/*
* 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 example demonstrates how to add options for a given underlying equity security.
/// It also shows how you can prefilter contracts easily based on strikes and expirations, and how you
/// can inspect the option chain to pick a specific option contract to trade.
///
///
///
///
public class BasicTemplateOptionsHourlyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private const string UnderlyingTicker = "AAPL";
private Symbol _optionSymbol;
public override void Initialize()
{
SetStartDate(2014, 6, 6);
SetEndDate(2014, 6, 9);
SetCash(100000);
var equity = AddEquity(UnderlyingTicker, Resolution.Hour);
var option = AddOption(UnderlyingTicker, Resolution.Hour);
_optionSymbol = option.Symbol;
// set our strike/expiry filter for this option chain
option.SetFilter(u => u.Strikes(-2, +2)
// Expiration method accepts TimeSpan objects or integer for days.
// The following statements yield the same filtering criteria
.Expiration(0, 180));
// .Expiration(TimeSpan.Zero, TimeSpan.FromDays(180)));
// 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 && IsMarketOpen(_optionSymbol))
{
OptionChain chain;
if (slice.OptionChains.TryGetValue(_optionSymbol, out chain))
{
// we find at the money (ATM) put contract with farthest expiration
var atmContract = chain
.OrderByDescending(x => x.Expiry)
.ThenBy(x => Math.Abs(chain.Underlying.Price - x.Strike))
.ThenByDescending(x => x.Right)
.FirstOrDefault();
if (atmContract != null && IsMarketOpen(atmContract.Symbol))
{
// if found, trade it
MarketOrder(atmContract.Symbol, 1);
MarketOnCloseOrder(atmContract.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 => 9504;
///
/// 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", "5"},
{"Average Win", "0%"},
{"Average Loss", "-0.07%"},
{"Compounding Annual Return", "-11.517%"},
{"Drawdown", "0.200%"},
{"Expectancy", "-1"},
{"Start Equity", "100000"},
{"End Equity", "99866"},
{"Net Profit", "-0.134%"},
{"Sharpe Ratio", "-9.78"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "0%"},
{"Loss Rate", "100%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0.075"},
{"Beta", "-0.054"},
{"Annual Standard Deviation", "0.008"},
{"Annual Variance", "0"},
{"Information Ratio", "-18.699"},
{"Tracking Error", "0.155"},
{"Treynor Ratio", "1.434"},
{"Total Fees", "$4.00"},
{"Estimated Strategy Capacity", "$1000.00"},
{"Lowest Capacity Asset", "AAPL 2ZTXYMUAHCIAU|AAPL R735QTJ8XC9X"},
{"Portfolio Turnover", "2.28%"},
{"Drawdown Recovery", "0"},
{"OrderListHash", "7804b3dcf20d3096a2265a289fa81cd3"}
};
}
}