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 QuantConnect.Algorithm.Framework.Alphas;
+using QuantConnect.Algorithm.Framework.Execution;
+using QuantConnect.Algorithm.Framework.Portfolio;
+using QuantConnect.Algorithm.Framework.Selection;
+using QuantConnect.Brokerages;
+using QuantConnect.Data;
+using QuantConnect.Interfaces;
+using QuantConnect.Orders;
+using System;
+using System.Collections.Generic;
+using System.Linq;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Basic template framework algorithm uses framework components to define the algorithm.
+    /// Shows EqualWeightingPortfolioConstructionModel.LongOnly() application
+    /// </summary>
+    /// <meta name="tag" content="alpha streams" />
+    /// <meta name="tag" content="using quantconnect" />
+    /// <meta name="tag" content="algorithm framework" />
+    public class LongOnlyAlphaStreamAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        public override void Initialize()
+        {
+            // 1. Required: 
+            SetStartDate(2013, 10, 07);
+            SetEndDate(2013, 10, 11);
+
+            // 2. Required: Alpha Streams Models:
+            SetBrokerageModel(BrokerageName.AlphaStreams);
+
+            // 3. Required: Significant AUM Capacity
+            SetCash(1000000);
+
+            // Only SPY will be traded
+            SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel(Resolution.Daily, PortfolioBias.Long));
+            SetExecution(new ImmediateExecutionModel());
+
+            // Order margin value has to have a minimum of 0.5% of Portfolio value, allows filtering out small trades and reduce fees.
+            // Commented so regression algorithm is more sensitive
+            //Settings.MinimumOrderMarginPortfolioPercentage = 0.005m;
+
+            // set algorithm framework models
+            SetUniverseSelection(
+                new ManualUniverseSelectionModel(
+                    new[] {"SPY", "IBM"}
+                        .Select(x => QuantConnect.Symbol.Create(x, SecurityType.Equity, Market.USA))
+                )
+            );
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (Portfolio.Invested) return;
+
+            EmitInsights(
+                Insight.Price("SPY", TimeSpan.FromDays(1), InsightDirection.Up),
+                Insight.Price("IBM", TimeSpan.FromDays(1), InsightDirection.Down)
+            );
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            if (orderEvent.Status.IsFill())
+            {
+                if (Securities[orderEvent.Symbol].Holdings.IsShort)
+                {
+                    throw new RegressionTestException("Invalid position, should not be short");
+                }
+                Debug($"Purchased Stock: {orderEvent}");
+            }
+        }
+
+        /// <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 => 7843;
+
+        /// <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", "9"},
+            {"Average Win", "0.99%"},
+            {"Average Loss", "-0.60%"},
+            {"Compounding Annual Return", "216.678%"},
+            {"Drawdown", "2.300%"},
+            {"Expectancy", "0.318"},
+            {"Start Equity", "1000000"},
+            {"End Equity", "1014847.05"},
+            {"Net Profit", "1.485%"},
+            {"Sharpe Ratio", "7.265"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "64.807%"},
+            {"Loss Rate", "50%"},
+            {"Win Rate", "50%"},
+            {"Profit-Loss Ratio", "1.64"},
+            {"Alpha", "-0.36"},
+            {"Beta", "1.003"},
+            {"Annual Standard Deviation", "0.223"},
+            {"Annual Variance", "0.05"},
+            {"Information Ratio", "-100.088"},
+            {"Tracking Error", "0.004"},
+            {"Treynor Ratio", "1.617"},
+            {"Total Fees", "$309.75"},
+            {"Estimated Strategy Capacity", "$15000000.00"},
+            {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
+            {"Portfolio Turnover", "179.37%"},
+            {"Drawdown Recovery", "3"},
+            {"OrderListHash", "15b25d354d282abb9adfcc80bd4d67bc"}
+        };
+    }
+}