chore: import upstream snapshot with attribution

2026-07-13 13:02:50 +08:00
commit 0fc60fdcb1
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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.IO;
+using QuantConnect.Data;
+using QuantConnect.Data.Custom.IconicTypes;
+using QuantConnect.Data.Market;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Provides an example algorithm showcasing the <see cref="Security.Data"/> features
+    /// </summary>
+    public class DynamicSecurityDataRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Security Equity;
+        private const string Ticker = "GOOGL";
+
+        public override void Initialize()
+        {
+            SetStartDate(2015, 10, 22);
+            SetEndDate(2015, 10, 30);
+
+            Equity = AddEquity(Ticker, Resolution.Daily);
+            var customLinkedEquity = AddData<LinkedData>(Ticker, Resolution.Daily).Symbol;
+
+            // Adding linked data manually to cache for example purposes, since
+            // LinkedData is a type used for testing and doesn't point to any real data.
+            Equity.Cache.AddDataList(new List<LinkedData>
+            {
+                new LinkedData
+                {
+                    Count = 100,
+
+                    Symbol = customLinkedEquity,
+                    EndTime = StartDate,
+                },
+                new LinkedData
+                {
+                    Count = 50,
+                    
+                    Symbol = customLinkedEquity,
+                    EndTime = StartDate
+                }
+            }, typeof(LinkedData), false);
+        }
+
+        public override void OnData(Slice slice)
+        {
+            // The Security object's Data property provides convenient access
+            // to the various types of data related to that security. You can
+            // access not only the security's price data, but also any custom
+            // data that is mapped to the security, such as our SEC reports.
+
+            // 1. Get the most recent data point of a particular type:
+            // 1.a Using the C# generic method, Get<T>:
+            LinkedData customLinkedData = Equity.Data.Get<LinkedData>();
+            Log($"{Time:o}: LinkedData: {customLinkedData}");
+
+            // 2. Get the list of data points of a particular type for the most recent time step:
+            // 2.a Using the C# generic method, GetAll<T>:
+            List<LinkedData> customLinkedDataList = Equity.Data.GetAll<LinkedData>();
+            Log($"{Time:o}: List: LinkedData: {customLinkedDataList.Count}");
+
+            if (!Portfolio.Invested)
+            {
+                Buy(Equity.Symbol, 10);
+            }
+        }
+        
+        /// <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, Language.Python };
+
+        /// <summary>
+        /// Data Points count of all timeslices of algorithm
+        /// </summary>
+        public long DataPoints => 65;
+
+        /// <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", "1"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "-4.847%"},
+            {"Drawdown", "0.300%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99882.1"},
+            {"Net Profit", "-0.118%"},
+            {"Sharpe Ratio", "-2.151"},
+            {"Sortino Ratio", "-1.743"},
+            {"Probabilistic Sharpe Ratio", "27.257%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0.008"},
+            {"Beta", "-0.104"},
+            {"Annual Standard Deviation", "0.02"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-5.063"},
+            {"Tracking Error", "0.108"},
+            {"Treynor Ratio", "0.423"},
+            {"Total Fees", "$1.00"},
+            {"Estimated Strategy Capacity", "$1600000000.00"},
+            {"Lowest Capacity Asset", "GOOG T1AZ164W5VTX"},
+            {"Portfolio Turnover", "0.83%"},
+            {"Drawdown Recovery", "0"},
+            {"OrderListHash", "ffab48ec7d6bf58aae9377c4bdf3be02"}
+        };
+    }
+}