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* Adds Unit Tests The `LimitFill` method should not fill using `QuoteBar` or `Tick` with `TickType.Quote` type. Adds missing test for tick data (`TickType.Trade`). * Fixes EquityFillModel.FillModel Use `Tick` with `TickType.Trade` or `TradeBar` information to fill limit orders. * Update Regression Test Expected Statistics The regression tests changed because of different fills. The `ExtendedMarketTradingRegressionAlgorithm` has different number of trades because of an extra fill on the 4th order generated by TradeBar with a Low lower than than the QuoteBar.Ask Low: > 20230222 13:56:24.251 TRACE:: Log: Time: 10/10/2013 12:01:00 OrderID: 4 EventID: 2 Symbol: SPY Status: Filled Quantity: 10 FillQuantity: 10 FillPrice: 143.8998 USD > asset.Cache.GetData<QuoteBar>().ToString() "SPY: Bid: O: 144.2457 Bid: H: 144.2629 Bid: **L: 144.2457** Bid: C: 144.2629 Ask: O: 144.2543 Ask: H: 144.2889 Ask: **L: 144.2543** Ask: C: 144.2889 " > asset.Cache.GetData<TradeBar>().ToString() "SPY: O: 144.2543 H: 144.4532 **L: 143.4156** C: 144.2716 V: 75423" * Improves Tick Resolution Unit Test * Fixes Tick Resolution Case Handling `master` only considers the latest trade, missing possible fills in the batch of trades. * Adds Unit Test for Gap See https://github.com/QuantConnect/Lean/issues/963 * Addresses Fill Optimistic Assumption If we have a bar that gaps in our favor, we accept the limit price to avoid optimitic fills. * Fixes Regression Tests All regression tests with limit orders have worst performance after we remove the optimitic assumption, and use the limit price instead.
208 lines
8.9 KiB
C#
208 lines
8.9 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.Orders;
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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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/// Demonstration algorithm of time in force order settings.
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/// </summary>
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/// <meta name="tag" content="using data" />
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/// <meta name="tag" content="using quantconnect" />
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/// <meta name="tag" content="trading and orders" />
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public class TimeInForceAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Symbol _symbol;
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private OrderTicket _gtcOrderTicket1, _gtcOrderTicket2;
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private OrderTicket _dayOrderTicket1, _dayOrderTicket2;
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private OrderTicket _gtdOrderTicket1, _gtdOrderTicket2;
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private readonly Dictionary<int, OrderStatus> _expectedOrderStatuses = new Dictionary<int, OrderStatus>();
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/// <summary>
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/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
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/// </summary>
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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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// The default time in force setting for all orders is GoodTilCancelled (GTC),
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// uncomment this line to set a different time in force.
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// We currently only support GTC, DAY, GTD.
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// DefaultOrderProperties.TimeInForce = TimeInForce.Day;
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_symbol = AddEquity("SPY", Resolution.Minute).Symbol;
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}
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/// <summary>
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/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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/// </summary>
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/// <param name="data">Slice object keyed by symbol containing the stock data</param>
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public override void OnData(Slice data)
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{
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if (_gtcOrderTicket1 == null)
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{
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// These GTC orders will never expire and will not be canceled automatically.
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DefaultOrderProperties.TimeInForce = TimeInForce.GoodTilCanceled;
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// this order will not be filled before the end of the backtest
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_gtcOrderTicket1 = LimitOrder(_symbol, 10, 100m);
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_expectedOrderStatuses.Add(_gtcOrderTicket1.OrderId, OrderStatus.Submitted);
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// this order will be filled before the end of the backtest
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_gtcOrderTicket2 = LimitOrder(_symbol, 10, 160m);
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_expectedOrderStatuses.Add(_gtcOrderTicket2.OrderId, OrderStatus.Filled);
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}
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if (_dayOrderTicket1 == null)
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{
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// These DAY orders will expire at market close,
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// if not filled by then they will be canceled automatically.
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DefaultOrderProperties.TimeInForce = TimeInForce.Day;
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// this order will not be filled before market close and will be canceled
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_dayOrderTicket1 = LimitOrder(_symbol, 10, 140m);
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_expectedOrderStatuses.Add(_dayOrderTicket1.OrderId, OrderStatus.Canceled);
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// this order will be filled before market close
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_dayOrderTicket2 = LimitOrder(_symbol, 10, 180m);
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_expectedOrderStatuses.Add(_dayOrderTicket2.OrderId, OrderStatus.Filled);
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}
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if (_gtdOrderTicket1 == null)
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{
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// These GTD orders will expire on October 10th at market close,
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// if not filled by then they will be canceled automatically.
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DefaultOrderProperties.TimeInForce = TimeInForce.GoodTilDate(new DateTime(2013, 10, 10));
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// this order will not be filled before expiry and will be canceled
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_gtdOrderTicket1 = LimitOrder(_symbol, 10, 100m);
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_expectedOrderStatuses.Add(_gtdOrderTicket1.OrderId, OrderStatus.Canceled);
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// this order will be filled before expiry
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_gtdOrderTicket2 = LimitOrder(_symbol, 10, 160m);
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_expectedOrderStatuses.Add(_gtdOrderTicket2.OrderId, OrderStatus.Filled);
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}
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}
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/// <summary>
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/// Order event handler. This handler will be called for all order events, including submissions, fills, cancellations.
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/// </summary>
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/// <param name="orderEvent">Order event instance containing details of the event</param>
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/// <remarks>This method can be called asynchronously, ensure you use proper locks on thread-unsafe objects</remarks>
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public override void OnOrderEvent(OrderEvent orderEvent)
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{
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Debug($"{Time} {orderEvent}");
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}
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/// <summary>
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/// End of algorithm run event handler. This method is called at the end of a backtest or live trading operation.
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/// </summary>
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public override void OnEndOfAlgorithm()
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{
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foreach (var kvp in _expectedOrderStatuses)
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{
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var orderId = kvp.Key;
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var expectedStatus = kvp.Value;
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var order = Transactions.GetOrderById(orderId);
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if (order.Status != expectedStatus)
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{
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throw new Exception($"Invalid status for order {orderId} - Expected: {expectedStatus}, actual: {order.Status}");
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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 Language[] Languages { get; } = { 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 => 3943;
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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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/// 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 Trades", "3"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "-36.833%"},
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{"Drawdown", "0.700%"},
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{"Expectancy", "0"},
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{"Net Profit", "-0.586%"},
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{"Sharpe Ratio", "5.023"},
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{"Probabilistic Sharpe Ratio", "67.468%"},
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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", "-0.038"},
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{"Beta", "0.043"},
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{"Annual Standard Deviation", "0.01"},
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{"Annual Variance", "0"},
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{"Information Ratio", "-9.087"},
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{"Tracking Error", "0.213"},
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{"Treynor Ratio", "1.118"},
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{"Total Fees", "$3.00"},
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{"Estimated Strategy Capacity", "$43000000.00"},
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{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
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{"Fitness Score", "0"},
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{"Kelly Criterion Estimate", "0"},
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{"Kelly Criterion Probability Value", "0"},
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{"Sortino Ratio", "-5.89"},
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{"Return Over Maximum Drawdown", "-57.561"},
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{"Portfolio Turnover", "0.012"},
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{"Total Insights Generated", "0"},
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{"Total Insights Closed", "0"},
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{"Total Insights Analysis Completed", "0"},
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{"Long Insight Count", "0"},
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{"Short Insight Count", "0"},
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{"Long/Short Ratio", "100%"},
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{"Estimated Monthly Alpha Value", "$0"},
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{"Total Accumulated Estimated Alpha Value", "$0"},
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{"Mean Population Estimated Insight Value", "$0"},
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{"Mean Population Direction", "0%"},
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{"Mean Population Magnitude", "0%"},
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{"Rolling Averaged Population Direction", "0%"},
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{"Rolling Averaged Population Magnitude", "0%"},
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{"OrderListHash", "5c0b51e308a4638b7cae3b84ddb36526"}
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};
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}
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}
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