/*
* 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
{
///
/// This regression algorithm has two different Universe using the same SubscriptionDataConfig.
/// One of them will add and remove it in a toggle fashion but since it will still be consumed
/// by the other Universe it should not be removed.
///
///
public class UniverseSharingSubscriptionRequestRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private readonly Symbol _spy = QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA);
private int _onDataCalls;
private bool _restOneDay;
///
/// 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, 01); //Set Start Date
SetEndDate(2013, 10, 30); //Set End Date
SetCash(100000); //Set Strategy Cash
AddEquity("SPY", Resolution.Daily);
UniverseSettings.Resolution = Resolution.Daily;
AddUniverse(SecurityType.Equity,
"SecondUniverse",
Resolution.Daily,
Market.USA,
UniverseSettings,
time => time.Day % 3 == 0 ? new[] { "SPY" } : Enumerable.Empty()
);
}
///
/// 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 (slice.Count != 1)
{
throw new RegressionTestException($"Unexpected data count {slice.Count}");
}
Debug($"{slice.Time}. Data count {slice.Count}. Data {slice.Bars.First().Value}");
_onDataCalls++;
if (_restOneDay)
{
// let a day pass before trading again, this will cause
// "SecondUniverse" remove request to be applied
_restOneDay = false;
}
else if(!Portfolio.Invested)
{
SetHoldings(_spy, 1);
Debug("Purchased Stock");
}
else
{
SetHoldings(_spy, 0);
Debug("Sell Stock");
_restOneDay = true;
}
}
public override void OnEndOfAlgorithm()
{
if (_onDataCalls != 22)
{
throw new RegressionTestException($"Unexpected OnData() calls count {_onDataCalls}");
}
}
///
/// 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 => 206;
///
/// 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", "15"},
{"Average Win", "0.30%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "29.578%"},
{"Drawdown", "0.700%"},
{"Expectancy", "0"},
{"Start Equity", "100000"},
{"End Equity", "102128.38"},
{"Net Profit", "2.128%"},
{"Sharpe Ratio", "4.345"},
{"Sortino Ratio", "7.134"},
{"Probabilistic Sharpe Ratio", "91.767%"},
{"Loss Rate", "0%"},
{"Win Rate", "100%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0.073"},
{"Beta", "0.292"},
{"Annual Standard Deviation", "0.045"},
{"Annual Variance", "0.002"},
{"Information Ratio", "-2.681"},
{"Tracking Error", "0.083"},
{"Treynor Ratio", "0.666"},
{"Total Fees", "$47.53"},
{"Estimated Strategy Capacity", "$760000000.00"},
{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
{"Portfolio Turnover", "46.41%"},
{"Drawdown Recovery", "7"},
{"OrderListHash", "224b0ff29c5b287ecffaaa257e594ef3"}
};
}
}