/*
* 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 QuantConnect.Data;
using QuantConnect.Interfaces;
using QuantConnect.Scheduling;
namespace QuantConnect.Algorithm.CSharp
{
///
/// Regression algorithm which reproduces GH issue 4131, we assert order events are executed in order
/// event outside market ours
///
public class ScheduledEventsOrderRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private int _scheduledEventCount;
private int _afterMarketOpenEventCount;
private Symbol _spy;
private DateTime _lastTime = DateTime.MinValue;
///
/// 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(2013, 10, 07);
SetEndDate(2013, 10, 11);
_spy = AddEquity("SPY").Symbol;
var test = 0;
var dateRule = DateRules.EveryDay(_spy);
var aEventCount = 0;
var bEventCount = 0;
var cEventCount = 0;
var symbol = QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA);
Schedule.On(DateRules.WeekStart(symbol), TimeRules.AfterMarketOpen(symbol), AfterMarketOpen);
// we add each twice and assert the order in which they are added is also respected for events at the same time
for (var i = 0; i < 2; i++)
{
var id = i;
Schedule.On(dateRule, TimeRules.At(9, 25), (name, time) =>
{
// for id 0 event count should always be 0, for id 1 should be 1
if (aEventCount != id)
{
throw new RegressionTestException($"Scheduled event triggered out of order: {Time} expected id {id} but was {aEventCount}");
}
aEventCount++;
// goes from 0 to 1
aEventCount %= 2;
AssertScheduledEventTime();
Debug($"{Time} :: Test: {test}"); test++;
});
Schedule.On(dateRule, TimeRules.BeforeMarketClose(_spy, 5), (name, time) =>
{
// for id 0 event count should always be 0, for id 1 should be 1
if (bEventCount != id)
{
throw new RegressionTestException($"Scheduled event triggered out of order: {Time} expected id {id} but was {bEventCount}");
}
bEventCount++;
// goes from 0 to 1
bEventCount %= 2;
AssertScheduledEventTime();
Debug($"{Time} :: Test: {test}"); test++;
});
Schedule.On(dateRule, TimeRules.At(16, 5), (name, time) =>
{
// for id 0 event count should always be 0, for id 1 should be 1
if (cEventCount != id)
{
throw new RegressionTestException($"Scheduled event triggered out of order: {Time} expected id {id} but was {cEventCount}");
}
cEventCount++;
// goes from 0 to 1
cEventCount %= 2;
AssertScheduledEventTime();
Debug($"{Time} :: Test: {test}"); test = 0;
});
}
}
private void AssertScheduledEventTime()
{
if (_lastTime > Time)
{
throw new RegressionTestException($"Scheduled event time shouldn't go backwards, last time {_lastTime}, current {Time}");
}
_lastTime = Time;
_scheduledEventCount++;
}
private void AfterMarketOpen()
{
_afterMarketOpenEventCount++;
if (Time.TimeOfDay != TimeSpan.FromHours(9.5))
{
throw new RegressionTestException($"AfterMarketOpen unexpected event time: {Time}");
}
}
public override void OnEndOfAlgorithm()
{
if (_scheduledEventCount != 28)
{
throw new RegressionTestException($"OnEndOfAlgorithm expected scheduled events but was {_scheduledEventCount}");
}
if (_afterMarketOpenEventCount != 1)
{
throw new RegressionTestException($"OnEndOfAlgorithm expected after MarketOpenEvent count {_afterMarketOpenEventCount}");
}
}
///
/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
///
/// Slice object keyed by symbol containing the stock data
public override void OnData(Slice slice)
{
if (!Portfolio.Invested)
{
SetHoldings(_spy, 1);
}
}
///
/// 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 => 3943;
///
/// 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", "271.453%"},
{"Drawdown", "2.200%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "101691.92"},
{"Net Profit", "1.692%"},
{"Sharpe Ratio", "8.854"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "67.609%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "-0.005"},
{"Beta", "0.996"},
{"Annual Standard Deviation", "0.222"},
{"Annual Variance", "0.049"},
{"Information Ratio", "-14.565"},
{"Tracking Error", "0.001"},
{"Treynor Ratio", "1.97"},
{"Total Fees", "$3.44"},
{"Estimated Strategy Capacity", "$56000000.00"},
{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
{"Portfolio Turnover", "19.93%"},
{"Drawdown Recovery", "3"},
{"OrderListHash", "3da9fa60bf95b9ed148b95e02e0cfc9e"}
};
}
}