Alexandre Catarino
96f42eb591
Build & Test Lean / build (push) Has been cancelled
* Updates Fundamental Data * Updates Regression Algorithms - `CoarseFundamentalTop3Algorithm` - New coarse has higher `DollarVolume` for `FB` - `CoarseNoLookAheadBiasAlgorithm` - Change from `SPY` update not included in #5493 - `SectorExposureRiskFrameworkAlgorithm` - `HasFundamentalData` was false for `GOOG` on 20140401 and 20140402. * Updates Unit Tests Minor changes in expected values * Updates Regression Tests Should have been included in #5493: - `OptionsExpiredContractRegression` - `FuturesExpiredContractRegression` * Adjusted Quantity By Lot Size in OrderTargetsByMarginImpact `OrderTargetsByMarginImpact` didn't calculate the order value with the quantity adjusted by order size which less to values that did not reflect the actual order value. It has a particular affect in `SectorExposureRiskFrameworkAlgorithm` where the Python and C# versions have the same orders but placed in a different sequence because of decimal/double precision. * Reduce dictionary access x3 on OrderTargetsByMarginImpact Co-authored-by: Martin-Molinero <martin@quantconnect.com>
111 lines
4.0 KiB
C#
111 lines
4.0 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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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.Interfaces;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Regression algorithm to test if expired options contracts chains are making their
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/// way into the timeslices being delivered to OnData()
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/// </summary>
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public class OptionsExpiredContractRegression : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private bool _receivedData;
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/// <summary>
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/// Initializes the algorithm state.
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/// </summary>
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public override void Initialize()
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{
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SetStartDate(2015, 12, 23);
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SetEndDate(2016, 1, 20);
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SetCash(1000000);
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// Subscribe to GOOG Options
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var option = AddOption("GOOG");
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option.SetFilter(x => x.CallsOnly().Strikes(0, 1).Expiration(0, 30));
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}
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public override void OnData(Slice data)
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{
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foreach (var chain in data.OptionChains)
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{
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_receivedData = true;
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foreach (var contract in chain.Value.OrderBy(x => x.Expiry))
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{
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if (contract.Expiry.Date < Time.Date)
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{
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throw new Exception($"Received expired contract {contract} expired: {contract.Expiry} current time: {Time}");
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}
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}
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}
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}
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public override void OnEndOfAlgorithm()
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{
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if (!_receivedData)
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{
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throw new Exception("No Options chains were received in this regression");
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}
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}
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/// <summary>
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/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
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/// </summary>
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public bool CanRunLocally { get; } = true;
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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 };
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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", "0"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "0%"},
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{"Drawdown", "0%"},
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{"Expectancy", "0"},
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{"Net Profit", "0%"},
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{"Sharpe Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "0%"},
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{"Loss Rate", "0%"},
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{"Win Rate", "0%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "0"},
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{"Beta", "0"},
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{"Annual Standard Deviation", "0"},
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{"Annual Variance", "0"},
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{"Information Ratio", "4.138"},
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{"Tracking Error", "0.184"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$0.00"},
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{"Estimated Strategy Capacity", "$0"},
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{"Fitness Score", "0"},
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{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
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};
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}
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}
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