chore: import upstream snapshot with attribution
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/*
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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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using System.Linq;
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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 leg limit orders
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/// </summary>
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public class ComboLegLimitOrderAlgorithm : ComboOrderAlgorithm
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{
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private List<decimal> _originalLimitPrices = new();
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protected virtual bool AsynchronousOrders => false;
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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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foreach (var leg in legs)
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{
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_originalLimitPrices.Add(leg.OrderPrice.Value);
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leg.OrderPrice *= 2; // Won't fill
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}
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return ComboLegLimitOrder(legs, quantity, asynchronous: AsynchronousOrders);
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}
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protected override void UpdateComboOrder(List<OrderTicket> tickets)
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{
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// Let's updated the limit prices to the original values
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for (int i = 0; i < tickets.Count; i++)
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{
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tickets[i].Update(new UpdateOrderFields { LimitPrice = _originalLimitPrices[i] });
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}
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}
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public override void OnEndOfAlgorithm()
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{
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base.OnEndOfAlgorithm();
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if (FillOrderEvents.Zip(OrderLegs).Any(x => x.Second.OrderPrice < x.First.FillPrice))
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{
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throw new RegressionTestException($"Limit price expected to be greater that the fill price for each order. Limit prices: {string.Join(",", OrderLegs.Select(x => x.OrderPrice))} Fill prices: {string.Join(",", FillOrderEvents.Select(x => x.FillPrice))}");
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}
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foreach (var ticket in Transactions.GetOrderTickets())
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{
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if (ticket.SubmitRequest.Asynchronous != AsynchronousOrders)
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{
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throw new RegressionTestException("Expected all orders to have the same asynchronous flag as the algorithm.");
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}
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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", "198524"},
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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", "$58000.00"},
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{"Lowest Capacity Asset", "GOOCV W78ZERHAT67A|GOOCV VP83T1ZUHROL"},
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{"Portfolio Turnover", "30.22%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "6168ffaa5b9f3c389f5da52e90455889"}
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};
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}
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}
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