(_symbol, 10, 100m);
_expectedOrderStatuses.Add(_gtdOrderTicket1.OrderId, OrderStatus.Canceled);
// this order will be filled before expiry
_gtdOrderTicket2 = LimitOrder(_symbol, 10, 160m);
_expectedOrderStatuses.Add(_gtdOrderTicket2.OrderId, OrderStatus.Filled);
}
}
/// <summary>
/// Order event handler. This handler will be called for all order events, including submissions, fills, cancellations.
/// </summary>
/// <param name="orderEvent">Order event instance containing details of the event</param>
/// <remarks>This method can be called asynchronously, ensure you use proper locks on thread-unsafe objects</remarks>
public override void OnOrderEvent(OrderEvent orderEvent)
{
Debug($"{Time} {orderEvent}");
}
/// <summary>
/// End of algorithm run event handler. This method is called at the end of a backtest or live trading operation.
/// </summary>
public override void OnEndOfAlgorithm()
{
foreach (var kvp in _expectedOrderStatuses)
{
var orderId = kvp.Key;
var expectedStatus = kvp.Value;
var order = Transactions.GetOrderById(orderId);
if (order.Status != expectedStatus)
{
throw new Exception($"Invalid status for order {orderId} - Expected: {expectedStatus}, actual: {order.Status}");
}
}
}
/// <summary>
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
/// </summary>
public bool CanRunLocally { get; } = true;
/// <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", "3"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "5.914%"},
{"Drawdown", "0.100%"},
{"Expectancy", "0"},
{"Net Profit", "0.073%"},
{"Sharpe Ratio", "4.198"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "-0.008"},
{"Beta", "4.042"},
{"Annual Standard Deviation", "0.009"},
{"Annual Variance", "0"},
{"Information Ratio", "2.968"},
{"Tracking Error", "0.009"},
{"Treynor Ratio", "0.009"},
{"Total Fees", "$3.00"}
};
}
}