Martin Molinero
216 lines
8.7 KiB
C#
216 lines
8.7 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 QuantConnect.Data;
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using QuantConnect.Data.UniverseSelection;
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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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/// Test algorithm using a <see cref="ConstituentsUniverse"/> with test data
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/// </summary>
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public class ConstituentsUniverseRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private readonly Symbol _appl = QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA);
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private readonly Symbol _spy = QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA);
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private readonly Symbol _qqq = QuantConnect.Symbol.Create("QQQ", SecurityType.Equity, Market.USA);
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private readonly Symbol _fb = QuantConnect.Symbol.Create("FB", SecurityType.Equity, Market.USA);
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private int _step;
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/// <summary>
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/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
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/// </summary>
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public override void Initialize()
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{
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SetStartDate(2013, 10, 07); //Set Start Date
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SetEndDate(2013, 10, 11); //Set End Date
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SetCash(100000); //Set Strategy Cash
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UniverseSettings.Resolution = Resolution.Daily;
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var customUniverseSymbol = new Symbol(SecurityIdentifier.GenerateConstituentIdentifier(
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"constituents-universe-qctest",
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SecurityType.Equity,
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Market.USA),
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"constituents-universe-qctest");
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AddUniverse(new ConstituentsUniverse(customUniverseSymbol, UniverseSettings));
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}
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/// <summary>
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/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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/// </summary>
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/// <param name="data">Slice object keyed by symbol containing the stock data</param>
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public override void OnData(Slice data)
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{
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_step++;
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if (_step == 1)
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{
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if (!data.ContainsKey(_qqq)
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|| !data.ContainsKey(_appl))
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{
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throw new Exception($"Unexpected symbols found, step: {_step}");
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}
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if (data.Count != 2)
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{
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throw new Exception($"Unexpected data count, step: {_step}");
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}
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// AAPL will be deselected by the ConstituentsUniverse
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// but it shouldn't be removed since we hold it
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SetHoldings(_appl, 0.5);
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}
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else if (_step == 2)
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{
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if (!data.ContainsKey(_appl))
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{
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throw new Exception($"Unexpected symbols found, step: {_step}");
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}
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if (data.Count != 1)
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{
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throw new Exception($"Unexpected data count, step: {_step}");
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}
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// AAPL should now be released
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// note: takes one extra loop because the order is executed on market open
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Liquidate();
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}
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else if (_step == 3)
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{
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if (!data.ContainsKey(_fb)
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|| !data.ContainsKey(_spy)
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|| !data.ContainsKey(_appl))
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{
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throw new Exception($"Unexpected symbols found, step: {_step}");
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}
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if (data.Count != 3)
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{
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throw new Exception($"Unexpected data count, step: {_step}");
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}
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}
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else if (_step == 4)
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{
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if (!data.ContainsKey(_fb)
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|| !data.ContainsKey(_spy))
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{
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throw new Exception($"Unexpected symbols found, step: {_step}");
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}
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if (data.Count != 2)
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{
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throw new Exception($"Unexpected data count, step: {_step}");
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}
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}
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else if (_step == 5)
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{
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if (!data.ContainsKey(_fb)
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|| !data.ContainsKey(_spy))
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{
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throw new Exception($"Unexpected symbols found, step: {_step}");
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}
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if (data.Count != 2)
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{
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throw new Exception($"Unexpected data count, step: {_step}");
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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 (_step != 5)
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{
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throw new Exception($"Unexpected step count: {_step}");
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}
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}
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public override void OnSecuritiesChanged(SecurityChanges changes)
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{
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foreach (var added in changes.AddedSecurities)
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{
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Log($"AddedSecurities {added}");
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}
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foreach (var removed in changes.RemovedSecurities)
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{
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Log($"RemovedSecurities {removed} {_step}");
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// we are currently notifying the removal of AAPl twice,
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// when deselected and when finally removed (since it stayed pending)
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if (removed.Symbol == _appl && _step != 1 && _step != 2
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|| removed.Symbol == _qqq && _step != 1)
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{
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throw new Exception($"Unexpected removal step count: {_step}");
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}
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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, 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", "-0.52%"},
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{"Compounding Annual Return", "-31.636%"},
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{"Drawdown", "0.900%"},
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{"Expectancy", "-1"},
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{"Net Profit", "-0.520%"},
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{"Sharpe Ratio", "-3.097"},
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{"Probabilistic Sharpe Ratio", "24.675%"},
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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", "-0.443"},
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{"Beta", "0.157"},
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{"Annual Standard Deviation", "0.074"},
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{"Annual Variance", "0.005"},
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{"Information Ratio", "-9.046"},
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{"Tracking Error", "0.176"},
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{"Treynor Ratio", "-1.46"},
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{"Total Fees", "$7.82"},
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{"Fitness Score", "0.1"},
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{"Kelly Criterion Estimate", "0"},
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{"Kelly Criterion Probability Value", "0"},
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{"Sortino Ratio", "79228162514264337593543950335"},
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{"Return Over Maximum Drawdown", "-35.683"},
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{"Portfolio Turnover", "0.2"},
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{"Total Insights Generated", "0"},
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{"Total Insights Closed", "0"},
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{"Total Insights Analysis Completed", "0"},
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{"Long Insight Count", "0"},
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{"Short Insight Count", "0"},
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{"Long/Short Ratio", "100%"},
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{"Estimated Monthly Alpha Value", "$0"},
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{"Total Accumulated Estimated Alpha Value", "$0"},
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{"Mean Population Estimated Insight Value", "$0"},
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{"Mean Population Direction", "0%"},
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{"Mean Population Magnitude", "0%"},
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{"Rolling Averaged Population Direction", "0%"},
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{"Rolling Averaged Population Magnitude", "0%"},
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{"OrderListHash", "-611289773"}
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};
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}
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}
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