chore: import upstream snapshot with attribution
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wehub-resource-sync
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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 System;
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using System.Collections.Generic;
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using System.Linq;
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using Python.Runtime;
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using QuantConnect.Algorithm.Framework.Alphas;
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using QuantConnect.Scheduling;
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namespace QuantConnect.Algorithm.Framework.Portfolio
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{
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/// <summary>
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/// Provides an implementation of <see cref="IPortfolioConstructionModel"/> that generates percent targets based on the
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/// <see cref="Insight.Weight"/>. The target percent holdings of each Symbol is given by the <see cref="Insight.Weight"/>
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/// from the last active <see cref="Insight"/> for that symbol.
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/// For insights of direction <see cref="InsightDirection.Up"/>, long targets are returned and for insights of direction
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/// <see cref="InsightDirection.Down"/>, short targets are returned.
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/// If the sum of all the last active <see cref="Insight"/> per symbol is bigger than 1, it will factor down each target
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/// percent holdings proportionally so the sum is 1.
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/// It will ignore <see cref="Insight"/> that have no <see cref="Insight.Weight"/> value.
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/// </summary>
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public class InsightWeightingPortfolioConstructionModel : EqualWeightingPortfolioConstructionModel
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{
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/// <summary>
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/// Initialize a new instance of <see cref="InsightWeightingPortfolioConstructionModel"/>
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/// </summary>
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/// <param name="rebalancingDateRules">The date rules used to define the next expected rebalance time
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/// in UTC</param>
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/// <param name="portfolioBias">Specifies the bias of the portfolio (Short, Long/Short, Long)</param>
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public InsightWeightingPortfolioConstructionModel(IDateRule rebalancingDateRules,
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PortfolioBias portfolioBias = PortfolioBias.LongShort)
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: base(rebalancingDateRules, portfolioBias)
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{
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}
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/// <summary>
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/// Initialize a new instance of <see cref="InsightWeightingPortfolioConstructionModel"/>
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/// </summary>
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/// <param name="rebalance">Rebalancing func or if a date rule, timedelta will be converted into func.
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/// For a given algorithm UTC DateTime the func returns the next expected rebalance time
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/// or null if unknown, in which case the function will be called again in the next loop. Returning current time
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/// will trigger rebalance. If null will be ignored</param>
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/// <param name="portfolioBias">Specifies the bias of the portfolio (Short, Long/Short, Long)</param>
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/// <remarks>This is required since python net can not convert python methods into func nor resolve the correct
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/// constructor for the date rules parameter.
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/// For performance we prefer python algorithms using the C# implementation</remarks>
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public InsightWeightingPortfolioConstructionModel(PyObject rebalance,
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PortfolioBias portfolioBias = PortfolioBias.LongShort)
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: base(rebalance, portfolioBias)
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{
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}
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/// <summary>
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/// Initialize a new instance of <see cref="InsightWeightingPortfolioConstructionModel"/>
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/// </summary>
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/// <param name="rebalancingFunc">For a given algorithm UTC DateTime returns the next expected rebalance time
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/// or null if unknown, in which case the function will be called again in the next loop. Returning current time
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/// will trigger rebalance.</param>
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/// <param name="portfolioBias">Specifies the bias of the portfolio (Short, Long/Short, Long)</param>
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public InsightWeightingPortfolioConstructionModel(Func<DateTime, DateTime?> rebalancingFunc,
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PortfolioBias portfolioBias = PortfolioBias.LongShort)
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: base(rebalancingFunc, portfolioBias)
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{
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}
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/// <summary>
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/// Initialize a new instance of <see cref="InsightWeightingPortfolioConstructionModel"/>
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/// </summary>
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/// <param name="rebalancingFunc">For a given algorithm UTC DateTime returns the next expected rebalance UTC time.
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/// Returning current time will trigger rebalance. If null will be ignored</param>
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/// <param name="portfolioBias">Specifies the bias of the portfolio (Short, Long/Short, Long)</param>
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public InsightWeightingPortfolioConstructionModel(Func<DateTime, DateTime> rebalancingFunc,
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PortfolioBias portfolioBias = PortfolioBias.LongShort)
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: base(rebalancingFunc, portfolioBias)
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{
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}
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/// <summary>
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/// Initialize a new instance of <see cref="InsightWeightingPortfolioConstructionModel"/>
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/// </summary>
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/// <param name="timeSpan">Rebalancing frequency</param>
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/// <param name="portfolioBias">Specifies the bias of the portfolio (Short, Long/Short, Long)</param>
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public InsightWeightingPortfolioConstructionModel(TimeSpan timeSpan,
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PortfolioBias portfolioBias = PortfolioBias.LongShort)
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: base(timeSpan, portfolioBias)
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{
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}
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/// <summary>
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/// Initialize a new instance of <see cref="InsightWeightingPortfolioConstructionModel"/>
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/// </summary>
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/// <param name="resolution">Rebalancing frequency</param>
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/// <param name="portfolioBias">Specifies the bias of the portfolio (Short, Long/Short, Long)</param>
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public InsightWeightingPortfolioConstructionModel(Resolution resolution = Resolution.Daily,
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PortfolioBias portfolioBias = PortfolioBias.LongShort)
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: base(resolution, portfolioBias)
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{
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}
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/// <summary>
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/// Method that will determine if the portfolio construction model should create a
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/// target for this insight
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/// </summary>
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/// <param name="insight">The insight to create a target for</param>
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/// <returns>True if the portfolio should create a target for the insight</returns>
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protected override bool ShouldCreateTargetForInsight(Insight insight)
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{
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return insight.Weight.HasValue;
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}
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/// <summary>
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/// Will determine the target percent for each insight
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/// </summary>
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/// <param name="activeInsights">The active insights to generate a target for</param>
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/// <returns>A target percent for each insight</returns>
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protected override Dictionary<Insight, double> DetermineTargetPercent(List<Insight> activeInsights)
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{
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var result = new Dictionary<Insight, double>();
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// We will adjust weights proportionally in case the sum is > 1 so it sums to 1.
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var weightSums = activeInsights.Where(RespectPortfolioBias).Sum(insight => GetValue(insight));
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var weightFactor = 1.0;
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if (weightSums > 1)
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{
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weightFactor = 1 / weightSums;
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}
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foreach (var insight in activeInsights)
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{
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result[insight] = (int)(RespectPortfolioBias(insight) ? insight.Direction : InsightDirection.Flat)
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* GetValue(insight)
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* weightFactor;
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}
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return result;
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}
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/// <summary>
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/// Method that will determine which member will be used to compute the weights and gets its value
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/// </summary>
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/// <param name="insight">The insight to create a target for</param>
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/// <returns>The value of the selected insight member</returns>
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protected virtual double GetValue(Insight insight) => insight.Weight != null ? Math.Abs((double)insight.Weight) : 0;
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}
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}
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