quantconnect--lean/Algorithm.CSharp/IndicatorBasedOptionPricingModelRegressionAlgorithm.cs

/*
 * 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 System.Collections.Generic;
using QuantConnect.Data;
using QuantConnect.Interfaces;
using QuantConnect.Indicators;
using QuantConnect.Securities.Option;
using System;

namespace QuantConnect.Algorithm.CSharp
{
    /// <summary>
    /// This example demonstrates how to override the option pricing model with the
    /// <see cref="IndicatorBasedOptionPriceModel"/> for a given option security.
    /// </summary>
    public class IndicatorBasedOptionPricingModelRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
    {
        private bool _checked;

        private Option _option;

        protected virtual DateTime TestStartDate => new(2015, 12, 24);

        protected virtual DateTime TestEndDate => new(2015, 12, 24);

        public override void Initialize()
        {
            SetStartDate(TestStartDate);
            SetEndDate(TestEndDate);
            SetCash(100000);

            _option = GetOption();

            if (_option.PriceModel is not IndicatorBasedOptionPriceModel)
            {
                throw new RegressionTestException("Option pricing model was not set to IndicatorBasedOptionPriceModel, which should be the default");
            }
        }

        protected virtual Option GetOption()
        {
            var equity = AddEquity("GOOG");
            var option = AddOption(equity.Symbol);
            option.SetFilter(u => u.Strikes(-2, +2).Expiration(0, 180));
            return option;
        }

        public override void OnData(Slice slice)
        {
            if (!_checked  && slice.OptionChains.TryGetValue(_option.Symbol, out var chain))
            {
                foreach (var contract in chain)
                {
                    var contractSecurity = Securities[contract.Symbol] as Option;
                    if (contractSecurity.PriceModel is not IndicatorBasedOptionPriceModel)
                    {
                        throw new RegressionTestException("Contract security pricing model was not set to IndicatorBasedOptionPriceModel");
                    }

                    var theoreticalPrice = contract.TheoreticalPrice;
                    var iv = contract.ImpliedVolatility;
                    var greeks = contract.Greeks;

                    Log($"{contract.Symbol}:: Theoretical Price: {theoreticalPrice}, IV: {iv}, " +
                           $"Delta: {greeks.Delta}, Gamma: {greeks.Gamma}, Vega: {greeks.Vega}, " +
                           $"Theta: {greeks.Theta}, Rho: {greeks.Rho}, Lambda: {greeks.Lambda}");

                    // Sanity check values

                    var theoreticalPriceChecked = false;
                    // If IV is zero (model could not converge) we skip the theoretical price check, as it will be zero too
                    if (iv != 0)
                    {
                        if (theoreticalPrice <= 0)
                        {
                            throw new RegressionTestException($"Invalid theoretical price for {contract.Symbol}: {theoreticalPrice}");
                        }
                        theoreticalPriceChecked = true;
                    }
                    // We check for all greeks and IV together. e.g. IV could be zero if the model can't converge, say for instance if a contract is iliquid or deep ITM/OTM
                    if (greeks == null ||
                        (iv == 0 && greeks.Delta == 0 && greeks.Gamma == 0 && greeks.Vega== 0 && greeks.Theta == 0 && greeks.Rho == 0))
                    {
                        throw new RegressionTestException($"Invalid Greeks for {contract.Symbol}");
                    }

                    // Manually evaluate the price model, just in case
                    var result = contractSecurity.EvaluatePriceModel(slice, contract);

                    if (result == null ||
                        result.TheoreticalPrice != theoreticalPrice ||
                        result.ImpliedVolatility != iv ||
                        result.Greeks.Delta != greeks.Delta ||
                        result.Greeks.Gamma != greeks.Gamma ||
                        result.Greeks.Vega != greeks.Vega ||
                        result.Greeks.Theta != greeks.Theta ||
                        result.Greeks.Rho != greeks.Rho)
                    {
                        throw new RegressionTestException($"EvaluatePriceModel returned different results for {contract.Symbol}");
                    }

                    _checked |= theoreticalPriceChecked;
                }
            }
        }

        public override void OnEndOfAlgorithm()
        {
            if (!_checked)
            {
                throw new RegressionTestException("Option chain was never received.");
            }
        }

        /// <summary>
        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
        /// </summary>
        public bool CanRunLocally { get; } = true;

        /// <summary>
        /// This is used by the regression test system to indicate which languages this algorithm is written in.
        /// </summary>
        public List<Language> Languages { get; } = new() { Language.CSharp };

        /// <summary>
        /// Data Points count of all timeslices of algorithm
        /// </summary>
        public virtual long DataPoints => 37131;

        /// <summary>
        /// Data Points count of the algorithm history
        /// </summary>
        public int AlgorithmHistoryDataPoints => 0;

        /// <summary>
        /// Final status of the algorithm
        /// </summary>
        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;

        /// <summary>
        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
        /// </summary>
        public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
        {
            {"Total Orders", "0"},
            {"Average Win", "0%"},
            {"Average Loss", "0%"},
            {"Compounding Annual Return", "0%"},
            {"Drawdown", "0%"},
            {"Expectancy", "0"},
            {"Start Equity", "100000"},
            {"End Equity", "100000"},
            {"Net Profit", "0%"},
            {"Sharpe Ratio", "0"},
            {"Sortino Ratio", "0"},
            {"Probabilistic Sharpe Ratio", "0%"},
            {"Loss Rate", "0%"},
            {"Win Rate", "0%"},
            {"Profit-Loss Ratio", "0"},
            {"Alpha", "0"},
            {"Beta", "0"},
            {"Annual Standard Deviation", "0"},
            {"Annual Variance", "0"},
            {"Information Ratio", "0"},
            {"Tracking Error", "0"},
            {"Treynor Ratio", "0"},
            {"Total Fees", "$0.00"},
            {"Estimated Strategy Capacity", "$0"},
            {"Lowest Capacity Asset", ""},
            {"Portfolio Turnover", "0%"},
            {"Drawdown Recovery", "0"},
            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
        };
    }
}