239 lines
9.7 KiB
C#
239 lines
9.7 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 System.Linq;
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using QuantConnect.Data;
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using QuantConnect.Indicators;
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using QuantConnect.Interfaces;
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using QuantConnect.Orders;
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using QuantConnect.Statistics;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Demonstration of how to access the statistics results from within an algorithm through the <see cref="Statistics"/> property.
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/// </summary>
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public class StatisticsResultsAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private const string MostTradedSecurityStatistic = "Most Traded Security";
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private const string MostTradedSecurityTradeCountStatistic = "Most Traded Security Trade Count";
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private Symbol _spy;
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private Symbol _ibm;
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private ExponentialMovingAverage _fastSpyEma;
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private ExponentialMovingAverage _slowSpyEma;
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private ExponentialMovingAverage _fastIbmEma;
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private ExponentialMovingAverage _slowIbmEma;
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private Dictionary<Symbol, int> _tradeCounts = new();
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public override void Initialize()
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{
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SetStartDate(2013, 10, 07);
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SetEndDate(2013, 10, 11);
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SetCash(100000);
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_spy = AddEquity("SPY", Resolution.Minute).Symbol;
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_ibm = AddEquity("IBM", Resolution.Minute).Symbol;
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_fastSpyEma = EMA(_spy, 30, Resolution.Minute);
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_slowSpyEma = EMA(_spy, 60, Resolution.Minute);
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_fastIbmEma = EMA(_spy, 10, Resolution.Minute);
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_slowIbmEma = EMA(_spy, 30, Resolution.Minute);
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}
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public override void OnData(Slice slice)
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{
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if (!_slowSpyEma.IsReady) return;
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if (_fastSpyEma > _slowSpyEma)
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{
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SetHoldings(_spy, 0.5);
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}
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else if (Securities[_spy].Invested)
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{
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Liquidate(_spy);
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}
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if (_fastIbmEma > _slowIbmEma)
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{
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SetHoldings(_ibm, 0.2);
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}
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else if (Securities[_ibm].Invested)
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{
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Liquidate(_ibm);
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}
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}
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public override void OnOrderEvent(OrderEvent orderEvent)
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{
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if (orderEvent.Status == OrderStatus.Filled)
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{
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// We can access the statistics summary at runtime
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var statistics = Statistics.Summary;
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var statisticsStr = string.Join("\n\t", statistics.Select(kvp => $"{kvp.Key}: {kvp.Value}"));
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Debug($"\nStatistics after fill:\n\t{statisticsStr}");
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// Access a single statistic
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Log($"Total trades so far: {statistics[PerformanceMetrics.TotalOrders]}");
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Log($"Sharpe Ratio: {statistics[PerformanceMetrics.SharpeRatio]}");
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// --------
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// We can also set custom summary statistics:
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KeyValuePair<Symbol, int> mostTradeSecurityKvp;
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// Before the first fill event, our custom statistics should not be set in the summary
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if (_tradeCounts.All(kvp => kvp.Value == 0))
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{
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if (statistics.ContainsKey(MostTradedSecurityStatistic))
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{
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throw new RegressionTestException($"Statistic {MostTradedSecurityStatistic} should not be set yet");
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}
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if (statistics.ContainsKey(MostTradedSecurityTradeCountStatistic))
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{
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throw new RegressionTestException($"Statistic {MostTradedSecurityTradeCountStatistic} should not be set yet");
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}
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}
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else
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{
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// The current most traded security should be set in the summary
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mostTradeSecurityKvp = _tradeCounts.MaxBy(kvp => kvp.Value);
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CheckMostTradedSecurityStatistic(statistics, mostTradeSecurityKvp.Key, mostTradeSecurityKvp.Value);
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}
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// Update the trade count
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var tradeCount = _tradeCounts.GetValueOrDefault(orderEvent.Symbol);
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_tradeCounts[orderEvent.Symbol] = tradeCount + 1;
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// Set the most traded security
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mostTradeSecurityKvp = _tradeCounts.MaxBy(kvp => kvp.Value);
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SetSummaryStatistic(MostTradedSecurityStatistic, mostTradeSecurityKvp.Key);
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SetSummaryStatistic(MostTradedSecurityTradeCountStatistic, mostTradeSecurityKvp.Value);
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// Re-calculate statistics:
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statistics = Statistics.Summary;
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// Let's keep track of our custom summary statistics after the update
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CheckMostTradedSecurityStatistic(statistics, mostTradeSecurityKvp.Key, mostTradeSecurityKvp.Value);
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}
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}
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public override void OnEndOfAlgorithm()
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{
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var statistics = Statistics.Summary;
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if (!statistics.ContainsKey(MostTradedSecurityStatistic))
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{
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throw new RegressionTestException($"Statistic {MostTradedSecurityStatistic} should be in the summary statistics");
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}
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if (!statistics.ContainsKey(MostTradedSecurityTradeCountStatistic))
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{
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throw new RegressionTestException($"Statistic {MostTradedSecurityTradeCountStatistic} should be in the summary statistics");
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}
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var mostTradeSecurityKvp = _tradeCounts.MaxBy(kvp => kvp.Value);
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CheckMostTradedSecurityStatistic(statistics, mostTradeSecurityKvp.Key, mostTradeSecurityKvp.Value);
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}
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private void CheckMostTradedSecurityStatistic(Dictionary<string, string> statistics, Symbol mostTradedSecurity, int tradeCount)
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{
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var mostTradedSecurityStatistic = statistics[MostTradedSecurityStatistic];
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var mostTradedSecurityTradeCountStatistic = statistics[MostTradedSecurityTradeCountStatistic];
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Log($"Most traded security: {mostTradedSecurityStatistic}");
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Log($"Most traded security trade count: {mostTradedSecurityTradeCountStatistic}");
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if (mostTradedSecurityStatistic != mostTradedSecurity)
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{
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throw new RegressionTestException($"Most traded security should be {mostTradedSecurity} but it is {mostTradedSecurityStatistic}");
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}
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if (mostTradedSecurityTradeCountStatistic != tradeCount.ToStringInvariant())
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{
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throw new RegressionTestException($"Most traded security trade count should be {tradeCount} but it is {mostTradedSecurityTradeCountStatistic}");
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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 => 7843;
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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", "94"},
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{"Average Win", "0.09%"},
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{"Average Loss", "-0.03%"},
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{"Compounding Annual Return", "18.903%"},
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{"Drawdown", "0.800%"},
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{"Expectancy", "0.135"},
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{"Start Equity", "100000"},
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{"End Equity", "100221.61"},
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{"Net Profit", "0.222%"},
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{"Sharpe Ratio", "6.406"},
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{"Sortino Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "68.575%"},
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{"Loss Rate", "70%"},
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{"Win Rate", "30%"},
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{"Profit-Loss Ratio", "2.73"},
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{"Alpha", "-0.144"},
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{"Beta", "0.264"},
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{"Annual Standard Deviation", "0.059"},
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{"Annual Variance", "0.003"},
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{"Information Ratio", "-9.751"},
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{"Tracking Error", "0.164"},
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{"Treynor Ratio", "1.43"},
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{"Total Fees", "$114.39"},
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{"Estimated Strategy Capacity", "$1100000.00"},
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{"Lowest Capacity Asset", "IBM R735QTJ8XC9X"},
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{"Portfolio Turnover", "549.26%"},
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{"Drawdown Recovery", "3"},
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{"Most Traded Security", "IBM"},
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{"Most Traded Security Trade Count", "63"},
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{"OrderListHash", "8dd77e35338a81410a5b68dc8345f402"}
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};
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}
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}
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