/*
* 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.Interfaces;
namespace QuantConnect.Algorithm.CSharp
{
///
/// Regression test algorithm simply fetch and compare data of minute resolution around daylight saving period
/// reproduces issue reported in GB issue GH issue https://github.com/QuantConnect/Lean/issues/4925
/// related issues https://github.com/QuantConnect/Lean/issues/3707; https://github.com/QuantConnect/Lean/issues/4630
///
public class FillForwardEnumeratorOutOfOrderBarRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private decimal _exptectedClose = 84.09m;
private DateTime _exptectedTime = new DateTime(2008, 3, 10, 9, 30, 0);
private Symbol _shy;
///
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
///
public override void Initialize()
{
SetStartDate(2008, 3, 7);
SetEndDate(2008, 3, 10);
_shy = AddEquity("SHY", Resolution.Minute).Symbol;
// just to make debugging easier, less subscriptions
SetBenchmark(time => 1);
}
public override void OnData(Slice slice)
{
var trackingBar = slice.Bars.Values.FirstOrDefault(s => s.Time.Equals(_exptectedTime));
if (trackingBar != null)
{
if (!Portfolio.Invested)
{
SetHoldings(_shy, 1);
}
if (trackingBar.Close != _exptectedClose)
{
throw new RegressionTestException(
$"Bar at {_exptectedTime.ToStringInvariant()} closed at price {trackingBar.Close.ToStringInvariant()}; expected {_exptectedClose.ToStringInvariant()}");
}
}
}
///
/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
///
public bool CanRunLocally { get; } = true;
///
/// This is used by the regression test system to indicate which languages this algorithm is written in.
///
public List Languages { get; } = new() { Language.CSharp };
///
/// Data Points count of all timeslices of algorithm
///
public long DataPoints => 1561;
///
/// Data Points count of the algorithm history
///
public int AlgorithmHistoryDataPoints => 0;
///
/// Final status of the algorithm
///
public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
///
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
///
public Dictionary ExpectedStatistics => new Dictionary
{
{"Total Orders", "1"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "16.086%"},
{"Drawdown", "0.100%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "100148.25"},
{"Net Profit", "0.148%"},
{"Sharpe Ratio", "7.182"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "0%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0"},
{"Beta", "0"},
{"Annual Standard Deviation", "0.014"},
{"Annual Variance", "0"},
{"Information Ratio", "9.758"},
{"Tracking Error", "0.014"},
{"Treynor Ratio", "0"},
{"Total Fees", "$5.93"},
{"Estimated Strategy Capacity", "$150000.00"},
{"Lowest Capacity Asset", "SHY 2T"},
{"Portfolio Turnover", "24.91%"},
{"Drawdown Recovery", "0"},
{"OrderListHash", "9d00701591b363edda102536ec5e75e0"}
};
}
}