/*
* 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.Linq;
using QuantConnect.Data;
using QuantConnect.Interfaces;
using QuantConnect.Securities;
using System.Collections.Generic;
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 Security _es19m20;
private Option _esOption;
private Symbol _expectedOptionContract;
public override void Initialize()
{
SetStartDate(2020, 1, 5);
SetEndDate(2020, 6, 30);
_es19m20 = AddFutureContract(
QuantConnect.Symbol.CreateFuture(
Futures.Indices.SP500EMini,
Market.CME,
new DateTime(2020, 6, 19)),
Resolution.Minute);
// We must set the volatility model on the underlying, since the defaults are
// too strict to calculate greeks with when we only have data for a single day
_es19m20.VolatilityModel = new StandardDeviationOfReturnsVolatilityModel(
60,
Resolution.Minute,
TimeSpan.FromMinutes(1));
// Select a future option expiring ITM, and adds it to the algorithm.
_esOption = AddFutureOptionContract(OptionChain(_es19m20.Symbol)
.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.Symbol, Market.CME, OptionStyle.American, OptionRight.Call, 3200m, new DateTime(2020, 6, 19));
if (_esOption.Symbol != _expectedOptionContract)
{
throw new RegressionTestException($"Contract {_expectedOptionContract} was not found in the chain");
}
}
public override void OnData(Slice slice)
{
// Let the algo warmup, but without using SetWarmup. Otherwise, we get
// no contracts in the option chain
if (_invested || _onDataCalls++ < 40)
{
return;
}
if (slice.OptionChains.Count == 0)
{
return;
}
if (slice.OptionChains.Values.All(o => o.Contracts.Values.Any(c => !slice.ContainsKey(c.Symbol))))
{
return;
}
if (slice.OptionChains.Values.First().Contracts.Count == 0)
{
throw new RegressionTestException($"No contracts found in the option {slice.OptionChains.Keys.First()}");
}
var deltas = slice.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Delta).ToList();
var gammas = slice.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Gamma).ToList();
var lambda = slice.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Lambda).ToList();
var rho = slice.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Rho).ToList();
var theta = slice.OptionChains.Values.OrderByDescending(y => y.Contracts.Values.Sum(x => x.Volume)).First().Contracts.Values.Select(x => x.Greeks.Theta).ToList();
var vega = slice.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)
{
// the margin requirement for the FOPs is less than the one of the underlying so we can't allocate all our buying power
// into FOPs else we won't be able to exercise
SetHoldings(slice.OptionChains.Values.First().Contracts.Values.First().Symbol, 0.25);
_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 RegressionTestException($"Expected no holdings at end of algorithm, but are invested in: {string.Join(", ", Portfolio.Keys)}");
}
if (!_invested)
{
throw new RegressionTestException($"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 List Languages { get; } = new() { Language.CSharp };
///
/// Data Points count of all timeslices of algorithm
///
public long DataPoints => 212196;
///
/// Data Points count of the algorithm history
///
public int AlgorithmHistoryDataPoints => 1;
///
/// Final status of the algorithm
///
public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
///
/// 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 Orders", "3"},
{"Average Win", "16.44%"},
{"Average Loss", "-35.38%"},
{"Compounding Annual Return", "-44.262%"},
{"Drawdown", "26.200%"},
{"Expectancy", "-0.268"},
{"Start Equity", "100000"},
{"End Equity", "75242.9"},
{"Net Profit", "-24.757%"},
{"Sharpe Ratio", "-0.965"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "0.060%"},
{"Loss Rate", "50%"},
{"Win Rate", "50%"},
{"Profit-Loss Ratio", "0.46"},
{"Alpha", "-0.303"},
{"Beta", "0.016"},
{"Annual Standard Deviation", "0.313"},
{"Annual Variance", "0.098"},
{"Information Ratio", "-0.649"},
{"Tracking Error", "0.483"},
{"Treynor Ratio", "-18.59"},
{"Total Fees", "$7.10"},
{"Estimated Strategy Capacity", "$24000000.00"},
{"Lowest Capacity Asset", "ES XFH59UPBIJ7O|ES XFH59UK0MYO1"},
{"Portfolio Turnover", "12.22%"},
{"Drawdown Recovery", "0"},
{"OrderListHash", "355dbab2e93d7a62b073b6e6cd4557c2"}
};
}
}