chore: import upstream snapshot with attribution
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wehub-resource-sync
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/*
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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*
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*/
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using System;
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using System.Linq;
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using QuantConnect.Data;
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using System.Globalization;
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using QuantConnect.Interfaces;
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using System.Collections.Generic;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// The regression algorithm showcases the utilization of a custom data source with the Sort flag set to true.
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/// This means that the source initially provides data in descending order, which is then organized into ascending order and returned in the <see cref="OnData(Slice)"/> function.
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/// </summary>
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public class DescendingCustomDataObjectStoreRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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protected virtual string CustomDataKey => "CustomData/SortCustomData";
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protected readonly static string[] descendingCustomData = new string[]
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{
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"2024-10-03 19:00:00,173.5,176.0,172.0,175.2,120195681,4882.29",
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"2024-10-02 18:00:00,174.0,177.0,173.0,175.8,116275729,4641.97",
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"2024-10-01 17:00:00,175.0,178.0,172.5,174.5,127707078,6591.27",
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"2024-09-30 11:00:00,174.8,176.5,172.8,175.0,127707078,6591.27",
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"2024-09-27 10:00:00,172.5,175.0,171.5,173.5,120195681,4882.29",
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"2024-09-26 09:00:00,171.0,172.5,170.0,171.8,117516350,4820.53",
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"2024-09-25 08:00:00,169.5,172.0,169.0,171.0,110427867,4661.55",
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"2024-09-24 07:00:00,170.0,171.0,168.0,169.5,127624733,4823.52",
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"2024-09-23 06:00:00,172.0,173.5,169.5,171.5,123586417,4303.93",
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"2024-09-20 05:00:00,168.0,171.0,167.5,170.5,151929179,5429.87",
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"2024-09-19 04:00:00,170.5,171.5,166.0,167.0,160523863,5219.24",
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"2024-09-18 03:00:00,173.0,174.0,169.0,172.0,145721790,5163.09",
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"2024-09-17 02:00:00,171.0,173.5,170.0,172.5,144794030,5405.72",
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"2024-09-16 01:00:00,168.0,171.0,167.0,170.0,214402430,8753.33",
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"2024-09-13 16:00:00,173.5,176.0,172.0,175.2,120195681,4882.29",
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"2024-09-12 15:00:00,174.5,177.5,173.5,176.5,171728134,7774.83",
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"2024-09-11 14:00:00,175.0,178.0,174.0,175.5,191516153,8349.59",
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"2024-09-10 13:00:00,174.5,176.0,173.0,174.0,151162819,5915.8",
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"2024-09-09 12:00:00,176.0,178.0,175.0,177.0,116275729,4641.97"
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};
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private Symbol _customSymbol;
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private List<SortCustomData> _receivedData = new();
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public override void Initialize()
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{
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SetStartDate(2024, 09, 09);
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SetEndDate(2024, 10, 03);
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SetCash(100000);
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SetBenchmark(x => 0);
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SortCustomData.CustomDataKey = CustomDataKey;
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_customSymbol = AddData<SortCustomData>("SortCustomData", Resolution.Daily).Symbol;
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// Saving data here for demonstration and regression testing purposes.
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// In real scenarios, data has to be saved to the object store before the algorithm starts.
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ObjectStore.Save(CustomDataKey, string.Join("\n", descendingCustomData));
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}
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public override void OnData(Slice slice)
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{
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if (slice.ContainsKey(_customSymbol))
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{
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var sortCustomData = slice.Get<SortCustomData>(_customSymbol);
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if (sortCustomData.Open == 0 || sortCustomData.High == 0 || sortCustomData.Low == 0 || sortCustomData.Close == 0 || sortCustomData.Price == 0)
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{
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throw new RegressionTestException("One or more custom data fields (Open, High, Low, Close, Price) are zero.");
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}
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_receivedData.Add(sortCustomData);
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}
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}
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public override void OnEndOfAlgorithm()
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{
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if (_receivedData.Count == 0)
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{
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throw new RegressionTestException("Custom data was not fetched");
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}
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var history = History<SortCustomData>(_customSymbol, StartDate, EndDate, Resolution.Hour).ToList();
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if (history.Count != _receivedData.Count)
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{
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throw new RegressionTestException("History request returned different data than expected");
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}
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// Iterate through the history collection, checking if the EndTime is in ascending order.
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for (int i = 0; i < history.Count - 1; i++)
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{
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if (history[i].EndTime > history[i + 1].EndTime)
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{
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throw new RegressionTestException($"Order failure: {history[i].EndTime} > {history[i + 1].EndTime} at index {i}.");
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}
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}
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}
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/// <summary>
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/// Final status of the algorithm
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/// </summary>
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public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
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/// <summary>
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/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
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/// </summary>
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public bool CanRunLocally => true;
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/// <summary>
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/// This is used by the regression test system to indicate which languages this algorithm is written in.
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/// </summary>
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public List<Language> Languages => new() { Language.CSharp, Language.Python };
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/// <summary>
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/// Data Points count of all TimeSlices of algorithm
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/// </summary>
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public long DataPoints => 20;
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/// <summary>
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/// Data Points count of the algorithm history
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/// </summary>
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public int AlgorithmHistoryDataPoints => 19;
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/// <summary>
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/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
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/// </summary>
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public Dictionary<string, string> ExpectedStatistics => new ()
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{
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{"Total Orders", "0"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "0%"},
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{"Drawdown", "0%"},
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{"Expectancy", "0"},
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{"Start Equity", "100000"},
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{"End Equity", "100000"},
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{"Net Profit", "0%"},
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{"Sharpe Ratio", "0"},
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{"Sortino Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "0%"},
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{"Loss Rate", "0%"},
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{"Win Rate", "0%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "0"},
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{"Beta", "0"},
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{"Annual Standard Deviation", "0"},
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{"Annual Variance", "0"},
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{"Information Ratio", "0"},
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{"Tracking Error", "0"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$0.00"},
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{"Estimated Strategy Capacity", "$0"},
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{"Lowest Capacity Asset", ""},
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{"Portfolio Turnover", "0%"},
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{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
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};
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}
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public class SortCustomData : BaseData
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{
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public static string CustomDataKey { get; set; }
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public decimal Open { get; set; }
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public decimal High { get; set; }
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public decimal Low { get; set; }
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public decimal Close { get; set; }
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public override SubscriptionDataSource GetSource(SubscriptionDataConfig config, DateTime date, bool isLiveMode)
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{
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return new SubscriptionDataSource(CustomDataKey, SubscriptionTransportMedium.ObjectStore, FileFormat.Csv)
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{
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// Indicate that the data from the subscription will be returned in descending order.
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Sort = true
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};
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}
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public override BaseData Reader(SubscriptionDataConfig config, string line, DateTime date, bool isLiveMode)
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{
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var csv = line.Split(",");
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var data = new SortCustomData()
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{
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Symbol = config.Symbol,
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Time = DateTime.ParseExact(csv[0], DateFormat.DB, CultureInfo.InvariantCulture),
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Value = csv[4].ToDecimal(),
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Open = csv[1].ToDecimal(),
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High = csv[2].ToDecimal(),
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Low = csv[3].ToDecimal(),
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Close = csv[4].ToDecimal()
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};
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return data;
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}
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}
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}
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