/*
* 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 QuantConnect.Data;
using QuantConnect.Interfaces;
using QuantConnect.Securities;
using System.Collections.Generic;
using System.Linq;
namespace QuantConnect.Algorithm.CSharp
{
///
/// Regression algorithm reproducing issue #5160 where delisting order would be cancelled because it was placed at the market close on the delisting day
///
public class DelistingFutureOptionRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
protected virtual Resolution Resolution => Resolution.Minute;
private bool _traded;
private int _lastMonth;
public override void Initialize()
{
SetStartDate(2012, 1, 1);
SetEndDate(2013, 1, 1);
SetCash(10000000);
var dc = AddFuture(Futures.Dairy.ClassIIIMilk, Resolution, Market.CME);
dc.SetFilter(1, 120);
AddFutureOption(dc.Symbol, universe => universe.Strikes(-2, 2));
_lastMonth = -1;
// This is required to prevent the algorithm from automatically delisting the underlying. Without this, future options will be subscribed
// with resolution default to Minute insted of this.Resolution. This could be replaced after GH issue #6491 is implemented.
UniverseSettings.Resolution = Resolution;
}
public override void OnData(Slice slice)
{
if (Time.Month != _lastMonth)
{
_lastMonth = Time.Month;
var investedSymbols = Securities.Values
.Where(security => security.Invested)
.Select(security => security.Symbol)
.ToList();
var delistedSecurity = investedSymbols.Where(symbol => symbol.ID.Date.AddDays(1) < Time).ToList();
if (delistedSecurity.Count > 0)
{
throw new RegressionTestException($"[{UtcTime}] We hold a delisted securities: {string.Join(",", delistedSecurity)}");
}
Log($"Holdings({Time}): {string.Join(",", investedSymbols)}");
}
if (Portfolio.Invested)
{
return;
}
foreach (var chain in slice.OptionChains.Values)
{
foreach (var contractsValue in chain.Contracts.Values)
{
MarketOrder(contractsValue.Symbol, 1);
_traded = true;
}
}
}
public override void OnEndOfAlgorithm()
{
if (!_traded)
{
throw new RegressionTestException("We expected some FOP trading to happen");
}
if (Portfolio.Invested)
{
throw new RegressionTestException("We shouldn't be invested anymore");
}
}
///
/// 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 virtual long DataPoints => 761073;
///
/// Data Points count of the algorithm history
///
public int AlgorithmHistoryDataPoints => 0;
///
/// 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 virtual Dictionary ExpectedStatistics => new Dictionary
{
{"Total Orders", "16"},
{"Average Win", "0.01%"},
{"Average Loss", "-0.02%"},
{"Compounding Annual Return", "-0.111%"},
{"Drawdown", "0.100%"},
{"Expectancy", "-0.678"},
{"Start Equity", "10000000"},
{"End Equity", "9988880.24"},
{"Net Profit", "-0.111%"},
{"Sharpe Ratio", "-10.416"},
{"Sortino Ratio", "-0.959"},
{"Probabilistic Sharpe Ratio", "0.000%"},
{"Loss Rate", "80%"},
{"Win Rate", "20%"},
{"Profit-Loss Ratio", "0.61"},
{"Alpha", "-0.008"},
{"Beta", "-0.001"},
{"Annual Standard Deviation", "0.001"},
{"Annual Variance", "0"},
{"Information Ratio", "-1.076"},
{"Tracking Error", "0.107"},
{"Treynor Ratio", "14.634"},
{"Total Fees", "$19.76"},
{"Estimated Strategy Capacity", "$1400000000.00"},
{"Lowest Capacity Asset", "DC V5E8PHPRCHJ8|DC V5E8P9SH0U0X"},
{"Portfolio Turnover", "0.00%"},
{"Drawdown Recovery", "0"},
{"OrderListHash", "6448bae646ab35724a0cd23936d94a48"}
};
}
}