chore: import upstream snapshot with attribution

2026-07-13 13:02:50 +08:00
commit 0fc60fdcb1
5008 changed files with 910633 additions and 0 deletions
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+/*
+ * 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;
+using System.Collections.Generic;
+using System.Linq;
+using QuantConnect.Algorithm.Framework.Alphas;
+using QuantConnect.Algorithm.Framework.Portfolio;
+using QuantConnect.Algorithm.Framework.Risk;
+using QuantConnect.Algorithm.Framework.Selection;
+using QuantConnect.Data;
+using QuantConnect.Interfaces;
+using QuantConnect.Orders;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Regression test showcasing an algorithm using the framework models
+    /// and directly calling <see cref="QCAlgorithm.EmitInsights"/>
+    /// </summary>
+    public class EmitInsightsAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private readonly Symbol _symbol = QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA);
+        private bool _toggle;
+
+        /// <summary>
+        /// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
+        /// </summary>
+        public override void Initialize()
+        {
+            // Set requested data resolution
+            UniverseSettings.Resolution = Resolution.Daily;
+
+            SetStartDate(2013, 10, 07);  //Set Start Date
+            SetEndDate(2013, 10, 11);    //Set End Date
+            SetCash(100000);             //Set Strategy Cash
+
+            // set algorithm framework models
+            SetUniverseSelection(new ManualUniverseSelectionModel(_symbol));
+            SetAlpha(new ConstantAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromDays(1), 0.025, null));
+            SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel());
+            SetRiskManagement(new MaximumDrawdownPercentPerSecurity(0.01m));
+        }
+
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
+        {
+            if (_toggle)
+            {
+                _toggle = false;
+                var order = Transactions.GetOpenOrders(_symbol).FirstOrDefault();
+
+                if (order != null)
+                {
+                    throw new RegressionTestException($"Unexpected open order {order}");
+                }
+
+                // we manually emit an insight
+                EmitInsights(Insight.Price(_symbol, Resolution.Daily, 1, InsightDirection.Down));
+
+                // emitted insight should have triggered a new order
+                order = Transactions.GetOpenOrders(_symbol).FirstOrDefault();
+
+                if (order == null)
+                {
+                    throw new RegressionTestException("Expected open order for emitted insight");
+                }
+                if (order.Direction != OrderDirection.Sell
+                    || order.Symbol != _symbol)
+                {
+                    throw new RegressionTestException($"Unexpected open order for emitted insight: {order}");
+                }
+            }
+            else
+            {
+                _toggle = true;
+            }
+        }
+
+        /// <summary>
+        /// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
+        /// </summary>
+        public bool CanRunLocally { get; } = true;
+
+        /// <summary>
+        /// This is used by the regression test system to indicate which languages this algorithm is written in.
+        /// </summary>
+        public List<Language> Languages { get; } = new() { Language.CSharp };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 48;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 0;
+
+        /// <summary>
+        /// Final status of the algorithm
+        /// </summary>
+        public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
+
+        /// <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 Orders", "6"},
+            {"Average Win", "0.94%"},
+            {"Average Loss", "-0.98%"},
+            {"Compounding Annual Return", "-49.613%"},
+            {"Drawdown", "1.200%"},
+            {"Expectancy", "-0.021"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99127.48"},
+            {"Net Profit", "-0.873%"},
+            {"Sharpe Ratio", "-2.432"},
+            {"Sortino Ratio", "-26.344"},
+            {"Probabilistic Sharpe Ratio", "33.228%"},
+            {"Loss Rate", "50%"},
+            {"Win Rate", "50%"},
+            {"Profit-Loss Ratio", "0.96"},
+            {"Alpha", "-1.649"},
+            {"Beta", "0.62"},
+            {"Annual Standard Deviation", "0.175"},
+            {"Annual Variance", "0.031"},
+            {"Information Ratio", "-17.555"},
+            {"Tracking Error", "0.137"},
+            {"Treynor Ratio", "-0.686"},
+            {"Total Fees", "$17.19"},
+            {"Estimated Strategy Capacity", "$1600000000.00"},
+            {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
+            {"Portfolio Turnover", "100.44%"},
+            {"Drawdown Recovery", "2"},
+            {"OrderListHash", "54c868bc2bc19b62922c1fec8c1d327e"}
+        };
+    }
+}