chore: import upstream snapshot with attribution
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wehub-resource-sync
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/*
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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.Algorithm.Framework.Alphas;
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using QuantConnect.Algorithm.Framework.Portfolio;
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using QuantConnect.Algorithm.Framework.Selection;
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using QuantConnect.Data;
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using QuantConnect.Interfaces;
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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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/// Regression test showcasing an algorithm without setting an <see cref="AlphaModel"/>,
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/// directly calling <see cref="QCAlgorithm.EmitInsights"/> and <see cref="QCAlgorithm.SetHoldings"/>.
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/// Note that calling <see cref="QCAlgorithm.SetHoldings"/> is useless because
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/// next time Lean calls the Portfolio construction model it will counter it with another order
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/// since it only knows of the emitted insights
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/// </summary>
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public class EmitInsightNoAlphaModelAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private readonly Symbol _symbol = QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA);
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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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// Set requested data resolution
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UniverseSettings.Resolution = Resolution.Daily;
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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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// set algorithm framework models except ALPHA
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SetUniverseSelection(new ManualUniverseSelectionModel(_symbol));
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SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel());
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// Order margin value has to have a minimum of 0.5% of Portfolio value, allows filtering out small trades and reduce fees.
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// Commented so regression algorithm is more sensitive
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//Settings.MinimumOrderMarginPortfolioPercentage = 0.005m;
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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 slice)
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{
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if (!Portfolio.Invested)
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{
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var order = Transactions.GetOpenOrders(_symbol).FirstOrDefault();
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if (order != null)
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{
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throw new RegressionTestException($"Unexpected open order {order}");
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}
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EmitInsights(Insight.Price(_symbol, Resolution.Daily, 10, InsightDirection.Down));
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// emitted insight should have triggered a new order
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order = Transactions.GetOpenOrders(_symbol).FirstOrDefault();
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if (order == null)
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{
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throw new RegressionTestException("Expected open order for emitted insight");
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}
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if (order.Direction != OrderDirection.Sell
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|| order.Symbol != _symbol)
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{
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throw new RegressionTestException($"Unexpected open order for emitted insight: {order}");
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}
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SetHoldings(_symbol, 1);
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}
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}
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public override void OnEndOfAlgorithm()
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{
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var holdings = Securities[_symbol].Holdings;
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if (Math.Sign(holdings.Quantity) != -1)
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{
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throw new RegressionTestException("Unexpected holdings");
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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 List<Language> Languages { get; } = new() { Language.CSharp };
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/// <summary>
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/// Data Points count of all timeslices of algorithm
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/// </summary>
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public long DataPoints => 48;
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/// <summary>
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/// Data Points count of the algorithm history
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/// </summary>
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public int AlgorithmHistoryDataPoints => 0;
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/// <summary>
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/// Final status of the algorithm
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/// </summary>
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public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
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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 Orders", "6"},
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{"Average Win", "0%"},
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{"Average Loss", "-0.02%"},
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{"Compounding Annual Return", "-74.669%"},
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{"Drawdown", "2.900%"},
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{"Expectancy", "-1"},
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{"Start Equity", "100000"},
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{"End Equity", "98259.71"},
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{"Net Profit", "-1.740%"},
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{"Sharpe Ratio", "-3.018"},
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{"Sortino Ratio", "-3.766"},
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{"Probabilistic Sharpe Ratio", "24.480%"},
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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", "1.301"},
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{"Beta", "-0.998"},
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{"Annual Standard Deviation", "0.222"},
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{"Annual Variance", "0.049"},
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{"Information Ratio", "-5.95"},
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{"Tracking Error", "0.445"},
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{"Treynor Ratio", "0.672"},
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{"Total Fees", "$19.23"},
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{"Estimated Strategy Capacity", "$1200000000.00"},
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{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
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{"Portfolio Turnover", "100.02%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "094cbf077486ed2ec2558a2255a385c2"}
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};
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}
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}
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