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.Collections.Generic;
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using QuantConnect.Data;
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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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/// Regression algorithm reproducing the stale fill issue: a market order must not be filled on data that is older
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/// than the subscribed resolution (the latest available bar is more than one resolution behind the fill time),
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/// regardless of the time of day. The fill should wait until fresh data is available.
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///
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/// Two orders are submitted to cover both cases:
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/// - right after the market open (9:30:01), when the only data available is the previous trading date's bar
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/// (the original reported case), and
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/// - mid-session (noon), where data is continuous and the order fills normally on fresh data.
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/// <see cref="QuantConnect.Orders.Fills.EquityFillModel.MarketFill"/>
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/// </summary>
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public class MarketOrderStaleDataFillRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Symbol _spy;
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private System.TimeSpan _resolutionSpan;
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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.
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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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var resolution = Resolution.Minute;
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_resolutionSpan = resolution.ToTimeSpan();
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_spy = AddEquity("SPY", resolution).Symbol;
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// Market open: order one second after the open, before the first minute bar of the session is available
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Schedule.On(DateRules.EveryDay(_spy), TimeRules.At(9, 30, 1), Trade);
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// Mid-session: data is continuous here, so the order fills normally on fresh data
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Schedule.On(DateRules.EveryDay(_spy), TimeRules.At(12, 0, 0), Trade);
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}
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private void Trade()
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{
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// Only trade once the security already has data, so a stale fill would be attempted against an older bar
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// (the data we want to avoid filling on) rather than against an empty cache
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if (Securities[_spy].HasData)
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{
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MarketOrder(_spy, 1);
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}
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}
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/// <summary>
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/// Asserts that market orders are never filled on data staler than the subscribed resolution, at any time of day
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/// </summary>
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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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return;
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}
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var security = Securities[orderEvent.Symbol];
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var lastData = security.GetLastData();
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if (lastData == null)
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{
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return;
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}
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// The latest available data must be within one resolution bar of the fill time. Without the fix, a market
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// order placed when only stale data is available (e.g. right after the open, before the first session bar)
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// would fill on that stale price instead of waiting for fresh data.
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var dataGap = orderEvent.UtcTime - lastData.EndTime.ConvertToUtc(security.Exchange.TimeZone);
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if (dataGap > _resolutionSpan)
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{
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throw new RegressionTestException(
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$"Order {orderEvent.OrderId} for {orderEvent.Symbol} filled at {orderEvent.UtcTime} UTC on stale " +
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$"data ending {lastData.EndTime} ({dataGap} behind, more than the {_resolutionSpan} resolution). " +
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$"The fill should have waited for fresh data.");
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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 };
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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", "9"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "1.007%"},
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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", "100012.81"},
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{"Net Profit", "0.013%"},
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{"Sharpe Ratio", "1.079"},
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{"Sortino Ratio", "3.268"},
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{"Probabilistic Sharpe Ratio", "50.232%"},
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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", "-0.012"},
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{"Beta", "0.007"},
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{"Annual Standard Deviation", "0.002"},
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{"Annual Variance", "0"},
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{"Information Ratio", "-8.931"},
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{"Tracking Error", "0.221"},
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{"Treynor Ratio", "0.244"},
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{"Total Fees", "$9.00"},
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{"Estimated Strategy Capacity", "$290000000.00"},
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{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
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{"Portfolio Turnover", "0.26%"},
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{"Drawdown Recovery", "2"},
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{"OrderListHash", "c849aa80f00dde3d93bf4cc6d65c4d5e"}
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};
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}
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}
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