Files
quantconnect--lean/Algorithm.CSharp/RollOutFrontMonthToBackMonthOptionUsingCalendarSpreadRegressionAlgorithm.cs
T
Martin-Molinero ff47ede36c Minor fix for automatically added option underlying (#7311)
- Lean engine will automatically add an options underlying if not
  present, but in most cases the option chain will select the underlying
  too, so let's make sure the configurations match. Previous to this
  change 'fill forward' setting could be different causing the
  underlying to be duplicated in the data stack
2023-06-09 19:03:35 -03:00

179 lines
6.9 KiB
C#

/*
* 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.Util;
using QuantConnect.Interfaces;
using QuantConnect.Securities.Option;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Regression algorithm asserting that we can liquidate an existing option position with an option strategy.
///
/// This specific case rolls out a front month put to a back month put using a calendar spread, working in two steps:
/// 1. Short front month put
/// 2. Roll out front month put to back month put using a calendar spread.
/// </summary>
public class RollOutFrontMonthToBackMonthOptionUsingCalendarSpreadRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private Symbol _symbol;
private Symbol _frontMonthPutSymbol;
private Symbol _backMonthPutSymbol;
private decimal _atmStrike;
private bool _done;
public override void Initialize()
{
SetStartDate(2015, 12, 24);
SetEndDate(2015, 12, 24);
SetCash(500000);
var option = AddOption("GOOG", Resolution.Minute);
option.SetFilter(universe => universe.Strikes(-1, 1).Expiration(0, 62));
_symbol = option.Symbol;
}
public override void OnData(Slice data)
{
if (_done || !data.OptionChains.TryGetValue(_symbol, out var chain) || !chain.Any())
{
return;
}
var isFirstStep = !Portfolio.Invested;
if (isFirstStep)
{
_atmStrike = chain.MinBy(x => Math.Abs(x.Strike - chain.Underlying.Price)).Strike;
}
var puts = chain.Where(x => x.Strike == _atmStrike && x.Right == OptionRight.Put).ToList();
if (isFirstStep)
{
if (puts.Count == 0)
{
return;
}
// Step 1: short front month put
_frontMonthPutSymbol = puts.MinBy(x => x.Expiry).Symbol;
Sell(_frontMonthPutSymbol, 1);
}
else if (puts.Count > 1)
{
// Step 2: roll out front month put to back month put using a calendar spread.
// Near expiry contract would be the same we shorted in step 1 (closets expiry, same strike),
// which we want to roll out to the farther expiry
var frontMonthExpiry = puts[0].Expiry;
var backMonthExpiry = puts[puts.Count - 1].Expiry;
var optionStrategy = OptionStrategies.PutCalendarSpread(_symbol, _atmStrike, frontMonthExpiry, backMonthExpiry);
var tickets = Sell(optionStrategy, 1);
if (!tickets.Any(ticket => ticket.Symbol == _frontMonthPutSymbol && ticket.Quantity == 1))
{
throw new Exception($"Expected to find a ticket for {_frontMonthPutSymbol} with quantity {-Securities[_frontMonthPutSymbol].Holdings.Quantity}");
}
_backMonthPutSymbol = tickets.First(ticket => ticket.Symbol != _frontMonthPutSymbol).Symbol;
_done = true;
}
}
public override void OnEndOfAlgorithm()
{
if (!_done)
{
throw new Exception("Expected the algorithm to have bought and sold a Bull Call Spread and a Bear Put Spread.");
}
if (Portfolio.Positions.Groups.Count != 1)
{
throw new Exception($"Expected 1 position group, found {Portfolio.Positions.Groups.Count}");
}
var positions = Portfolio.Positions.Groups.Single().Positions.ToList();
if (positions.Count != 1)
{
throw new Exception($"Expected 1 position in the position group, found {positions.Count()}");
}
// The position should correspond to the far expiry contract
var position = positions[0];
if (position.Symbol != _backMonthPutSymbol)
{
throw new Exception($"Expected final portfolio position to be {_backMonthPutSymbol}, found {position.Symbol}");
}
}
/// <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 };
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 467379;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public 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 Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Trades", "3"},
{"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", "$3.00"},
{"Estimated Strategy Capacity", "$190000.00"},
{"Lowest Capacity Asset", "GOOCV 306CZK4DP0LC6|GOOCV VP83T1ZUHROL"},
{"Portfolio Turnover", "1.19%"},
{"OrderListHash", "3a57cd934e8d045b555aea5a446c9628"}
};
}
}