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.Data;
+using System.Collections.Generic;
+using QuantConnect.Interfaces;
+using QuantConnect.Orders;
+
+namespace QuantConnect.Algorithm.CSharp
+{
+    /// <summary>
+    /// Basic template India algorithm simply initializes the date range and cash. This is a skeleton
+    /// framework you can use for designing an algorithm.
+    /// </summary>
+    /// <meta name="tag" content="using data" />
+    /// <meta name="tag" content="using quantconnect" />
+    /// <meta name="tag" content="trading and orders" />
+    public class BasicTemplateIndiaAlgorithm : 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()
+        {
+            SetAccountCurrency("INR");  //Set Account Currency
+            SetStartDate(2019, 1, 23);  //Set Start Date
+            SetEndDate(2019, 10, 31);   //Set End Date
+            SetCash(100000);            //Set Strategy Cash
+
+            // Find more symbols here: http://quantconnect.com/data
+            // Equities Resolutions: Tick, Second, Minute, Hour, Daily.
+            AddEquity("YESBANK", Resolution.Minute, Market.India);
+
+            //Set Order Properties as per the requirements for order placement
+            DefaultOrderProperties = new IndiaOrderProperties(exchange: Exchange.NSE);
+            //override default productType value set in config.json if needed - order specific productType value
+            //DefaultOrderProperties = new IndiaOrderProperties(exchange: Exchange.NSE, IndiaOrderProperties.IndiaProductType.CNC);
+
+            // General Debug statement for acknowledgement
+            Debug("Initialization Done");
+        }
+
+        /// <summary>
+        /// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
+        /// </summary>
+        /// <param name="data">Slice object keyed by symbol containing the stock data</param>
+        public override void OnData(Slice slice)
+        {
+            if (!Portfolio.Invested)
+            {
+                var marketTicket = MarketOrder("YESBANK", 1);
+            }
+        }
+
+        public override void OnOrderEvent(OrderEvent orderEvent)
+        {
+            if (orderEvent.Status.IsFill())
+            {
+                Debug($"Purchased Complete: {orderEvent.Symbol}");
+            }
+        }
+
+        /// <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 => 29524;
+
+        /// <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", "-0.010%"},
+            {"Drawdown", "0.000%"},
+            {"Expectancy", "0"},
+            {"Start Equity", "100000"},
+            {"End Equity", "99992.45"},
+            {"Net Profit", "-0.008%"},
+            {"Sharpe Ratio", "-497.389"},
+            {"Sortino Ratio", "-73.22"},
+            {"Probabilistic Sharpe Ratio", "0.794%"},
+            {"Loss Rate", "0%"},
+            {"Win Rate", "0%"},
+            {"Profit-Loss Ratio", "0"},
+            {"Alpha", "0"},
+            {"Beta", "0"},
+            {"Annual Standard Deviation", "0"},
+            {"Annual Variance", "0"},
+            {"Information Ratio", "-1.183"},
+            {"Tracking Error", "0"},
+            {"Treynor Ratio", "0"},
+            {"Total Fees", "₹6.00"},
+            {"Estimated Strategy Capacity", "₹61000000000.00"},
+            {"Lowest Capacity Asset", "YESBANK UL"},
+            {"Portfolio Turnover", "0.00%"},
+            {"Drawdown Recovery", "0"},
+            {"OrderListHash", "06f782c83dd633dac6f228b91273ba26"}
+        };
+    }
+}