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@quant1729 @mchandschuh @Martin-Molinero @jaredbroad @StefanoRaggi
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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;
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Data;
using QuantConnect.Data.Market;
using QuantConnect.Orders;
using QuantConnect.Interfaces;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// This example demonstrates how to add options for a given underlying equity security.
/// It also shows how you can prefilter contracts easily based on strikes and expirations, and how you
/// can inspect the option chain to pick a specific option contract to trade.
/// </summary>
/// <meta name="tag" content="using data" />
/// <meta name="tag" content="options" />
/// <meta name="tag" content="filter selection" />
public class BasicTemplateOptionsAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private const string UnderlyingTicker = "GOOG";
public readonly Symbol Underlying = QuantConnect.Symbol.Create(UnderlyingTicker, SecurityType.Equity, Market.USA);
public readonly Symbol OptionSymbol = QuantConnect.Symbol.Create(UnderlyingTicker, SecurityType.Option, Market.USA);
public override void Initialize()
{
SetStartDate(2015, 12, 24);
SetEndDate(2015, 12, 24);
SetCash(100000);
var equity = AddEquity(UnderlyingTicker);
var option = AddOption(UnderlyingTicker);
// set our strike/expiry filter for this option chain
option.SetFilter(u => u.Strikes(-2, +2)
.Expiration(TimeSpan.Zero, TimeSpan.FromDays(180)));
// use the underlying equity as the benchmark
SetBenchmark(equity.Symbol);
}
/// <summary>
/// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event
/// </summary>
/// <param name="slice">The current slice of data keyed by symbol string</param>
public override void OnData(Slice slice)
{
if (!Portfolio.Invested && IsMarketOpen(OptionSymbol))
{
OptionChain chain;
if (slice.OptionChains.TryGetValue(OptionSymbol, out chain))
{
// we find at the money (ATM) put contract with farthest expiration
var atmContract = chain
.OrderByDescending(x => x.Expiry)
.ThenBy(x => Math.Abs(chain.Underlying.Price - x.Strike))
.ThenByDescending(x => x.Right)
.FirstOrDefault();
if (atmContract != null)
{
// if found, trade it
MarketOrder(atmContract.Symbol, 1);
MarketOnCloseOrder(atmContract.Symbol, -1);
}
}
}
}
/// <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 evemts</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.ToString());
}
/// <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 Language[] Languages { get; } = { Language.CSharp, Language.Python };
/// <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 Trades", "2"},
{"Average Win", "0%"},
{"Average Loss", "-0.28%"},
{"Compounding Annual Return", "-78.282%"},
{"Drawdown", "0.300%"},
{"Expectancy", "-1"},
{"Net Profit", "-0.282%"},
{"Sharpe Ratio", "0"},
{"Loss Rate", "100%"},
{"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", "$2.00"}
};
}
}
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