/*
* 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.Data.Market;
using QuantConnect.Orders;
using QuantConnect.Interfaces;
namespace QuantConnect.Algorithm.CSharp
{
///
/// This regression algorithm checks if all the option chain data coming to the algo is consistent with current securities manager state
///
///
///
///
///
public class OptionChainConsistencyRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private const string UnderlyingTicker = "GOOG";
private readonly Symbol _optionSymbol = QuantConnect.Symbol.Create(UnderlyingTicker, SecurityType.Option, Market.USA);
public override void Initialize()
{
SetStartDate(2015, 12, 24);
SetEndDate(2015, 12, 24);
SetCash(10000);
var equity = AddEquity(UnderlyingTicker);
var option = AddOption(UnderlyingTicker);
// set our strike/expiry filter for this option chain
option.SetFilter(u => u.IncludeWeeklys()
.Strikes(-2, +2)
.Expiration(TimeSpan.Zero, TimeSpan.FromDays(10)));
// use the underlying equity as the benchmark
SetBenchmark(equity.Symbol);
}
///
/// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event
///
/// The current slice of data keyed by symbol string
public override void OnData(Slice slice)
{
if (!Portfolio.Invested)
{
OptionChain chain;
if (slice.OptionChains.TryGetValue(_optionSymbol, out chain))
{
// check if data is consistent
foreach (var o in chain)
{
if (!Securities.ContainsKey(o.Symbol))
{
// inconsistency found: option chains contains contract information that is not available in securities manager and not available for trading
throw new RegressionTestException("inconsistency found: option chains contains contract " +
$"{o.Symbol.Value} that is not available in securities manager and not available for trading"
);
}
}
// trade
var contract = (
from optionContract in chain.OrderByDescending(x => x.Strike)
where optionContract.Right == OptionRight.Call
where optionContract.Expiry == Time.Date
where optionContract.Strike < chain.Underlying.Price
select optionContract
).Skip(2).FirstOrDefault();
if (contract != null)
{
MarketOrder(contract.Symbol, 1);
MarketOnCloseOrder(contract.Symbol, -1);
}
}
}
}
///
/// Order fill event handler. On an order fill update the resulting information is passed to this method.
///
/// Order event details containing details of the events
/// This method can be called asynchronously and so should only be used by seasoned C# experts. Ensure you use proper locks on thread-unsafe objects
public override void OnOrderEvent(OrderEvent orderEvent)
{
Log(orderEvent.ToString());
}
///
/// 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, Language.Python };
///
/// Data Points count of all timeslices of algorithm
///
public long DataPoints => 14325;
///
/// 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 Dictionary ExpectedStatistics => new Dictionary
{
{"Total Orders", "2"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "0%"},
{"Drawdown", "0%"},
{"Expectancy", "0"},
{"Start Equity", "10000"},
{"End Equity", "9613"},
{"Net Profit", "0%"},
{"Sharpe Ratio", "0"},
{"Sortino 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", "$2.00"},
{"Estimated Strategy Capacity", "$5000.00"},
{"Lowest Capacity Asset", "GOOCV W6NBKPFL0ACM|GOOCV VP83T1ZUHROL"},
{"Portfolio Turnover", "9.93%"},
{"Drawdown Recovery", "0"},
{"OrderListHash", "8887ac32d29175b21e40f335437cee61"}
};
}
}