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
@@ -0,0 +1,131 @@
+/*
+ * 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.Brokerages;
+using QuantConnect.Data;
+using QuantConnect.Interfaces;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// This regression algorithm is a test case for validation of conversion rates during warm up.
+    /// </summary>
+    public class WarmupConversionRatesRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
+    {
+        /// <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()
+        {
+            SetStartDate(2018, 4, 5);
+            SetEndDate(2018, 4, 5);
+            SetBrokerageModel(BrokerageName.GDAX, AccountType.Cash);
+            SetCash(10000);
+
+            SetWarmUp(TimeSpan.FromDays(1));
+            AddCrypto("BTCEUR");
+            AddCrypto("LTCUSD");
+        }
+
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="slice">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
+        {
+            if (Portfolio.CashBook["EUR"].ConversionRate == 0
+                || Portfolio.CashBook["BTC"].ConversionRate == 0
+                || Portfolio.CashBook["LTC"].ConversionRate == 0)
+            {
+                Log($"BTCEUR current price: {Securities["BTCEUR"].Price}");
+                Log($"LTCUSD current price: {Securities["LTCUSD"].Price}");
+                Log($"EUR conversion rate: {Portfolio.CashBook["EUR"].ConversionRate}");
+                Log($"BTC conversion rate: {Portfolio.CashBook["BTC"].ConversionRate}");
+                Log($"LTC conversion rate: {Portfolio.CashBook["LTC"].ConversionRate}");
+
+                throw new RegressionTestException("Conversion rate is 0");
+            }
+
+            if (IsWarmingUp) return;
+            if (!Portfolio.Invested)
+            {
+                SetHoldings("LTCUSD", 1);
+                Debug("Purchased Stock");
+            }
+        }
+
+        /// <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 => 17277;
+
+        /// <summary>
+        /// Data Points count of the algorithm history
+        /// </summary>
+        public int AlgorithmHistoryDataPoints => 20;
+
+        /// <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", "0%"},
+            {"Drawdown", "0%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "10000.00"},
+            {"End Equity", "9884.48"},
+            {"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", "0"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "$29.84"},
+            {"Estimated Strategy Capacity", "$410000.00"},
+            {"Lowest Capacity Asset", "LTCUSD 2XR"},
+            {"Portfolio Turnover", "100.61%"},
+            {"Drawdown Recovery", "0"},
+            {"OrderListHash", "716b5757844f607d1402a5571f015aea"}
+        };
+    }
+}