8402b6f01e
It's important that we keep the factor files consistent with respect to the date that they were generated. This enables us to run the regression algorithms in the cloud and get the same results by using the factor files from the correct date.
145 lines
5.6 KiB
C#
145 lines
5.6 KiB
C#
/*
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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*
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*/
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using QuantConnect.Data;
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using QuantConnect.Data.Market;
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using QuantConnect.Orders;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// This is an option split regression algorithm
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/// </summary>
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/// <meta name="tag" content="regression test" />
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/// <meta name="tag" content="options" />
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public class OptionSplitRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Symbol _optionSymbol;
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public override void Initialize()
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{
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// this test opens position in the first day of trading, lives through stock split (7 for 1), and closes adjusted position on the second day
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SetStartDate(2014, 06, 05);
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SetEndDate(2014, 06, 09);
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SetCash(1000000);
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var option = AddOption("AAPL");
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_optionSymbol = option.Symbol;
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// set our strike/expiry filter for this option chain
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option.SetFilter(u => u.IncludeWeeklys()
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.Strikes(-2, +2)
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.Expiration(TimeSpan.Zero, TimeSpan.FromDays(365 * 2)));
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// use the underlying equity as the benchmark
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SetBenchmark("AAPL");
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}
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/// <summary>
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/// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event
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/// </summary>
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/// <param name="slice">The current slice of data keyed by symbol string</param>
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public override void OnData(Slice slice)
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{
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if (!Portfolio.Invested)
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{
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if (Time.Hour > 9 && Time.Minute > 0)
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{
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OptionChain chain;
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if (slice.OptionChains.TryGetValue(_optionSymbol, out chain))
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{
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var contract =
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chain.OrderBy(x => x.Expiry)
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.Where(x => x.Right == OptionRight.Call && x.Strike == 650)
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.Skip(1)
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.FirstOrDefault();
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if (contract != null)
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{
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Buy(contract.Symbol, 1);
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}
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}
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}
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}
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else
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{
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if (Time.Day > 6 && Time.Hour > 14 && Time.Minute > 0)
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{
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Liquidate();
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}
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}
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if (Portfolio.Invested)
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{
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var holdings = Portfolio.Securities.Where(x => x.Value.Holdings.AbsoluteQuantity != 0).First().Value.Holdings.AbsoluteQuantity;
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if (Time.Day == 6 && holdings != 1)
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{
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throw new Exception(string.Format("Expected position quantity of 1 but was {0}", holdings));
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}
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if (Time.Day == 9 && holdings != 7)
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{
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throw new Exception(string.Format("Expected position quantity of 7 but was {0}", holdings));
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}
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}
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}
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/// <summary>
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/// Order fill event handler. On an order fill update the resulting information is passed to this method.
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/// </summary>
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/// <param name="orderEvent">Order event details containing details of the evemts</param>
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/// <remarks>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</remarks>
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public override void OnOrderEvent(OrderEvent orderEvent)
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{
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Log(orderEvent.ToString());
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}
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/// <summary>
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/// This is used by the regression test system to indicate which languages this algorithm is written in.
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/// </summary>
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public Language[] Languages { get; } = { Language.CSharp, Language.Python };
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/// <summary>
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/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
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/// </summary>
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public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Trades", "2"},
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{"Average Win", "0%"},
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{"Average Loss", "-0.02%"},
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{"Compounding Annual Return", "-1.242%"},
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{"Drawdown", "0.000%"},
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{"Expectancy", "-1"},
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{"Net Profit", "-0.017%"},
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{"Sharpe Ratio", "-7.099"},
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{"Loss Rate", "100%"},
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{"Win Rate", "0%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "-0.01"},
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{"Beta", "0"},
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{"Annual Standard Deviation", "0.001"},
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{"Annual Variance", "0"},
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{"Information Ratio", "7.126"},
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{"Tracking Error", "6.064"},
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{"Treynor Ratio", "174.306"},
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{"Total Fees", "$0.50"}
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};
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}
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}
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