wehub-resource-sync
102 lines
4.4 KiB
C#
102 lines
4.4 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 System.Linq;
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using Python.Runtime;
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using QuantConnect.Packets;
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using System.Collections.Generic;
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using QuantConnect.Lean.Engine.Results;
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namespace QuantConnect.Report.ReportElements
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{
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internal sealed class RollingPortfolioBetaReportElement : ChartReportElement
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{
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private LiveResult _live;
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private BacktestResult _backtest;
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/// <summary>
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/// The number of trading days per year to get better result of statistics
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/// </summary>
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private int _tradingDaysPerYear;
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/// <summary>
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/// Create a new plot of the rolling portfolio beta to equities
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/// </summary>
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/// <param name="name">Name of the widget</param>
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/// <param name="key">Location of injection</param>
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/// <param name="backtest">Backtest result object</param>
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/// <param name="live">Live result object</param>
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/// <param name="tradingDaysPerYear">The number of trading days per year to get better result of statistics</param>
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public RollingPortfolioBetaReportElement(string name, string key, BacktestResult backtest, LiveResult live, int tradingDaysPerYear)
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{
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_live = live;
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_backtest = backtest;
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Name = name;
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Key = key;
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_tradingDaysPerYear = tradingDaysPerYear;
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}
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/// <summary>
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/// Generate the rolling portfolio beta to equities plot using the python libraries.
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/// </summary>
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public override string Render()
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{
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var backtestPoints = GetReturnSeries(_backtest);
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var backtestBenchmarkPoints = ResultsUtil.BenchmarkPoints(_backtest);
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var livePoints = GetReturnSeries(_live);
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var liveBenchmarkPoints = ResultsUtil.BenchmarkPoints(_live);
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var base64 = "";
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using (Py.GIL())
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{
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var backtestList = new PyList();
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var liveList = new PyList();
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var backtestRollingBetaSixMonths = Rolling.Beta(backtestPoints, backtestBenchmarkPoints, windowSize: 22 * 6);
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var backtestRollingBetaTwelveMonths = Rolling.Beta(backtestPoints, backtestBenchmarkPoints, windowSize: _tradingDaysPerYear);
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backtestList.Append(backtestRollingBetaSixMonths.Keys.ToList().ToPython());
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backtestList.Append(backtestRollingBetaSixMonths.Values.ToList().ToPython());
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backtestList.Append(backtestRollingBetaTwelveMonths.Keys.ToList().ToPython());
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backtestList.Append(backtestRollingBetaTwelveMonths.Values.ToList().ToPython());
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var liveRollingBetaSixMonths = Rolling.Beta(livePoints, liveBenchmarkPoints, windowSize: 22 * 6);
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var liveRollingBetaTwelveMonths = Rolling.Beta(livePoints, liveBenchmarkPoints, windowSize: _tradingDaysPerYear);
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liveList.Append(liveRollingBetaSixMonths.Keys.ToList().ToPython());
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liveList.Append(liveRollingBetaSixMonths.Values.ToList().ToPython());
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liveList.Append(liveRollingBetaTwelveMonths.Keys.ToList().ToPython());
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liveList.Append(liveRollingBetaTwelveMonths.Values.ToList().ToPython());
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base64 = Charting.GetRollingBeta(backtestList, liveList);
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}
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return base64;
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}
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private static SortedList<DateTime, double> GetReturnSeries(Result leanResult)
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{
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var returnSeries = ResultsUtil.EquityPoints(leanResult, BaseResultsHandler.ReturnKey);
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if (returnSeries == null || returnSeries.Count == 0)
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{
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// for backwards compatibility
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returnSeries = ResultsUtil.EquityPoints(leanResult, "Daily Performance");
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}
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return returnSeries;
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}
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}
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}
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