Files
2026-07-13 13:02:50 +08:00

113 lines
4.3 KiB
C#

/*
* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
using System;
using System.Collections.Generic;
using System.Linq;
using QuantConnect.Data;
using QuantConnect.Data.Market;
using QuantConnect.Interfaces;
namespace QuantConnect.Algorithm.CSharp
{
public class MissingTickDataAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
public override void Initialize()
{
SetStartDate(2013, 10, 08);
SetEndDate(2013, 10, 08);
var spy = AddEquity("SPY", Resolution.Tick).Symbol;
var start = new DateTime(2013, 10, 07, 15, 0, 0);
var slices = History(new[] { spy }, start, start.AddSeconds(10), Resolution.Tick).ToList();
var tickCountInSliceHistoryCall = slices.Sum(x => x.Ticks[spy].Count);
var ticks = History<Tick>(spy, start, start.AddSeconds(10), Resolution.Tick).ToList();
var tickCountInTickHistoryCall = ticks.Count;
if (tickCountInSliceHistoryCall != tickCountInTickHistoryCall)
{
throw new RegressionTestException($@"Tick count mismatch in Slice and Tick history calls: History() returned {
tickCountInSliceHistoryCall} ticks, while History<Tick>() returned {tickCountInTickHistoryCall} ticks");
}
// Early quit, we already tested what we wanted
Quit();
}
/// <summary>
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
/// </summary>
public bool CanRunLocally { get; } = true;
/// <summary>
/// This is used by the regression test system to indicate which languages this algorithm is written in.
/// </summary>
public List<Language> Languages { get; } = new() { Language.CSharp };
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 0;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 1610;
/// <summary>
/// Final status of the algorithm
/// </summary>
public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
/// </summary>
public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Orders", "0"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "0%"},
{"Drawdown", "0%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "100000"},
{"Net Profit", "0%"},
{"Sharpe Ratio", "0"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "0%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0"},
{"Beta", "0"},
{"Annual Standard Deviation", "0"},
{"Annual Variance", "0"},
{"Information Ratio", "0"},
{"Tracking Error", "0"},
{"Treynor Ratio", "0"},
{"Total Fees", "$0.00"},
{"Estimated Strategy Capacity", "$0"},
{"Lowest Capacity Asset", ""},
{"Portfolio Turnover", "0%"},
{"Drawdown Recovery", "0"},
{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
};
}
}