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 QuantConnect.Data;
+using QuantConnect.Interfaces;
+using QuantConnect.Securities;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Algorithm asserting that the volatility models don't have big jumps due to price discontinuities on splits and dividends when using raw data
+    /// </summary>
+    public class VolatilityModelsWithRawDataAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        private Symbol _aapl;
+
+        private int _splitsCount;
+        private int _dividendsCount;
+
+        public override void Initialize()
+        {
+            SetStartDate(2014, 1, 1);
+            SetEndDate(2014, 12, 31);
+            SetCash(100000);
+
+            var equity = AddEquity("AAPL", Resolution.Daily, dataNormalizationMode: DataNormalizationMode.Raw);
+            equity.SetVolatilityModel(new StandardDeviationOfReturnsVolatilityModel(7));
+
+            _aapl = equity.Symbol;
+        }
+
+        public override void OnData(Slice slice)
+        {
+            if (slice.Splits.ContainsKey(_aapl))
+            {
+                _splitsCount++;
+            }
+
+            if (slice.Dividends.ContainsKey(_aapl))
+            {
+                _dividendsCount++;
+            }
+        }
+
+        public override void OnEndOfDay(Symbol symbol)
+        {
+            if (symbol != _aapl)
+            {
+                return;
+            }
+
+            // This is expected only in this case, 0.6 is not a magical number of any kind.
+            // Just making sure we don't get big jumps on volatility
+            if (Securities[_aapl].VolatilityModel.Volatility > 0.6m)
+            {
+                throw new RegressionTestException(
+                    "Expected volatility to stay less than 0.6 (not big jumps due to price discontinuities on splits and dividends), " +
+                    $"but got {Securities[_aapl].VolatilityModel.Volatility}");
+            }
+        }
+
+        public override void OnEndOfAlgorithm()
+        {
+            if (_splitsCount == 0 || _dividendsCount == 0)
+            {
+                throw new RegressionTestException($"Expected to receive at least one split and one dividend, but got {_splitsCount} splits and {_dividendsCount} dividends");
+            }
+        }
+
+        /// <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 => 2021;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 40;
+
+        /// <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", "0"},
+            {"Average Win", "0%"},
+            {"Average Loss", "0%"},
+            {"Compounding Annual Return", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "100000"},
+            {"Net Profit", "0%"},
+            {"Sharpe Ratio", "0"},
+            {"Sortino Ratio", "0"},
+            {"Probabilistic Sharpe Ratio", "0%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-1.025"},
+            {"Tracking Error", "0.094"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$0.00"},
+            {"Estimated Strategy Capacity", "$0"},
+            {"Lowest Capacity Asset", ""},
+            {"Portfolio Turnover", "0%"},
+            {"Drawdown Recovery", "0"},
+            {"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
+        };
+    }
+}