/*
* 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;
namespace QuantConnect.Algorithm.CSharp
{
///
/// This regression algorithm tests Out of The Money (OTM) future option expiry for calls.
/// We expect 1 order from the algorithm, which are:
///
/// * Initial entry, buy ES Call Option (expiring OTM)
/// - contract expires worthless, not exercised, so never opened a position in the underlying
///
/// Additionally, we test delistings for future options and assert that our
/// portfolio holdings reflect the orders the algorithm has submitted.
///
///
/// Total Trades in regression algorithm should be 1, but expiration is counted as a trade.
/// See related issue: https://github.com/QuantConnect/Lean/issues/4854
///
public class FutureOptionCallOTMExpiryRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private Symbol _es19m20;
private Symbol _esOption;
private Symbol _expectedContract;
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 call expiring OTM, and adds it to the algorithm.
_esOption = AddFutureOptionContract(OptionChainProvider.GetOptionContractList(_es19m20, Time)
.Where(x => x.ID.StrikePrice >= 3300m && x.ID.OptionRight == OptionRight.Call)
.OrderBy(x => x.ID.StrikePrice)
.Take(1)
.Single(), Resolution.Minute).Symbol;
_expectedContract = QuantConnect.Symbol.CreateOption(_es19m20, Market.CME, OptionStyle.American, OptionRight.Call, 3300m, new DateTime(2020, 6, 19));
if (_esOption != _expectedContract)
{
throw new Exception($"Contract {_expectedContract} was not found in the chain");
}
Schedule.On(DateRules.Tomorrow, TimeRules.AfterMarketOpen(_es19m20, 1), () =>
{
MarketOrder(_esOption, 1);
});
}
public override void OnData(Slice data)
{
// Assert delistings, so that we can make sure that we receive the delisting warnings at
// the expected time. These assertions detect bug #4872
foreach (var delisting in data.Delistings.Values)
{
if (delisting.Type == DelistingType.Warning)
{
if (delisting.Time != new DateTime(2020, 6, 19))
{
throw new Exception($"Delisting warning issued at unexpected date: {delisting.Time}");
}
}
if (delisting.Type == DelistingType.Delisted)
{
if (delisting.Time != new DateTime(2020, 6, 20))
{
throw new Exception($"Delisting happened at unexpected date: {delisting.Time}");
}
}
}
}
public override void OnOrderEvent(OrderEvent orderEvent)
{
if (orderEvent.Status != OrderStatus.Filled)
{
// There's lots of noise with OnOrderEvent, but we're only interested in fills.
return;
}
if (!Securities.ContainsKey(orderEvent.Symbol))
{
throw new Exception($"Order event Symbol not found in Securities collection: {orderEvent.Symbol}");
}
var security = Securities[orderEvent.Symbol];
if (security.Symbol == _es19m20)
{
throw new Exception("Invalid state: did not expect a position for the underlying to be opened, since this contract expires OTM");
}
if (security.Symbol == _expectedContract)
{
AssertFutureOptionContractOrder(orderEvent, security);
}
else
{
throw new Exception($"Received order event for unknown Symbol: {orderEvent.Symbol}");
}
Log($"{orderEvent}");
}
private void AssertFutureOptionContractOrder(OrderEvent orderEvent, Security option)
{
if (orderEvent.Direction == OrderDirection.Buy && option.Holdings.Quantity != 1)
{
throw new Exception($"No holdings were created for option contract {option.Symbol}");
}
if (orderEvent.Direction == OrderDirection.Sell && option.Holdings.Quantity != 0)
{
throw new Exception("Holdings were found after a filled option exercise");
}
if (orderEvent.Direction == OrderDirection.Sell && !orderEvent.Message.Contains("OTM"))
{
throw new Exception("Contract did not expire OTM");
}
if (orderEvent.Message.Contains("Exercise"))
{
throw new Exception("Exercised option, even though it expires OTM");
}
}
///
/// Ran at the end of the algorithm to ensure the algorithm has no holdings
///
/// The algorithm has holdings
public override void OnEndOfAlgorithm()
{
if (Portfolio.Invested)
{
throw new Exception($"Expected no holdings at end of algorithm, but are invested in: {string.Join(", ", Portfolio.Keys)}");
}
}
///
/// 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, Language.Python };
///
/// 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", "2"},
{"Average Win", "0%"},
{"Average Loss", "-4.03%"},
{"Compounding Annual Return", "-8.088%"},
{"Drawdown", "4.000%"},
{"Expectancy", "-1"},
{"Net Profit", "-4.029%"},
{"Sharpe Ratio", "-1.274"},
{"Probabilistic Sharpe Ratio", "0.015%"},
{"Loss Rate", "100%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "-0.066"},
{"Beta", "-0.002"},
{"Annual Standard Deviation", "0.052"},
{"Annual Variance", "0.003"},
{"Information Ratio", "0.9"},
{"Tracking Error", "0.179"},
{"Treynor Ratio", "28.537"},
{"Total Fees", "$3.70"},
{"Fitness Score", "0"},
{"Kelly Criterion Estimate", "0"},
{"Kelly Criterion Probability Value", "0"},
{"Sortino Ratio", "-0.183"},
{"Return Over Maximum Drawdown", "-2.007"},
{"Portfolio Turnover", "0"},
{"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", "-1116221764"}
};
}
}