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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.Generic;
using System.Linq;
using QuantConnect.Brokerages;
using QuantConnect.Data;
using QuantConnect.Orders;
using QuantConnect.Interfaces;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// This algorithm is a regression test case for CancelOpenOrders and rejected orders
/// </summary>
public class CancelOpenOrdersRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
/// <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(2017, 9, 3); //Set Start Date
SetEndDate(2017, 9, 3); //Set End Date
SetCash(1000); //Set Strategy Cash
SetBrokerageModel(BrokerageName.GDAX, AccountType.Cash);
AddCrypto("BTCUSD");
AddCrypto("ETHUSD");
}
/// <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 (UtcTime.Hour != 6) return;
if (UtcTime.Minute == 0)
{
// this order will be rejected for insufficient funds
LimitOrder("BTCUSD", 100m, 4734.64m);
LimitOrder("ETHUSD", 1.35505027m, 368.8m);
}
else if (UtcTime.Minute == 6)
{
Transactions.CancelOpenOrders("BTCUSD");
LimitOrder("BTCUSD", 0.10576312m, 4727.61m);
}
else if (UtcTime.Minute == 12)
{
Transactions.CancelOpenOrders("BTCUSD");
LimitOrder("BTCUSD", 0.10576267m, 4727.63m);
}
else if (UtcTime.Minute == 18)
{
Transactions.CancelOpenOrders("BTCUSD");
LimitOrder("BTCUSD", 0.10547724m, 4740.42m);
}
else if (UtcTime.Minute == 24)
{
Transactions.CancelOpenOrders("BTCUSD");
}
}
/// <summary>
/// Order fill event handler. On an order fill update the resulting information is passed to this method.
/// </summary>
/// <param name="orderEvent">Order event details containing details of the events</param>
public override void OnOrderEvent(OrderEvent orderEvent)
{
Debug(orderEvent.ToString());
}
/// <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()
{
const int expectedOrders = 5;
var expectedStatus = new[] { OrderStatus.Invalid, OrderStatus.Filled, OrderStatus.Canceled, OrderStatus.Canceled, OrderStatus.Filled };
var orders = Transactions.GetOrders(x => true).ToList();
if (orders.Count != expectedOrders)
{
throw new Exception($"Expected orders: {expectedOrders}, actual orders: {orders.Count}");
}
for (var i = 0; i < expectedOrders; i++)
{
var order = orders[i];
if (order.Status != expectedStatus[i])
{
throw new Exception($"Invalid status for order {order.Id}, Expected: {expectedStatus[i]}, 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 };
/// <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", "2"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "-100.000%"},
{"Drawdown", "5.600%"},
{"Expectancy", "0"},
{"Net Profit", "-4.431%"},
{"Sharpe Ratio", "-23.129"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "-8.364"},
{"Beta", "395.811"},
{"Annual Standard Deviation", "0.243"},
{"Annual Variance", "0.059"},
{"Information Ratio", "-23.216"},
{"Tracking Error", "0.243"},
{"Treynor Ratio", "-0.014"},
{"Total Fees", "$0.00"}
};
}
}