wehub-resource-sync
124 lines
4.7 KiB
C#
124 lines
4.7 KiB
C#
/*
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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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using System.Collections.Generic;
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using QuantConnect.Data;
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using QuantConnect.Interfaces;
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using QuantConnect.Orders;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// This regression test algorithm reproduces GH issue 3239, where the stopLoss order
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/// place on <see cref="OnOrderEvent"/> was not being filled.
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/// </summary>
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public class StopLossOnOrderEventRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Symbol _spy;
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private bool _alreadyTraded;
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public override void Initialize()
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{
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SetStartDate(2013, 10, 07);
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SetEndDate(2013, 10, 11);
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_spy = AddEquity("SPY").Symbol;
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}
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public override void OnOrderEvent(OrderEvent orderEvent)
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{
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Debug($"{orderEvent}");
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var order = Transactions.GetOrderById(orderEvent.OrderId);
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if (order.Tag == "Entry" && orderEvent.Status == OrderStatus.Filled)
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{
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// Entry short $2 below
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var stopPrice = orderEvent.FillPrice - 2;
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var currencySymbol = Currencies.GetCurrencySymbol(order.PriceCurrency);
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Debug($"Enter short at {orderEvent.FillPrice} set STOPLOSS at {currencySymbol}{stopPrice}");
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StopMarketOrder(order.Symbol, -order.Quantity, stopPrice, tag: "StopLoss");
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}
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}
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public override void OnData(Slice slice)
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{
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if (!Portfolio.Invested && !_alreadyTraded)
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{
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_alreadyTraded = true;
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MarketOrder(_spy, -100, false, "Entry");
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Debug("Purchased Stock");
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}
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}
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/// <summary>
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/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
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/// </summary>
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public bool CanRunLocally { get; } = true;
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/// <summary>
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/// This is used by the regression test system to indicate which languages this algorithm is written in.
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/// </summary>
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public List<Language> Languages { get; } = new() { Language.CSharp };
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/// <summary>
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/// Data Points count of all timeslices of algorithm
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/// </summary>
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public long DataPoints => 3943;
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/// <summary>
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/// Data Points count of the algorithm history
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/// </summary>
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public int AlgorithmHistoryDataPoints => 0;
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/// <summary>
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/// Final status of the algorithm
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/// </summary>
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public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
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/// <summary>
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/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
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/// </summary>
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public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Orders", "2"},
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{"Average Win", "0%"},
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{"Average Loss", "0.00%"},
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{"Compounding Annual Return", "-0.359%"},
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{"Drawdown", "0.000%"},
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{"Expectancy", "-1"},
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{"Start Equity", "100000"},
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{"End Equity", "99995.41"},
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{"Net Profit", "-0.005%"},
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{"Sharpe Ratio", "0"},
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{"Sortino Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "0%"},
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{"Loss Rate", "100%"},
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{"Win Rate", "0%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "0"},
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{"Beta", "0"},
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{"Annual Standard Deviation", "0"},
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{"Annual Variance", "0"},
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{"Information Ratio", "-8.91"},
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{"Tracking Error", "0.223"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$2.00"},
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{"Estimated Strategy Capacity", "$18000000.00"},
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{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
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{"Portfolio Turnover", "5.79%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "d448232662a0cada4bf83ef8334bcb5b"}
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};
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}
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}
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