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 QuantConnect.Interfaces;
+using QuantConnect.Securities;
+using System.Collections.Generic;
+using QuantConnect.Data;
+using QuantConnect.Orders;
+using System;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Demonstration of using custom margin interest rate model in backtesting.
+    /// </summary>
+    /// <meta name="tag" content="custom margin interest rate models" />
+    public class CustomMarginInterestRateModelAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _spy;
+
+        private decimal _cashAfterOrder;
+
+        public override void Initialize()
+        {
+            SetStartDate(2013, 10, 01);
+            SetEndDate(2013, 10, 31);
+
+            var security = AddEquity("SPY", Resolution.Hour);
+            _spy = security.Symbol;
+
+            // set the margin interest rate model
+            security.SetMarginInterestRateModel(new CustomMarginInterestRateModel());
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (!Portfolio.Invested)
+            {
+                SetHoldings(_spy, 1);
+            }
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            if (orderEvent.Status == OrderStatus.Filled)
+            {
+                _cashAfterOrder = Portfolio.Cash;
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            var security = Securities[_spy];
+            var marginInterestRateModel = security.MarginInterestRateModel as CustomMarginInterestRateModel;
+
+            if (marginInterestRateModel == null)
+            {
+                throw new RegressionTestException("CustomMarginInterestRateModel was not set");
+            }
+
+            if (marginInterestRateModel.CallCount == 0)
+            {
+                throw new RegressionTestException("CustomMarginInterestRateModel was not called");
+            }
+
+            var expectedCash = _cashAfterOrder * (decimal)Math.Pow(1 + (double)marginInterestRateModel.InterestRate, marginInterestRateModel.CallCount);
+
+            // add a tolerance since using Math.Pow(double, double) given the lack of a decimal overload
+            if (Math.Abs(Portfolio.Cash - expectedCash) > 1e-10m)
+            {
+                throw new RegressionTestException($"Expected cash {expectedCash} but got {Portfolio.Cash}");
+            }
+        }
+
+        public class CustomMarginInterestRateModel : IMarginInterestRateModel
+        {
+            public decimal InterestRate { get; } = 0.01m;
+
+            public int CallCount { get; private set; }
+
+            public void ApplyMarginInterestRate(MarginInterestRateParameters marginInterestRateParameters)
+            {
+                var security = marginInterestRateParameters.Security;
+                var positionValue = security.Holdings.GetQuantityValue(security.Holdings.Quantity);
+
+                if (positionValue.Amount > 0)
+                {
+                    positionValue.Cash.AddAmount(InterestRate * positionValue.Cash.Amount);
+                    CallCount++;
+                }
+            }
+        }
+
+        /// <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 => 330;
+
+        /// <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", "93.409%"},
+            {"Drawdown", "2.400%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "105698.63"},
+            {"Net Profit", "5.699%"},
+            {"Sharpe Ratio", "4.701"},
+            {"Sortino Ratio", "9.153"},
+            {"Probabilistic Sharpe Ratio", "85.015%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0.145"},
+            {"Beta", "0.998"},
+            {"Annual Standard Deviation", "0.108"},
+            {"Annual Variance", "0.012"},
+            {"Information Ratio", "28.436"},
+            {"Tracking Error", "0.005"},
+            {"Treynor Ratio", "0.506"},
+            {"Total Fees", "$3.43"},
+            {"Estimated Strategy Capacity", "$150000000.00"},
+            {"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
+            {"Portfolio Turnover", "3.19%"},
+            {"Drawdown Recovery", "8"},
+            {"OrderListHash", "c0205e9d3d1bfdee958fecccb36413ec"}
+        };
+    }
+}