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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*/
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using System.Collections.Generic;
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using QuantConnect.Data;
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using QuantConnect.Interfaces;
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using QuantConnect.Indicators;
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using QuantConnect.Securities.Option;
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using System;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// This example demonstrates how to override the option pricing model with the
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/// <see cref="IndicatorBasedOptionPriceModel"/> for a given option security.
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/// </summary>
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public class IndicatorBasedOptionPricingModelRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private bool _checked;
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private Option _option;
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protected virtual DateTime TestStartDate => new(2015, 12, 24);
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protected virtual DateTime TestEndDate => new(2015, 12, 24);
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public override void Initialize()
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{
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SetStartDate(TestStartDate);
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SetEndDate(TestEndDate);
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SetCash(100000);
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_option = GetOption();
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if (_option.PriceModel is not IndicatorBasedOptionPriceModel)
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{
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throw new RegressionTestException("Option pricing model was not set to IndicatorBasedOptionPriceModel, which should be the default");
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}
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}
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protected virtual Option GetOption()
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{
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var equity = AddEquity("GOOG");
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var option = AddOption(equity.Symbol);
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option.SetFilter(u => u.Strikes(-2, +2).Expiration(0, 180));
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return option;
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}
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public override void OnData(Slice slice)
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{
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if (!_checked && slice.OptionChains.TryGetValue(_option.Symbol, out var chain))
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{
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foreach (var contract in chain)
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{
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var contractSecurity = Securities[contract.Symbol] as Option;
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if (contractSecurity.PriceModel is not IndicatorBasedOptionPriceModel)
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{
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throw new RegressionTestException("Contract security pricing model was not set to IndicatorBasedOptionPriceModel");
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}
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var theoreticalPrice = contract.TheoreticalPrice;
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var iv = contract.ImpliedVolatility;
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var greeks = contract.Greeks;
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Log($"{contract.Symbol}:: Theoretical Price: {theoreticalPrice}, IV: {iv}, " +
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$"Delta: {greeks.Delta}, Gamma: {greeks.Gamma}, Vega: {greeks.Vega}, " +
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$"Theta: {greeks.Theta}, Rho: {greeks.Rho}, Lambda: {greeks.Lambda}");
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// Sanity check values
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var theoreticalPriceChecked = false;
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// If IV is zero (model could not converge) we skip the theoretical price check, as it will be zero too
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if (iv != 0)
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{
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if (theoreticalPrice <= 0)
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{
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throw new RegressionTestException($"Invalid theoretical price for {contract.Symbol}: {theoreticalPrice}");
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}
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theoreticalPriceChecked = true;
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}
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// We check for all greeks and IV together. e.g. IV could be zero if the model can't converge, say for instance if a contract is iliquid or deep ITM/OTM
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if (greeks == null ||
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(iv == 0 && greeks.Delta == 0 && greeks.Gamma == 0 && greeks.Vega== 0 && greeks.Theta == 0 && greeks.Rho == 0))
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{
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throw new RegressionTestException($"Invalid Greeks for {contract.Symbol}");
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}
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// Manually evaluate the price model, just in case
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var result = contractSecurity.EvaluatePriceModel(slice, contract);
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if (result == null ||
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result.TheoreticalPrice != theoreticalPrice ||
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result.ImpliedVolatility != iv ||
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result.Greeks.Delta != greeks.Delta ||
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result.Greeks.Gamma != greeks.Gamma ||
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result.Greeks.Vega != greeks.Vega ||
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result.Greeks.Theta != greeks.Theta ||
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result.Greeks.Rho != greeks.Rho)
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{
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throw new RegressionTestException($"EvaluatePriceModel returned different results for {contract.Symbol}");
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}
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_checked |= theoreticalPriceChecked;
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}
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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 (!_checked)
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{
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throw new RegressionTestException("Option chain was never received.");
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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 virtual long DataPoints => 37131;
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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", "0"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "0%"},
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{"Drawdown", "0%"},
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{"Expectancy", "0"},
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{"Start Equity", "100000"},
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{"End Equity", "100000"},
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{"Net Profit", "0%"},
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{"Sharpe Ratio", "0"},
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{"Sortino Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "0%"},
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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"},
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{"Beta", "0"},
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{"Annual Standard Deviation", "0"},
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{"Annual Variance", "0"},
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{"Information Ratio", "0"},
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{"Tracking Error", "0"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$0.00"},
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{"Estimated Strategy Capacity", "$0"},
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{"Lowest Capacity Asset", ""},
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{"Portfolio Turnover", "0%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
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};
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}
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}
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