9ee61f425c
A mechanical refactoring was performed to make algorithms currently used in regression algorithms to implement IRegressionAlgorithmDefinition, which allows algorithms to define their own expected statistics and what languages should be run as part of regression. The type name of the C# type is used to determine the file/model name for python. This was for simplicity, but if needed, could later be refactored to expose more information, but for now the convention of keeping names the same makes sense and just works easily.
211 lines
9.2 KiB
C#
211 lines
9.2 KiB
C#
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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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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.Orders;
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using QuantConnect.Securities;
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using QuantConnect.Util;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Provides a regression baseline focused on updating orders
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/// </summary>
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/// <meta name="tag" content="regression test" />
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public class UpdateOrderRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private int LastMonth = -1;
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private Security Security;
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private int Quantity = 100;
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private const int DeltaQuantity = 10;
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private const decimal StopPercentage = 0.025m;
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private const decimal StopPercentageDelta = 0.005m;
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private const decimal LimitPercentage = 0.025m;
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private const decimal LimitPercentageDelta = 0.005m;
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private const string symbol = "SPY";
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private const SecurityType SecType = SecurityType.Equity;
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private readonly CircularQueue<OrderType> _orderTypesQueue = new CircularQueue<OrderType>(Enum.GetValues(typeof(OrderType))
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.OfType<OrderType>()
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.Where (x => x != OrderType.OptionExercise));
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private readonly List<OrderTicket> _tickets = new List<OrderTicket>();
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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, 01, 01); //Set Start Date
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SetEndDate(2015, 01, 01); //Set End Date
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SetCash(100000); //Set Strategy Cash
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// Find more symbols here: http://quantconnect.com/data
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AddSecurity(SecType, symbol, Resolution.Daily);
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Security = Securities[symbol];
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_orderTypesQueue.CircleCompleted += (sender, args) =>
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{
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// flip our signs when we've gone through all the order types
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Quantity *= -1;
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};
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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 (!data.Bars.ContainsKey(symbol)) return;
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// each month make an action
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if (Time.Month != LastMonth)
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{
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// we'll submit the next type of order from the queue
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var orderType = _orderTypesQueue.Dequeue();
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//Log("");
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Log("\r\n--------------MONTH: " + Time.ToString("MMMM") + ":: " + orderType + "\r\n");
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//Log("");
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LastMonth = Time.Month;
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Log("ORDER TYPE:: " + orderType);
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var isLong = Quantity > 0;
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var stopPrice = isLong ? (1 + StopPercentage)*data.Bars[symbol].High : (1 - StopPercentage)*data.Bars[symbol].Low;
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var limitPrice = isLong ? (1 - LimitPercentage)*stopPrice : (1 + LimitPercentage)*stopPrice;
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if (orderType == OrderType.Limit)
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{
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limitPrice = !isLong ? (1 + LimitPercentage) * data.Bars[symbol].High : (1 - LimitPercentage) * data.Bars[symbol].Low;
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}
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var request = new SubmitOrderRequest(orderType, SecType, symbol, Quantity, stopPrice, limitPrice, UtcTime, orderType.ToString());
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var ticket = Transactions.AddOrder(request);
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_tickets.Add(ticket);
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}
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else if (_tickets.Count > 0)
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{
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var ticket = _tickets.Last();
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if (Time.Day > 8 && Time.Day < 14)
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{
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if (ticket.UpdateRequests.Count == 0 && ticket.Status.IsOpen())
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{
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Log("TICKET:: " + ticket);
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ticket.Update(new UpdateOrderFields
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{
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Quantity = ticket.Quantity + Math.Sign(Quantity)*DeltaQuantity,
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Tag = "Change quantity: " + Time
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});
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Log("UPDATE1:: " + ticket.UpdateRequests.Last());
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}
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}
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else if (Time.Day > 13 && Time.Day < 20)
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{
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if (ticket.UpdateRequests.Count == 1 && ticket.Status.IsOpen())
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{
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Log("TICKET:: " + ticket);
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ticket.Update(new UpdateOrderFields
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{
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LimitPrice = Security.Price*(1 - Math.Sign(ticket.Quantity)*LimitPercentageDelta),
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StopPrice = Security.Price*(1 + Math.Sign(ticket.Quantity)*StopPercentageDelta),
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Tag = "Change prices: " + Time
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});
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Log("UPDATE2:: " + ticket.UpdateRequests.Last());
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}
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}
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else
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{
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if (ticket.UpdateRequests.Count == 2 && ticket.Status.IsOpen())
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{
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Log("TICKET:: " + ticket);
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ticket.Cancel(Time + " and is still open!");
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Log("CANCELLED:: " + ticket.CancelRequest);
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}
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}
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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 the order time isn't equal to the algo time, then the modified time on the order should be updated
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var order = Transactions.GetOrderById(orderEvent.OrderId);
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var ticket = Transactions.GetOrderTicket(orderEvent.OrderId);
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if (order.Status == OrderStatus.Canceled && order.CanceledTime != orderEvent.UtcTime)
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{
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throw new Exception("Expected canceled order CanceledTime to equal canceled order event time.");
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}
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// fills update LastFillTime
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if ((order.Status == OrderStatus.Filled || order.Status == OrderStatus.PartiallyFilled) && order.LastFillTime != orderEvent.UtcTime)
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{
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throw new Exception("Expected filled order LastFillTime to equal fill order event time.");
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}
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// check the ticket to see if the update was successfully processed
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if (ticket.UpdateRequests.Any(ur => ur.Response?.IsSuccess == true) && order.CreatedTime != UtcTime && order.LastUpdateTime == null)
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{
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throw new Exception("Expected updated order LastUpdateTime to equal submitted update order event time");
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}
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if (orderEvent.Status == OrderStatus.Filled)
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{
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Log("FILLED:: " + Transactions.GetOrderById(orderEvent.OrderId) + " FILL PRICE:: " + orderEvent.FillPrice.SmartRounding());
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}
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else
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{
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Log(orderEvent.ToString());
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Log("TICKET:: " + _tickets.Last());
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}
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}
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private new void Log(string msg)
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{
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if (LiveMode) Debug(msg);
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else base.Log(msg);
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}
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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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/// 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", "21"},
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{"Average Win", "0%"},
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{"Average Loss", "-1.70%"},
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{"Compounding Annual Return", "-8.246%"},
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{"Drawdown", "16.600%"},
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{"Expectancy", "-1"},
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{"Net Profit", "-15.812%"},
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{"Sharpe Ratio", "-1.352"},
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{"Loss Rate", "100%"},
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{"Win Rate", "0%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "-0.063"},
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{"Beta", "-1.046"},
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{"Annual Standard Deviation", "0.062"},
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{"Annual Variance", "0.004"},
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{"Information Ratio", "-1.673"},
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{"Tracking Error", "0.062"},
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{"Treynor Ratio", "0.08"},
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{"Total Fees", "$21.00"},
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};
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}
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} |