Michael Handschuh
9ee61f425c
A mechanical refactoring was performed to make algorithms currently used in regression algorithms to implement IRegressionAlgorithmDefinition, which allows algorithms to define their own expected statistics and what languages should be run as part of regression. The type name of the C# type is used to determine the file/model name for python. This was for simplicity, but if needed, could later be refactored to expose more information, but for now the convention of keeping names the same makes sense and just works easily.
117 lines
4.9 KiB
C#
117 lines
4.9 KiB
C#
/*
|
|
* 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.
|
|
/*
|
|
* 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.Collections.Generic;
|
|
using System.Linq;
|
|
using QuantConnect.Data;
|
|
using QuantConnect.Securities.Option;
|
|
|
|
namespace QuantConnect.Algorithm.CSharp
|
|
{
|
|
/// <summary>
|
|
/// Demonstration of the Option Chain Provider -- a much faster mechanism for manually specifying the option contracts you'd like to recieve
|
|
/// data for and manually subscribing to them.
|
|
/// </summary>
|
|
/// <meta name="tag" content="strategy example" />
|
|
/// <meta name="tag" content="options" />
|
|
/// <meta name="tag" content="using data" />
|
|
/// <meta name="tag" content="selecting options" />
|
|
/// <meta name="tag" content="manual selection" />
|
|
public class OptionChainProviderAlgorithm : QCAlgorithm
|
|
{
|
|
private Symbol _equitySymbol;
|
|
private Symbol _optionContract = string.Empty;
|
|
|
|
public override void Initialize()
|
|
{
|
|
SetStartDate(2015, 12, 24);
|
|
SetEndDate(2015, 12, 24);
|
|
SetCash(100000);
|
|
var equity = AddEquity("GOOG", Resolution.Minute);
|
|
_equitySymbol = equity.Symbol;
|
|
}
|
|
|
|
public override void OnData(Slice data)
|
|
{
|
|
if (!Portfolio[_equitySymbol].Invested)
|
|
{
|
|
MarketOrder(_equitySymbol, 100);
|
|
}
|
|
|
|
if (!(Securities.ContainsKey(_optionContract) && Portfolio[_optionContract].Invested))
|
|
{
|
|
var contracts = OptionChainProvider.GetOptionContractList(_equitySymbol, data.Time);
|
|
var underlyingPrice = Securities[_equitySymbol].Price;
|
|
// filter the out-of-money call options from the contract list which expire in 10 to 30 days from now on
|
|
var otmCalls = (from symbol in contracts
|
|
where symbol.ID.OptionRight == OptionRight.Call
|
|
where symbol.ID.StrikePrice - underlyingPrice > 0
|
|
where ((symbol.ID.Date - data.Time).TotalDays < 30 && (symbol.ID.Date - data.Time).TotalDays > 10)
|
|
select symbol);
|
|
|
|
if (otmCalls.Count() != 0)
|
|
{
|
|
_optionContract = otmCalls.OrderBy(x => x.ID.Date)
|
|
.ThenBy(x => (x.ID.StrikePrice - underlyingPrice))
|
|
.FirstOrDefault();
|
|
// use AddOptionContract() to subscribe the data for specified contract
|
|
AddOptionContract(_optionContract, Resolution.Minute);
|
|
}
|
|
else _optionContract = string.Empty;
|
|
}
|
|
if (Securities.ContainsKey(_optionContract) && !Portfolio[_optionContract].Invested)
|
|
{
|
|
MarketOrder(_optionContract, -1);
|
|
}
|
|
}
|
|
|
|
/// <summary>
|
|
/// This is used by the regression test system to indicate which languages this algorithm is written in.
|
|
/// </summary>
|
|
public Language[] Languages { get; } = { Language.CSharp, Language.Python };
|
|
|
|
/// <summary>
|
|
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
|
|
/// </summary>
|
|
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
|
|
{
|
|
{"Total Trades", "2"},
|
|
{"Average Win", "0%"},
|
|
{"Average Loss", "0%"},
|
|
{"Compounding Annual Return", "3.198%"},
|
|
{"Drawdown", "0.200%"},
|
|
{"Expectancy", "0"},
|
|
{"Net Profit", "0.006%"},
|
|
{"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", "$1.25"},
|
|
};
|
|
}
|
|
} |