AlexCatarino
dd14821e75
Creates a python wrapper for volatility models created in python algorithms and adds a method to the Security object to set such models. Adds an algorithm to show how volatility models can be implemented.
79 lines
2.9 KiB
C#
79 lines
2.9 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 Python.Runtime;
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using QuantConnect.Data;
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using QuantConnect.Securities;
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using System;
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using System.Collections.Generic;
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namespace QuantConnect.Python
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{
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/// <summary>
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/// Provides a volatility model that wraps a <see cref="PyObject"/> object that represents a model that computes the volatility of a security
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/// </summary>
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public class VolatilityModelPythonWrapper : IVolatilityModel
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{
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private readonly dynamic _model;
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/// <summary>
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/// Constructor for initialising the <see cref="VolatilityModelPythonWrapper"/> class with wrapped <see cref="PyObject"/> object
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/// </summary>
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/// <param name="model"> Represents a model that computes the volatility of a security</param>
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public VolatilityModelPythonWrapper(PyObject model)
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{
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_model = model;
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}
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/// <summary>
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/// Gets the volatility of the security as a percentage
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/// </summary>
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public decimal Volatility
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{
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get
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{
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return _model.Volatility;
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}
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}
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/// <summary>
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/// Updates this model using the new price information in
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/// the specified security instance
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/// </summary>
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/// <param name="security">The security to calculate volatility for</param>
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/// <param name="data">The new data used to update the model</param>
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public void Update(Security security, BaseData data)
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{
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using (Py.GIL())
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{
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_model.Update(security, data);
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}
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}
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/// <summary>
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/// Returns history requirements for the volatility model expressed in the form of history request
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/// </summary>
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/// <param name="security">The security of the request</param>
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/// <param name="utcTime">The date/time of the request</param>
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/// <returns>History request object list, or empty if no requirements</returns>
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public IEnumerable<HistoryRequest> GetHistoryRequirements(Security security, DateTime utcTime)
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{
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using (Py.GIL())
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{
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return _model.GetHistoryRequirements(security, utcTime);
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}
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}
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}
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} |