36404a6187
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Submit (and fill in case of market orders) in the same time step even if orders are asynchronous in backtesting since it's data driven instead of real time driven.
142 lines
5.3 KiB
C#
142 lines
5.3 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 QuantConnect.Data.Market;
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using QuantConnect.Interfaces;
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using QuantConnect.Orders;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Demonstration on how to access order tickets right after placing an order.
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/// </summary>
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public class OrderTicketAssignmentDemoAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Symbol _symbol;
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private OrderTicket _ticket;
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private int _tradeCount;
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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, 11);
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SetCash(100000);
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_symbol = AddEquity("SPY", Resolution.Minute).Symbol;
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Consolidate(_symbol, TimeSpan.FromHours(1), (TradeBar bar) =>
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{
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// Reset _ticket to null on each new bar
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_ticket = null;
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_ticket = MarketOrder(_symbol, 1, asynchronous: true);
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Debug($"{Time}: Buy: Price {bar.Price}, orderId: {_ticket.OrderId}");
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_tradeCount++;
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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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// We cannot access _ticket directly because it is assigned asynchronously:
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// this order event could be triggered before _ticket is assigned.
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var ticket = orderEvent.Ticket;
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if (ticket == null)
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{
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throw new RegressionTestException("Expected order ticket in order event to not be null");
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}
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if (orderEvent.Status == OrderStatus.Submitted && _ticket != null)
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{
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throw new RegressionTestException("Field _ticket not expected no be assigned on the first order event");
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}
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Debug(ticket.ToString());
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}
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public override void OnEndOfAlgorithm()
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{
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// Just checking that orders were placed
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if (!Portfolio.Invested || _tradeCount != Transactions.OrdersCount)
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{
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throw new RegressionTestException($"Expected the portfolio to have holdings and to have {_tradeCount} trades, but had {Transactions.OrdersCount}");
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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 => 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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/// 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", "35"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "3.632%"},
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{"Drawdown", "0.000%"},
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{"Expectancy", "0"},
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{"Start Equity", "100000"},
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{"End Equity", "100045.62"},
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{"Net Profit", "0.046%"},
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{"Sharpe Ratio", "4.618"},
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{"Sortino Ratio", "13.697"},
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{"Probabilistic Sharpe Ratio", "73.517%"},
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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", "-0.025"},
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{"Beta", "0.027"},
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{"Annual Standard Deviation", "0.006"},
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{"Annual Variance", "0"},
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{"Information Ratio", "-8.991"},
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{"Tracking Error", "0.217"},
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{"Treynor Ratio", "1.042"},
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{"Total Fees", "$34.00"},
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{"Estimated Strategy Capacity", "$36000000.00"},
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{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
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{"Portfolio Turnover", "0.99%"},
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{"Drawdown Recovery", "3"},
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{"OrderListHash", "ac3803a8abaf1d1e77e009c418ba68e2"}
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};
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}
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}
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