217 lines
8.7 KiB
C#
217 lines
8.7 KiB
C#
/*
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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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using System;
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using System.Collections.Generic;
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using QuantConnect.Data;
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using QuantConnect.Data.Consolidators;
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using QuantConnect.Data.Market;
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using QuantConnect.Indicators;
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using QuantConnect.Interfaces;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// This regression algorithm tests different overloads of the Consolidate method
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/// using a variety of bar types, including RenkoBar, VolumeRenkoBar, RangeBar,
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/// as well as common bars like TradeBar and QuoteBar with a maxCount parameter.
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/// It verifies that each overload functions correctly and that the appropriate consolidators are properly created and invoked.
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/// </summary>
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public class ConsolidateWithSizeAttributeRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Symbol _spy;
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private List<SimpleMovingAverage> _smaIndicators;
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private List<IDataConsolidator> _consolidators;
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/// <summary>
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/// Initializes the algorithm.
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/// </summary>
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public override void Initialize()
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{
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SetStartDate(2013, 10, 7);
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SetEndDate(2013, 10, 7);
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SetCash(100000);
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_spy = AddEquity("SPY", Resolution.Minute).Symbol;
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_smaIndicators = new List<SimpleMovingAverage>()
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{
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new SimpleMovingAverage("RenkoBarSMA", 10),
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new SimpleMovingAverage("VolumeRenkoBarSMA", 10),
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new SimpleMovingAverage("RangeBarSMA", 10),
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new SimpleMovingAverage("TradeBarSMA", 10),
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new SimpleMovingAverage("QuoteBarSMA", 10),
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new SimpleMovingAverage("BaseDataSMA", 10),
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};
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_consolidators = new List<IDataConsolidator>()
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{
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Consolidate<RenkoBar>(_spy, 0.1m, null, renkoBar => UpdateWithRenkoBar(renkoBar, 0)),
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Consolidate<VolumeRenkoBar>(_spy, 10000m, null, volumeRenkoBar => UpdateWithVolumeRenkoBar(volumeRenkoBar, 1)),
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Consolidate<RangeBar>(_spy, 12m, null, rangeBar => UpdateWithRangeBar(rangeBar, 2)),
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// Trade and Quote consolidators with max count
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Consolidate<TradeBar>(_spy, 10, null, tradeBar => UpdateWithTradeBar(tradeBar, 3)),
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Consolidate<QuoteBar>(_spy, 10, null, quoteBar => UpdateWithQuoteBar(quoteBar, 4)),
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// BaseData consolidator with max count
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Consolidate<BaseData>(_spy, 10, null, quoteBar => UpdateWithBaseData(quoteBar, 5))
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};
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}
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// <summary>
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/// Updates the BaseDataSMA indicator with the bar's value.
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/// </summary>
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private void UpdateWithBaseData(BaseData baseData, int position)
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{
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_smaIndicators[position].Update(baseData.EndTime, baseData.Value);
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}
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/// <summary>
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/// Updates the TradeBarSMA indicator with the bar's high price.
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/// </summary>
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private void UpdateWithTradeBar(TradeBar tradeBar, int position)
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{
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_smaIndicators[position].Update(tradeBar.EndTime, tradeBar.High);
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}
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/// <summary>
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/// Updates the QuoteBarSMA indicator with the bar's high price.
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/// </summary>
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private void UpdateWithQuoteBar(QuoteBar quoteBar, int position)
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{
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_smaIndicators[position].Update(quoteBar.EndTime, quoteBar.High);
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}
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/// <summary>
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/// Updates the RenkoBarSMA indicator with the bar's high price.
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/// </summary>
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private void UpdateWithRenkoBar(RenkoBar renkoBar, int position)
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{
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_smaIndicators[position].Update(renkoBar.EndTime, renkoBar.High);
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}
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/// <summary>
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/// Updates the VolumeRenkoBarSMA indicator with the bar's high price.
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/// </summary>
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private void UpdateWithVolumeRenkoBar(VolumeRenkoBar volumeRenkoBar, int position)
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{
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_smaIndicators[position].Update(volumeRenkoBar.EndTime, volumeRenkoBar.High);
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}
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/// <summary>
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/// Updates the RangeBarSMA indicator with the bar's high price.
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/// </summary>
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private void UpdateWithRangeBar(RangeBar rangeBar, int position)
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{
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_smaIndicators[position].Update(rangeBar.EndTime, rangeBar.High);
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}
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public override void OnEndOfAlgorithm()
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{
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// Verifies that each SMA was updated and is ready, confirming the Consolidate overloads functioned correctly.
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foreach (var sma in _smaIndicators)
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{
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if (sma.Samples == 0)
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{
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throw new RegressionTestException($"The indicator '{sma.Name}' did not receive any updates. This indicates the associated consolidator was not triggered.");
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}
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if (!sma.IsReady)
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{
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throw new RegressionTestException($"The indicator '{sma.Name}' is not ready. It received only {sma.Samples} samples, but requires at least {sma.Period} to be ready.");
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}
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}
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var expectedConsolidatorTypes = new List<Type>()
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{
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typeof(RenkoConsolidator),
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typeof(VolumeRenkoConsolidator),
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typeof(RangeConsolidator),
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typeof(TradeBarConsolidator),
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typeof(QuoteBarConsolidator),
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typeof(BaseDataConsolidator)
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};
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for (var i = 0; i < _consolidators.Count; i++)
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{
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var consolidator = _consolidators[i];
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if (consolidator.GetType() != expectedConsolidatorTypes[i])
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{
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throw new RegressionTestException($"Expected consolidator type {expectedConsolidatorTypes[i]} but received {consolidator.GetType()}");
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}
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}
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}
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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 { get; } = 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 { get; } = 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 => 795;
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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 => 0;
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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 what the expected statistics are from running the algorithm
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/// </summary>
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public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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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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{"Drawdown Recovery", "0"},
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{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
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};
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}
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}
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