135 lines
5.1 KiB
C#
135 lines
5.1 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 System;
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using QuantConnect.Data;
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using QuantConnect.Interfaces;
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using QuantConnect.Data.Market;
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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 reproducing GH issue #5232, where we expect SPWR to be mapped to SPWRA
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/// </summary>
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public class HourResolutionMappingEventRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private DateTime _dateTime;
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private SymbolChangedEvent _changedEvent;
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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(2008, 08, 20);
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SetEndDate(2008, 10, 1);
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AddEquity("SPWR", Resolution.Hour, fillForward:false);
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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="data">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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_dateTime = Time.Date;
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if (!Portfolio.Invested)
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{
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SetHoldings("SPWR", 1);
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}
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foreach (var symbolChangedEvent in slice.SymbolChangedEvents.Values)
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{
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_changedEvent = symbolChangedEvent;
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Log($"{Time}: {symbolChangedEvent.OldSymbol} -> {symbolChangedEvent.NewSymbol}");
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}
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}
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public override void OnEndOfAlgorithm()
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{
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if (_dateTime != EndDate.Date)
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{
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throw new RegressionTestException($"Last day was {_dateTime}, should be algorithm end date: {EndDate.Date}");
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}
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if (_changedEvent == null)
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{
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throw new RegressionTestException("We got not symbol change event! 'SPWR' should of been mapped");
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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 => 429;
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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", "-78.316%"},
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{"Drawdown", "31.700%"},
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{"Expectancy", "0"},
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{"Start Equity", "100000"},
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{"End Equity", "83636.96"},
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{"Net Profit", "-16.363%"},
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{"Sharpe Ratio", "-0.498"},
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{"Sortino Ratio", "-0.507"},
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{"Probabilistic Sharpe Ratio", "24.798%"},
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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", "0.357"},
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{"Beta", "2.004"},
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{"Annual Standard Deviation", "0.924"},
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{"Annual Variance", "0.854"},
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{"Information Ratio", "-0.073"},
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{"Tracking Error", "0.718"},
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{"Treynor Ratio", "-0.23"},
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{"Total Fees", "$5.40"},
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{"Estimated Strategy Capacity", "$2400000.00"},
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{"Lowest Capacity Asset", "SPWR TDQZFPKOZ5UT"},
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{"Portfolio Turnover", "2.34%"},
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{"Drawdown Recovery", "5"},
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{"OrderListHash", "cc6e8f0ec77d9ed25118562e954bb781"}
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};
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}
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}
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