/*
* 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 System.Reflection;
using QuantConnect.Data;
using QuantConnect.Interfaces;
using QuantConnect.Orders;
using QuantConnect.Securities;
using QuantConnect.Securities.Option;
namespace QuantConnect.Algorithm.CSharp
{
///
/// This regression algorithm tests In The Money (ITM) future option expiry for calls.
/// We test to make sure that FOPs have greeks enabled, same as equity options.
///
public class FutureOptionCallITMGreeksExpiryRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private bool _invested;
private int _onDataCalls;
private Symbol _es19m20;
private Option _esOption;
private Symbol _expectedOptionContract;
public override void Initialize()
{
SetStartDate(2020, 1, 5);
SetEndDate(2020, 6, 30);
// We add AAPL as a temporary workaround for https://github.com/QuantConnect/Lean/issues/4872
// which causes delisting events to never be processed, thus leading to options that might never
// be exercised until the next data point arrives.
AddEquity("AAPL", Resolution.Daily);
_es19m20 = AddFutureContract(
QuantConnect.Symbol.CreateFuture(
Futures.Indices.SP500EMini,
Market.CME,
new DateTime(2020, 6, 19)),
Resolution.Minute).Symbol;
// Select a future option expiring ITM, and adds it to the algorithm.
_esOption = AddFutureOptionContract(OptionChainProvider.GetOptionContractList(_es19m20, new DateTime(2020, 1, 5))
.Where(x => x.ID.StrikePrice <= 3200m && x.ID.OptionRight == OptionRight.Call)
.OrderByDescending(x => x.ID.StrikePrice)
.Take(1)
.Single(), Resolution.Minute);
_esOption.PriceModel = OptionPriceModels.BjerksundStensland();
_expectedOptionContract = QuantConnect.Symbol.CreateOption(_es19m20, Market.CME, OptionStyle.American, OptionRight.Call, 3200m, new DateTime(2020, 6, 19));
if (_esOption.Symbol != _expectedOptionContract)
{
throw new Exception($"Contract {_expectedOptionContract} was not found in the chain");
}
}
public override void OnData(Slice data)
{
// Let the algo warmup, but without using SetWarmup. Otherwise, we get
// no contracts in the option chain
if (_invested || _onDataCalls++ < 40)
{
return;
}
if (data.OptionChains.Count == 0)
{
return;
}
if (data.OptionChains.Values.All(o => o.Contracts.Values.Any(c => !data.ContainsKey(c.Symbol))))
{
return;
}
if (data.OptionChains.Values.First().Contracts.Count == 0)
{
throw new Exception($"No contracts found in the option {data.OptionChains.Keys.First()}");
}
var deltas = data.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Delta).ToList();
var gammas = data.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Gamma).ToList();
var lambda = data.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Lambda).ToList();
var rho = data.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Rho).ToList();
var theta = data.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Theta).ToList();
var vega = data.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Vega).ToList();
// The commented out test cases all return zero.
// This is because of failure to evaluate the greeks in the option pricing model.
// For now, let's skip those.
if (deltas.Any(d => d == 0))
{
throw new AggregateException("Option contract Delta was equal to zero");
}
if (gammas.Any(g => g == 0))
{
throw new AggregateException("Option contract Gamma was equal to zero");
}
//if (lambda.Any(l => l == 0))
//{
// throw new AggregateException("Option contract Lambda was equal to zero");
//}
if (rho.Any(r => r == 0))
{
throw new AggregateException("Option contract Rho was equal to zero");
}
//if (theta.Any(t => t == 0))
//{
// throw new AggregateException("Option contract Theta was equal to zero");
//}
//if (vega.Any(v => v == 0))
//{
// throw new AggregateException("Option contract Vega was equal to zero");
//}
if (!_invested)
{
SetHoldings(data.OptionChains.Values.First().Contracts.Values.First().Symbol, 1);
_invested = true;
}
}
///
/// Ran at the end of the algorithm to ensure the algorithm has no holdings
///
/// The algorithm has holdings
public override void OnEndOfAlgorithm()
{
if (Portfolio.Invested)
{
throw new Exception($"Expected no holdings at end of algorithm, but are invested in: {string.Join(", ", Portfolio.Keys)}");
}
if (!_invested)
{
throw new Exception($"Never checked greeks, maybe we have no option data?");
}
}
///
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
///
public bool CanRunLocally { get; } = true;
///
/// This is used by the regression test system to indicate which languages this algorithm is written in.
///
public Language[] Languages { get; } = { Language.CSharp };
///
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
///
public Dictionary ExpectedStatistics => new Dictionary
{
{"Total Trades", "3"},
{"Average Win", "28.04%"},
{"Average Loss", "-62.81%"},
{"Compounding Annual Return", "-78.165%"},
{"Drawdown", "52.400%"},
{"Expectancy", "-0.277"},
{"Net Profit", "-52.379%"},
{"Sharpe Ratio", "-0.865"},
{"Probabilistic Sharpe Ratio", "0.019%"},
{"Loss Rate", "50%"},
{"Win Rate", "50%"},
{"Profit-Loss Ratio", "0.45"},
{"Alpha", "-0.596"},
{"Beta", "-0.031"},
{"Annual Standard Deviation", "0.681"},
{"Annual Variance", "0.463"},
{"Information Ratio", "-0.514"},
{"Tracking Error", "0.703"},
{"Treynor Ratio", "18.748"},
{"Total Fees", "$66.60"},
{"Fitness Score", "0.157"},
{"Kelly Criterion Estimate", "0"},
{"Kelly Criterion Probability Value", "0"},
{"Sortino Ratio", "-0.133"},
{"Return Over Maximum Drawdown", "-1.492"},
{"Portfolio Turnover", "0.411"},
{"Total Insights Generated", "0"},
{"Total Insights Closed", "0"},
{"Total Insights Analysis Completed", "0"},
{"Long Insight Count", "0"},
{"Short Insight Count", "0"},
{"Long/Short Ratio", "100%"},
{"Estimated Monthly Alpha Value", "$0"},
{"Total Accumulated Estimated Alpha Value", "$0"},
{"Mean Population Estimated Insight Value", "$0"},
{"Mean Population Direction", "0%"},
{"Mean Population Magnitude", "0%"},
{"Rolling Averaged Population Direction", "0%"},
{"Rolling Averaged Population Magnitude", "0%"},
{"OrderListHash", "151392833"}
};
}
}