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BasicTemplateOptionEquityStrategyAlgorithm.cs
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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");
* 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.Linq;
using QuantConnect.Data;
using QuantConnect.Orders;
using QuantConnect.Interfaces;
using QuantConnect.Data.Market;
using System.Collections.Generic;
using QuantConnect.Securities.Option;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Basic template algorithm trading a Call Butterfly option equity strategy
/// </summary>
/// <meta name="tag" content="options" />
/// <meta name="tag" content="using data" />
/// <meta name="tag" content="using quantconnect" />
/// <meta name="tag" content="trading and orders" />
public class BasicTemplateOptionEquityStrategyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private Symbol _optionSymbol;
public override void Initialize()
{
SetStartDate(2015, 12, 24);
SetEndDate(2015, 12, 24);
var equity = AddEquity("GOOG", leverage: 4);
var option = AddOption(equity.Symbol);
_optionSymbol = option.Symbol;
// set our strike/expiry filter for this option chain
option.SetFilter(u => u.StandardsOnly().Strikes(-2, +2)
// Expiration method accepts TimeSpan objects or integer for days.
// The following statements yield the same filtering criteria
.Expiration(0, 180));
}
/// <summary>
/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
/// </summary>
/// <param name="slice">Slice object keyed by symbol containing the stock data</param>
public override void OnData(Slice slice)
{
if (!Portfolio.Invested)
{
OptionChain chain;
if (IsMarketOpen(_optionSymbol) && slice.OptionChains.TryGetValue(_optionSymbol, out chain))
{
var callContracts = chain.Where(contract => contract.Right == OptionRight.Call)
.GroupBy(x => x.Expiry)
.OrderBy(grouping => grouping.Key)
.First()
.OrderBy(x => x.Strike)
.ToList();
var expiry = callContracts[0].Expiry;
var lowerStrike = callContracts[0].Strike;
var middleStrike = callContracts[1].Strike;
var higherStrike = callContracts[2].Strike;
var optionStrategy = OptionStrategies.CallButterfly(_optionSymbol, higherStrike, middleStrike, lowerStrike, expiry);
Order(optionStrategy, 10);
}
}
}
/// <summary>
/// Order fill event handler. On an order fill update the resulting information is passed to this method.
/// </summary>
/// <param name="orderEvent">Order event details containing details of the events</param>
/// <remarks>This method can be called asynchronously and so should only be used by seasoned C# experts. Ensure you use proper locks on thread-unsafe objects</remarks>
public override void OnOrderEvent(OrderEvent orderEvent)
{
Log($"{orderEvent}");
}
/// <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 => 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, Language.Python };
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 15023;
/// <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", "3"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "0%"},
{"Drawdown", "0%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "98024"},
{"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", "$26.00"},
{"Estimated Strategy Capacity", "$69000.00"},
{"Lowest Capacity Asset", "GOOCV W78ZERHAT67A|GOOCV VP83T1ZUHROL"},
{"Portfolio Turnover", "61.31%"},
{"Drawdown Recovery", "0"},
{"OrderListHash", "ccd6cb1b6244d0c6d30b2760938958f1"}
};
}
}