quantconnect--lean/Algorithm.CSharp/CoveredAndProtectiveCallStrategiesAlgorithm.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;
using System.Collections.Generic;
using System.Linq;

using QuantConnect.Data.Market;
using QuantConnect.Securities.Option;
using QuantConnect.Securities.Positions;

namespace QuantConnect.Algorithm.CSharp
{
    /// <summary>
    /// This algorithm demonstrate how to use OptionStrategies helper class to batch send orders for common strategies.
    /// In this case, the algorithm tests the Covered and Protective Call strategies.
    /// </summary>
    public class CoveredAndProtectiveCallStrategiesAlgorithm : OptionStrategyFactoryMethodsBaseAlgorithm
    {
        private OptionStrategy _coveredCall;
        private OptionStrategy _protectiveCall;

        protected override int ExpectedOrdersCount { get; } = 4;

        protected override void TradeStrategy(OptionChain chain)
        {
            var contract = chain
                .OrderBy(x => Math.Abs(chain.Underlying.Price - x.Strike))
                .ThenByDescending(x => x.Expiry)
                .FirstOrDefault();

            if (contract != null)
            {
                _coveredCall = OptionStrategies.CoveredCall(_optionSymbol, contract.Strike, contract.Expiry);
                _protectiveCall = OptionStrategies.ProtectiveCall(_optionSymbol, contract.Strike, contract.Expiry);
                Buy(_coveredCall, 2);
            }
        }

        protected override void AssertStrategyPositionGroup(IPositionGroup positionGroup)
        {
            if (positionGroup.Positions.Count() != 2)
            {
                throw new Exception($"Expected position group to have 2 positions. Actual: {positionGroup.Positions.Count()}");
            }

            var optionPosition = positionGroup.Positions.Single(x => x.Symbol.SecurityType == SecurityType.Option);
            if (optionPosition.Symbol.ID.OptionRight != OptionRight.Call)
            {
                throw new Exception($"Expected option position to be a call. Actual: {optionPosition.Symbol.ID.OptionRight}");
            }

            var underlyingPosition = positionGroup.Positions.Single(x => x.Symbol.SecurityType == SecurityType.Equity);
            var expectedOptionPositionQuantity = -2;
            var expectedUnderlyingPositionQuantity = 2 * Securities[_optionSymbol].SymbolProperties.ContractMultiplier;

            if (optionPosition.Quantity != expectedOptionPositionQuantity)
            {
                throw new Exception($@"Expected option position quantity to be {expectedOptionPositionQuantity}. Actual: {optionPosition.Quantity}");
            }

            if (underlyingPosition.Quantity != expectedUnderlyingPositionQuantity)
            {
                throw new Exception($@"Expected underlying position quantity to be {expectedUnderlyingPositionQuantity}. Actual: {underlyingPosition.Quantity}");
            }
        }

        protected override void LiquidateStrategy()
        {
            // We should be able to close the position using the inverse strategy (a protective call)
            Buy(_protectiveCall, 2);
        }

        /// <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 override bool CanRunLocally { get; } = true;

        /// <summary>
        /// This is used by the regression test system to indicate which languages this algorithm is written in.
        /// </summary>
        public override Language[] Languages { get; } = { Language.CSharp, Language.Python };

        /// <summary>
        /// Data Points count of all timeslices of algorithm
        /// </summary>
        public override long DataPoints => 4490;

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

        /// <summary>
        /// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
        /// </summary>
        public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
        {
            {"Total Trades", "4"},
            {"Average Win", "0%"},
            {"Average Loss", "0%"},
            {"Compounding Annual Return", "0%"},
            {"Drawdown", "0%"},
            {"Expectancy", "0"},
            {"Net Profit", "0%"},
            {"Sharpe 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", "$8.00"},
            {"Estimated Strategy Capacity", "$120000.00"},
            {"Lowest Capacity Asset", "GOOCV WBGM92QHIYO6|GOOCV VP83T1ZUHROL"},
            {"Portfolio Turnover", "32.18%"},
            {"OrderListHash", "44aee2765df08ed1dad3b1723445ac5e"}
        };
    }
}