wehub-resource-sync
103 lines
4.1 KiB
C#
103 lines
4.1 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 QuantConnect.Orders;
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using System;
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using System.Collections.Generic;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Regression algorithm to test combo market orders
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/// </summary>
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public class ComboMarketOrderAlgorithm : ComboOrderAlgorithm
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{
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protected override IEnumerable<OrderTicket> PlaceComboOrder(List<Leg> legs, int quantity, decimal? limitPrice = null)
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{
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legs.ForEach(x => { x.OrderPrice = null; });
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return ComboMarketOrder(legs, quantity);
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}
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public override void OnOrderEvent(OrderEvent orderEvent)
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{
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base.OnOrderEvent(orderEvent);
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if (orderEvent.Status == OrderStatus.Filled && orderEvent.OrderFee.Value.Amount != (orderEvent.AbsoluteFillQuantity * 0.65m))
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{
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throw new RegressionTestException($"The fee for each order should be {orderEvent.AbsoluteFillQuantity * 0.65m} USD, but for order {orderEvent.OrderId} was {orderEvent.OrderFee}");
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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 override bool CanRunLocally => 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 override 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 override long DataPoints => 15023;
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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 override 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 override 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 override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Orders", "3"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "0%"},
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{"Drawdown", "0%"},
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{"Expectancy", "0"},
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{"Start Equity", "200000"},
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{"End Equity", "198024"},
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{"Net Profit", "0%"},
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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", "0%"},
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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", "0"},
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{"Tracking Error", "0"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$26.00"},
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{"Estimated Strategy Capacity", "$69000.00"},
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{"Lowest Capacity Asset", "GOOCV W78ZERHAT67A|GOOCV VP83T1ZUHROL"},
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{"Portfolio Turnover", "30.35%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "0b9f42bc22c9c7c382bc57a64c99f7e5"}
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};
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}
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}
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