chore: import upstream snapshot with attribution
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wehub-resource-sync
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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.Orders;
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using QuantConnect.Interfaces;
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using QuantConnect.Data;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// This algorithm demonstrates extended market hours trading.
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/// </summary>
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/// <meta name="tag" content="using data" />
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/// <meta name="tag" content="assets" />
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/// <meta name="tag" content="regression test" />
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public class ExtendedMarketTradingRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private DateTime _lastAction;
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private Symbol _spy;
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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); //Set Start Date
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SetEndDate(2013, 10, 11); //Set End Date
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SetCash(100000); //Set Strategy Cash
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_spy = AddEquity("SPY", Resolution.Minute, Market.USA, true, 0m, true).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="slice">Slice object keyed by symbol containing the stock data</param>
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public override void OnData(Slice slice)
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{
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//Only take an action once a day.
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if (_lastAction.Date == Time.Date) return;
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TradeBar spyBar = slice["SPY"];
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//If it isnt during market hours, go ahead and buy ten!
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if (!InMarketHours())
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{
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LimitOrder(_spy, 10, spyBar.Low);
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_lastAction = Time;
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}
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}
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/// <summary>
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/// Order events are triggered on order status changes. There are many order events including non-fill messages.
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/// </summary>
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/// <param name="orderEvent">OrderEvent object with details about the order status</param>
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public override void OnOrderEvent(OrderEvent orderEvent)
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{
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if (InMarketHours())
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{
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throw new RegressionTestException("Order processed during market hours.");
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}
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Log($"{orderEvent}");
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}
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/// <summary>
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/// Check if we are in Market Hours, NYSE is open from (9:30 am to 4 pm)
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/// </summary>
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public bool InMarketHours()
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{
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TimeSpan now = Time.TimeOfDay;
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TimeSpan open = new TimeSpan(09, 30, 0);
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TimeSpan close = new TimeSpan(16, 0, 0);
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return (open < now) && (close > now);
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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 => 9643;
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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", "5"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "10.774%"},
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{"Drawdown", "0.100%"},
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{"Expectancy", "0"},
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{"Start Equity", "100000"},
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{"End Equity", "100135.59"},
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{"Net Profit", "0.136%"},
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{"Sharpe Ratio", "8.723"},
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{"Sortino Ratio", "41.728"},
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{"Probabilistic Sharpe Ratio", "85.708%"},
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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", "0.005"},
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{"Beta", "0.039"},
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{"Annual Standard Deviation", "0.009"},
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{"Annual Variance", "0"},
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{"Information Ratio", "-8.852"},
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{"Tracking Error", "0.214"},
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{"Treynor Ratio", "2.102"},
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{"Total Fees", "$5.00"},
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{"Estimated Strategy Capacity", "$14000000.00"},
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{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
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{"Portfolio Turnover", "1.44%"},
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{"Drawdown Recovery", "2"},
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{"OrderListHash", "ac13139c0d75afb3d39a5143eb506658"}
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};
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}
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}
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