wehub-resource-sync
129 lines
5.0 KiB
C#
129 lines
5.0 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;
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using QuantConnect.Data;
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using QuantConnect.Orders;
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using QuantConnect.Interfaces;
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using QuantConnect.Securities;
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using System.Collections.Generic;
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using QuantConnect.Securities.Future;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Continuous Futures Regression algorithm reproducing GH issue #6490 asserting limit if touched order works as expected
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/// </summary>
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public class ContinuousFutureLimitIfTouchedOrderRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private OrderTicket _ticket;
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private Future _continuousContract;
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/// <summary>
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/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
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/// </summary>
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public override void Initialize()
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{
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SetStartDate(2013, 10, 6);
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SetEndDate(2013, 10, 10);
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_continuousContract = AddFuture(Futures.Indices.SP500EMini,
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dataNormalizationMode: DataNormalizationMode.BackwardsRatio,
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dataMappingMode: DataMappingMode.LastTradingDay
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);
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}
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/// <summary>
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/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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/// </summary>
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/// <param name="slice">Slice object keyed by symbol containing the stock data</param>
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public override void OnData(Slice slice)
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{
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if (_ticket == null)
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{
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_ticket = LimitIfTouchedOrder(_continuousContract.Mapped, -1, _continuousContract.Price, _continuousContract.Price);
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}
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}
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public override void OnEndOfAlgorithm()
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{
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if (_ticket == null || _ticket.Status != OrderStatus.Filled)
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{
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throw new RegressionTestException("Order ticket was not placed or filled!");
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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 => 10883;
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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", "1"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "-99.012%"},
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{"Drawdown", "6.300%"},
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{"Expectancy", "0"},
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{"Start Equity", "100000"},
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{"End Equity", "93870.7"},
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{"Net Profit", "-6.129%"},
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{"Sharpe Ratio", "-2.199"},
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{"Sortino Ratio", "-2.305"},
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{"Probabilistic Sharpe Ratio", "5.122%"},
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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", "-0.984"},
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{"Beta", "-0.022"},
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{"Annual Standard Deviation", "0.449"},
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{"Annual Variance", "0.202"},
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{"Information Ratio", "-2.231"},
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{"Tracking Error", "0.513"},
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{"Treynor Ratio", "43.96"},
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{"Total Fees", "$2.15"},
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{"Estimated Strategy Capacity", "$2600000000.00"},
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{"Lowest Capacity Asset", "ES VMKLFZIH2MTD"},
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{"Portfolio Turnover", "16.49%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "d13f91ab95169699139d21685a5e346a"}
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};
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}
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}
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