chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
@@ -0,0 +1,34 @@
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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.
|
||||
* 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.Collections.Generic;
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using QuantConnect.Algorithm.Framework.Alphas;
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namespace QuantConnect.Algorithm.Framework.Portfolio
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{
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/// <summary>
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/// Algorithm framework model that
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/// </summary>
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public interface IPortfolioConstructionModel : INotifiedSecurityChanges
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{
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/// <summary>
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/// Create portfolio targets from the specified insights
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/// </summary>
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/// <param name="algorithm">The algorithm instance</param>
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/// <param name="insights">The insights to create portfolio targets from</param>
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/// <returns>An enumerable of portfolio targets to be sent to the execution model</returns>
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IEnumerable<IPortfolioTarget> CreateTargets(QCAlgorithm algorithm, Insight[] insights);
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}
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}
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@@ -0,0 +1,32 @@
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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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namespace QuantConnect.Algorithm.Framework.Portfolio
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{
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/// <summary>
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/// Interface for portfolio optimization algorithms
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/// </summary>
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public interface IPortfolioOptimizer
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{
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/// <summary>
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/// Perform portfolio optimization for a provided matrix of historical returns and an array of expected returns
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/// </summary>
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/// <param name="historicalReturns">Matrix of annualized historical returns where each column represents a security and each row returns for the given date/time (size: K x N).</param>
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/// <param name="expectedReturns">Array of double with the portfolio annualized expected returns (size: K x 1).</param>
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/// <param name="covariance">Multi-dimensional array of double with the portfolio covariance of annualized returns (size: K x K).</param>
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/// <returns>Array of double with the portfolio weights (size: K x 1)</returns>
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double[] Optimize(double[,] historicalReturns, double[] expectedReturns = null, double[,] covariance = null);
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}
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}
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@@ -0,0 +1,36 @@
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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.Collections.Generic;
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using System.Linq;
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using QuantConnect.Algorithm.Framework.Alphas;
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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 does nothing
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/// </summary>
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public class NullPortfolioConstructionModel : PortfolioConstructionModel
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{
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/// <summary>
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/// Create Targets; Does nothing in this implementation and returns an empty IEnumerable
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/// </summary>
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/// <returns>Empty IEnumerable of <see cref="IPortfolioTarget"/>s</returns>
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public override IEnumerable<IPortfolioTarget> CreateTargets(QCAlgorithm algorithm, Insight[] insights)
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{
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return Enumerable.Empty<IPortfolioTarget>();
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}
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}
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}
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@@ -0,0 +1,19 @@
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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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from AlgorithmImports import *
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class NullPortfolioConstructionModel(PortfolioConstructionModel):
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'''Provides an implementation of IPortfolioConstructionModel that does nothing'''
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def create_targets(self, algorithm, insights):
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return []
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@@ -0,0 +1,38 @@
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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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namespace QuantConnect.Algorithm.Framework.Portfolio
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{
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/// <summary>
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/// Specifies the bias of the portfolio (Short, Long/Short, Long)
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/// </summary>
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public enum PortfolioBias
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{
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/// <summary>
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/// Portfolio can only have short positions (-1)
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/// </summary>
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Short = -1,
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/// <summary>
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/// Portfolio can have both long and short positions (0)
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/// </summary>
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LongShort = 0,
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/// <summary>
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/// Portfolio can only have long positions (1)
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/// </summary>
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Long = 1
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}
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}
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@@ -0,0 +1,337 @@
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/*
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||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* 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
|
||||
* 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.Data.UniverseSelection;
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using QuantConnect.Interfaces;
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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 a base class for portfolio construction models
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/// </summary>
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public class PortfolioConstructionModel : IPortfolioConstructionModel
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{
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private Func<DateTime, DateTime?> _rebalancingFunc;
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private DateTime? _rebalancingTime;
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private bool _securityChanges;
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/// <summary>
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/// True if should rebalance portfolio on security changes. True by default
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/// </summary>
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public virtual bool RebalanceOnSecurityChanges { get; set; } = true;
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/// <summary>
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/// True if should rebalance portfolio on new insights or expiration of insights. True by default
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/// </summary>
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public virtual bool RebalanceOnInsightChanges { get; set; } = true;
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/// <summary>
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/// The algorithm instance
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/// </summary>
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protected IAlgorithm Algorithm { get; private set; }
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/// <summary>
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/// This is required due to a limitation in PythonNet to resolved overriden methods.
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/// When Python calls a C# method that calls a method that's overriden in python it won't
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/// run the python implementation unless the call is performed through python too.
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/// </summary>
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protected PortfolioConstructionModelPythonWrapper PythonWrapper { get; set; }
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/// <summary>
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/// Initialize a new instance of <see cref="PortfolioConstructionModel"/>
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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. If null will be ignored</param>
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public PortfolioConstructionModel(Func<DateTime, DateTime?> rebalancingFunc)
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{
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_rebalancingFunc = rebalancingFunc;
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}
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/// <summary>
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/// Initialize a new instance of <see cref="PortfolioConstructionModel"/>
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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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public PortfolioConstructionModel(Func<DateTime, DateTime> rebalancingFunc = null)
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: this(rebalancingFunc != null ? (Func<DateTime, DateTime?>)(timeUtc => rebalancingFunc(timeUtc)) : null)
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{
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}
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/// <summary>
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/// Used to set the <see cref="PortfolioConstructionModelPythonWrapper"/> instance if any
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/// </summary>
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protected void SetPythonWrapper(PortfolioConstructionModelPythonWrapper pythonWrapper)
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{
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PythonWrapper = pythonWrapper;
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}
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/// <summary>
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/// Create portfolio targets from the specified insights
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/// </summary>
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/// <param name="algorithm">The algorithm instance</param>
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/// <param name="insights">The insights to create portfolio targets from</param>
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/// <returns>An enumerable of portfolio targets to be sent to the execution model</returns>
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public virtual IEnumerable<IPortfolioTarget> CreateTargets(QCAlgorithm algorithm, Insight[] insights)
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{
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Algorithm = algorithm;
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if (!(PythonWrapper?.IsRebalanceDue(insights, algorithm.UtcTime)
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?? IsRebalanceDue(insights, algorithm.UtcTime)))
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{
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return Enumerable.Empty<IPortfolioTarget>();
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}
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var targets = new List<IPortfolioTarget>();
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var lastActiveInsights = PythonWrapper?.GetTargetInsights()
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?? GetTargetInsights();
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var errorSymbols = new HashSet<Symbol>();
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// Determine target percent for the given insights
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var percents = PythonWrapper?.DetermineTargetPercent(lastActiveInsights)
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?? DetermineTargetPercent(lastActiveInsights);
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foreach (var insight in lastActiveInsights)
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{
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if (!percents.TryGetValue(insight, out var percent))
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{
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continue;
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}
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var target = PortfolioTarget.Percent(algorithm, insight.Symbol, percent);
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if (target != null)
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{
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targets.Add(target);
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}
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else
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{
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errorSymbols.Add(insight.Symbol);
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}
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}
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// Get expired insights and create flatten targets for each symbol
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var expiredInsights = Algorithm.Insights.RemoveExpiredInsights(algorithm.UtcTime);
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var expiredTargets = from insight in expiredInsights
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group insight.Symbol by insight.Symbol into g
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where !Algorithm.Insights.HasActiveInsights(g.Key, algorithm.UtcTime) && !errorSymbols.Contains(g.Key)
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select new PortfolioTarget(g.Key, 0);
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targets.AddRange(expiredTargets);
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|
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return targets;
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}
|
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/// <summary>
|
||||
/// Event fired each time the we add/remove securities from the data feed
|
||||
/// </summary>
|
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/// <param name="algorithm">The algorithm instance that experienced the change in securities</param>
|
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/// <param name="changes">The security additions and removals from the algorithm</param>
|
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public virtual void OnSecuritiesChanged(QCAlgorithm algorithm, SecurityChanges changes)
|
||||
{
|
||||
Algorithm ??= algorithm;
|
||||
|
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_securityChanges = changes != SecurityChanges.None;
|
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// Get removed symbol and invalidate them in the insight collection
|
||||
var removedSymbols = changes.RemovedSecurities.Select(x => x.Symbol);
|
||||
algorithm?.Insights.Expire(removedSymbols);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Gets the target insights to calculate a portfolio target percent for
|
||||
/// </summary>
|
||||
/// <returns>An enumerable of the target insights</returns>
|
||||
protected virtual List<Insight> GetTargetInsights()
|
||||
{
|
||||
// Validate we should create a target for this insight
|
||||
bool IsValidInsight(Insight insight) => PythonWrapper?.ShouldCreateTargetForInsight(insight)
|
||||
?? ShouldCreateTargetForInsight(insight);
|
||||
|
||||
// Get insight that haven't expired of each symbol that is still in the universe
|
||||
var activeInsights = Algorithm.Insights.GetActiveInsights(Algorithm.UtcTime).Where(IsValidInsight);
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||||
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||||
// Get the last generated active insight for each symbol
|
||||
return (from insight in activeInsights
|
||||
group insight by insight.Symbol into g
|
||||
select g.OrderBy(x => x.GeneratedTimeUtc).Last()).ToList();
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Method that will determine if the portfolio construction model should create a
|
||||
/// target for this insight
|
||||
/// </summary>
|
||||
/// <param name="insight">The insight to create a target for</param>
|
||||
/// <returns>True if the portfolio should create a target for the insight</returns>
|
||||
protected virtual bool ShouldCreateTargetForInsight(Insight insight)
|
||||
{
|
||||
return true;
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Will determine the target percent for each insight
|
||||
/// </summary>
|
||||
/// <param name="activeInsights">The active insights to generate a target for</param>
|
||||
/// <returns>A target percent for each insight</returns>
|
||||
protected virtual Dictionary<Insight, double> DetermineTargetPercent(List<Insight> activeInsights)
|
||||
{
|
||||
throw new NotImplementedException("Types deriving from 'PortfolioConstructionModel' must implement the 'Dictionary<Insight, double> DetermineTargetPercent(ICollection<Insight>)' method.");
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Python helper method to set the rebalancing function.
|
||||
/// This is required due to a python net limitation not being able to use the base type constructor, and also because
|
||||
/// when python algorithms use C# portfolio construction models, it can't convert python methods into func nor resolve
|
||||
/// the correct constructor for the date rules, timespan parameter.
|
||||
/// For performance we prefer python algorithms using the C# implementation
|
||||
/// </summary>
|
||||
/// <param name="rebalance">Rebalancing func or if a date rule, timedelta will be converted into func.
|
||||
/// For a given algorithm UTC DateTime the func returns the next expected rebalance time
|
||||
/// or null if unknown, in which case the function will be called again in the next loop. Returning current time
|
||||
/// will trigger rebalance. If null will be ignored</param>
|
||||
protected void SetRebalancingFunc(PyObject rebalance)
|
||||
{
|
||||
IDateRule dateRules;
|
||||
TimeSpan timeSpan;
|
||||
if (rebalance.TryConvert(out dateRules))
|
||||
{
|
||||
_rebalancingFunc = dateRules.ToFunc();
|
||||
}
|
||||
else if (!rebalance.TrySafeAs(out _rebalancingFunc))
|
||||
{
|
||||
try
|
||||
{
|
||||
using (Py.GIL())
|
||||
{
|
||||
// try convert does not work for timespan
|
||||
timeSpan = rebalance.As<TimeSpan>();
|
||||
if (timeSpan != default(TimeSpan))
|
||||
{
|
||||
_rebalancingFunc = time => time.Add(timeSpan);
|
||||
}
|
||||
}
|
||||
}
|
||||
catch
|
||||
{
|
||||
_rebalancingFunc = null;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Determines if the portfolio should be rebalanced base on the provided rebalancing func,
|
||||
/// if any security change have been taken place or if an insight has expired or a new insight arrived
|
||||
/// If the rebalancing function has not been provided will return true.
|
||||
/// </summary>
|
||||
/// <param name="insights">The insights to create portfolio targets from</param>
|
||||
/// <param name="algorithmUtc">The current algorithm UTC time</param>
|
||||
/// <returns>True if should rebalance</returns>
|
||||
protected virtual bool IsRebalanceDue(Insight[] insights, DateTime algorithmUtc)
|
||||
{
|
||||
// if there is no rebalance func set, just return true but refresh state
|
||||
// just in case the rebalance func is going to be set.
|
||||
if (_rebalancingFunc == null)
|
||||
{
|
||||
RefreshRebalance(algorithmUtc);
|
||||
return true;
|
||||
}
|
||||
|
||||
// we always get the next expiry time
|
||||
// we don't know if a new insight was added or removed
|
||||
var nextInsightExpiryTime = Algorithm.Insights.GetNextExpiryTime();
|
||||
|
||||
if (_rebalancingTime == null)
|
||||
{
|
||||
_rebalancingTime = _rebalancingFunc(algorithmUtc);
|
||||
|
||||
if (_rebalancingTime != null && _rebalancingTime <= algorithmUtc)
|
||||
{
|
||||
// if the rebalancing time stopped being null and is current time
|
||||
// we will ask for the next rebalance time in the next loop.
|
||||
// we don't want to call the '_rebalancingFunc' twice in the same loop,
|
||||
// since its internal state machine will probably be in the same state.
|
||||
_rebalancingTime = null;
|
||||
_securityChanges = false;
|
||||
return true;
|
||||
}
|
||||
}
|
||||
|
||||
if (_rebalancingTime != null && _rebalancingTime <= algorithmUtc
|
||||
|| RebalanceOnSecurityChanges && _securityChanges
|
||||
|| RebalanceOnInsightChanges
|
||||
&& (insights.Length != 0
|
||||
|| nextInsightExpiryTime != null && nextInsightExpiryTime < algorithmUtc))
|
||||
{
|
||||
RefreshRebalance(algorithmUtc);
|
||||
return true;
|
||||
}
|
||||
|
||||
return false;
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Refresh the next rebalance time and clears the security changes flag
|
||||
/// </summary>
|
||||
protected void RefreshRebalance(DateTime algorithmUtc)
|
||||
{
|
||||
if (_rebalancingFunc != null)
|
||||
{
|
||||
_rebalancingTime = _rebalancingFunc(algorithmUtc);
|
||||
}
|
||||
_securityChanges = false;
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Helper class that can be used by the different <see cref="IPortfolioConstructionModel"/>
|
||||
/// implementations to filter <see cref="Insight"/> instances with an invalid
|
||||
/// <see cref="Insight.Magnitude"/> value based on the <see cref="IAlgorithmSettings"/>
|
||||
/// </summary>
|
||||
/// <param name="algorithm">The algorithm instance</param>
|
||||
/// <param name="insights">The insight collection to filter</param>
|
||||
/// <returns>Returns a new array of insights removing invalid ones</returns>
|
||||
protected static Insight[] FilterInvalidInsightMagnitude(IAlgorithm algorithm, Insight[] insights)
|
||||
{
|
||||
var result = insights.Where(insight =>
|
||||
{
|
||||
if (!insight.Magnitude.HasValue || insight.Magnitude == 0)
|
||||
{
|
||||
return true;
|
||||
}
|
||||
|
||||
var absoluteMagnitude = Math.Abs(insight.Magnitude.Value);
|
||||
if (absoluteMagnitude > (double)algorithm.Settings.MaxAbsolutePortfolioTargetPercentage
|
||||
|| absoluteMagnitude < (double)algorithm.Settings.MinAbsolutePortfolioTargetPercentage)
|
||||
{
|
||||
algorithm.Error("PortfolioConstructionModel.FilterInvalidInsightMagnitude():" +
|
||||
$"The insight target Magnitude: {insight.Magnitude}, will not comply with the current " +
|
||||
$"'Algorithm.Settings' 'MaxAbsolutePortfolioTargetPercentage': {algorithm.Settings.MaxAbsolutePortfolioTargetPercentage}" +
|
||||
$" or 'MinAbsolutePortfolioTargetPercentage': {algorithm.Settings.MinAbsolutePortfolioTargetPercentage}. Skipping insight."
|
||||
);
|
||||
return false;
|
||||
}
|
||||
|
||||
return true;
|
||||
});
|
||||
return result.ToArray();
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,156 @@
|
||||
/*
|
||||
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
|
||||
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
|
||||
*
|
||||
* Licensed under the Apache License, Version 2.0 (the "License");
|
||||
* you may not use this file except in compliance with the License.
|
||||
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
|
||||
*
|
||||
* Unless required by applicable law or agreed to in writing, software
|
||||
* distributed under the License is distributed on an "AS IS" BASIS,
|
||||
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||
* See the License for the specific language governing permissions and
|
||||
* limitations under the License.
|
||||
*/
|
||||
|
||||
using Python.Runtime;
|
||||
using QuantConnect.Algorithm.Framework.Alphas;
|
||||
using QuantConnect.Data.UniverseSelection;
|
||||
using QuantConnect.Python;
|
||||
using System;
|
||||
using System.Collections.Generic;
|
||||
|
||||
namespace QuantConnect.Algorithm.Framework.Portfolio
|
||||
{
|
||||
/// <summary>
|
||||
/// Provides an implementation of <see cref="IPortfolioConstructionModel"/> that wraps a <see cref="PyObject"/> object
|
||||
/// </summary>
|
||||
public class PortfolioConstructionModelPythonWrapper : PortfolioConstructionModel
|
||||
{
|
||||
private readonly BasePythonWrapper<PortfolioConstructionModel> _model;
|
||||
private readonly bool _implementsDetermineTargetPercent;
|
||||
|
||||
/// <summary>
|
||||
/// True if should rebalance portfolio on security changes. True by default
|
||||
/// </summary>
|
||||
public override bool RebalanceOnSecurityChanges
|
||||
{
|
||||
get
|
||||
{
|
||||
return _model.GetProperty<bool>(nameof(RebalanceOnSecurityChanges));
|
||||
}
|
||||
set
|
||||
{
|
||||
_model.SetProperty(nameof(RebalanceOnSecurityChanges), value);
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// True if should rebalance portfolio on new insights or expiration of insights. True by default
|
||||
/// </summary>
|
||||
public override bool RebalanceOnInsightChanges
|
||||
{
|
||||
get
|
||||
{
|
||||
return _model.GetProperty<bool>(nameof(RebalanceOnInsightChanges));
|
||||
}
|
||||
set
|
||||
{
|
||||
_model.SetProperty(nameof(RebalanceOnInsightChanges), value);
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Constructor for initialising the <see cref="IPortfolioConstructionModel"/> class with wrapped <see cref="PyObject"/> object
|
||||
/// </summary>
|
||||
/// <param name="model">Model defining how to build a portfolio from alphas</param>
|
||||
public PortfolioConstructionModelPythonWrapper(PyObject model)
|
||||
{
|
||||
_model = new BasePythonWrapper<PortfolioConstructionModel>(model, false);
|
||||
using (Py.GIL())
|
||||
{
|
||||
foreach (var attributeName in new[] { "CreateTargets", "OnSecuritiesChanged" })
|
||||
{
|
||||
if (!_model.HasAttr(attributeName))
|
||||
{
|
||||
throw new NotImplementedException($"IPortfolioConstructionModel.{attributeName} must be implemented. Please implement this missing method on {model.GetPythonType()}");
|
||||
}
|
||||
}
|
||||
|
||||
_model.InvokeVoidMethod(nameof(SetPythonWrapper), this);
|
||||
|
||||
_implementsDetermineTargetPercent = model.GetPythonMethod("DetermineTargetPercent") != null;
|
||||
}
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Create portfolio targets from the specified insights
|
||||
/// </summary>
|
||||
/// <param name="algorithm">The algorithm instance</param>
|
||||
/// <param name="insights">The insights to create portfolio targets from</param>
|
||||
/// <returns>An enumerable of portfolio targets to be sent to the execution model</returns>
|
||||
public override IEnumerable<IPortfolioTarget> CreateTargets(QCAlgorithm algorithm, Insight[] insights)
|
||||
{
|
||||
return _model.InvokeMethodAndEnumerate<IPortfolioTarget>(nameof(CreateTargets), algorithm, insights);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Event fired each time the we add/remove securities from the data feed
|
||||
/// </summary>
|
||||
/// <param name="algorithm">The algorithm instance that experienced the change in securities</param>
|
||||
/// <param name="changes">The security additions and removals from the algorithm</param>
|
||||
public override void OnSecuritiesChanged(QCAlgorithm algorithm, SecurityChanges changes)
|
||||
{
|
||||
_model.InvokeVoidMethod(nameof(OnSecuritiesChanged), algorithm, changes);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Method that will determine if the portfolio construction model should create a
|
||||
/// target for this insight
|
||||
/// </summary>
|
||||
/// <param name="insight">The insight to create a target for</param>
|
||||
/// <returns>True if the portfolio should create a target for the insight</returns>
|
||||
protected override bool ShouldCreateTargetForInsight(Insight insight)
|
||||
{
|
||||
return _model.InvokeMethod<bool>(nameof(ShouldCreateTargetForInsight), insight);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Determines if the portfolio should be rebalanced base on the provided rebalancing func,
|
||||
/// if any security change have been taken place or if an insight has expired or a new insight arrived
|
||||
/// If the rebalancing function has not been provided will return true.
|
||||
/// </summary>
|
||||
/// <param name="insights">The insights to create portfolio targets from</param>
|
||||
/// <param name="algorithmUtc">The current algorithm UTC time</param>
|
||||
/// <returns>True if should rebalance</returns>
|
||||
protected override bool IsRebalanceDue(Insight[] insights, DateTime algorithmUtc)
|
||||
{
|
||||
return _model.InvokeMethod<bool>(nameof(IsRebalanceDue), insights, algorithmUtc);
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Gets the target insights to calculate a portfolio target percent for
|
||||
/// </summary>
|
||||
/// <returns>An enumerable of the target insights</returns>
|
||||
protected override List<Insight> GetTargetInsights()
|
||||
{
|
||||
return _model.InvokeMethod<List<Insight>>(nameof(GetTargetInsights));
|
||||
}
|
||||
|
||||
/// <summary>
|
||||
/// Will determine the target percent for each insight
|
||||
/// </summary>
|
||||
/// <param name="activeInsights">The active insights to generate a target for</param>
|
||||
/// <returns>A target percent for each insight</returns>
|
||||
protected override Dictionary<Insight, double> DetermineTargetPercent(List<Insight> activeInsights)
|
||||
{
|
||||
if (!_implementsDetermineTargetPercent)
|
||||
{
|
||||
// the implementation is in C#
|
||||
return _model.InvokeMethod<Dictionary<Insight, double>>(nameof(DetermineTargetPercent), activeInsights);
|
||||
}
|
||||
|
||||
return _model.InvokeMethodAndGetDictionary<Insight, double>(nameof(DetermineTargetPercent), activeInsights);
|
||||
}
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user