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quantconnect--lean/Algorithm.CSharp/WarmupOptionRegressionAlgorithm.cs
T
Martin-Molinero fc6835cace
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Normalize time in universe behavior (#6693)
* Normalize time in universe behavior

- Normalize Option & Future chain universe behavior regarding their
  assets time in universe. They will now respect the universe settings
  time in universe value. Adding new regression algorithms asserting the
  behavior

* Address reviews & cleanup
2022-10-14 15:13:59 -03:00

173 lines
6.9 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.Linq;
using QuantConnect.Data;
using QuantConnect.Interfaces;
using System.Collections.Generic;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Regression algorithm asserting the behavior of option warmup
/// </summary>
public class WarmupOptionRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private const string UnderlyingTicker = "GOOG";
private Symbol _optionSymbol;
protected List<DateTime> OptionWarmupTimes { get; } = new();
public override void Initialize()
{
SetStartDate(2015, 12, 24);
SetEndDate(2015, 12, 24);
SetCash(100000);
var option = AddOption(UnderlyingTicker);
_optionSymbol = option.Symbol;
option.SetFilter(u => u.Strikes(-5, +5).Expiration(0, 180).IncludeWeeklys());
SetWarmUp(TimeSpan.FromDays(1));
}
/// <summary>
/// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event
/// </summary>
/// <param name="slice">The current slice of data keyed by symbol string</param>
public override void OnData(Slice slice)
{
if (slice.OptionChains.TryGetValue(_optionSymbol, out var chain))
{
// we find at the money (ATM) put contract with farthest expiration
var atmContract = chain
.OrderByDescending(x => x.Expiry)
.ThenBy(x => Math.Abs(chain.Underlying.Price - x.Strike))
.ThenByDescending(x => x.Right)
.FirstOrDefault();
if (atmContract != null)
{
// during warmup, using daily resolution (with the same TZ as the algorithm) the last bar.EndTime of warmup
// overlaps with the algorithm start time, considered not to be in warmup anymore.
// This bar would also be emitted by lean if no warmup was set and daily resolution used, see 'BasicTemplateDailyAlgorithm'
if (Time <= StartDate)
{
if(atmContract.LastPrice == 0)
{
throw new Exception("Contract price is not set!");
}
OptionWarmupTimes.Add(Time);
}
else if (!Portfolio.Invested && IsMarketOpen(_optionSymbol))
{
// if found, trade it
MarketOrder(atmContract.Symbol, 1);
MarketOnCloseOrder(atmContract.Symbol, -1);
}
}
}
}
public override void OnEndOfAlgorithm()
{
var start = new DateTime(2015, 12, 23, 9, 31, 0);
var end = new DateTime(2015, 12, 23, 16, 0, 0);
var count = 0;
do
{
if (OptionWarmupTimes[count] != start)
{
throw new Exception($"Unexpected time {OptionWarmupTimes[count]} expected {start}");
}
count++;
start = start.AddMinutes(1);
}
while (start < end);
}
/// <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 Language[] Languages { get; } = { Language.CSharp };
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public virtual long DataPoints => 1111432;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 0;
/// <summary>
/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
/// </summary>
public virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
{
{"Total Trades", "2"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "0%"},
{"Drawdown", "0%"},
{"Expectancy", "0"},
{"Net Profit", "0%"},
{"Sharpe 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", "$2.00"},
{"Estimated Strategy Capacity", "$1300000.00"},
{"Lowest Capacity Asset", "GOOCV 30AKMEIPOSS1Y|GOOCV VP83T1ZUHROL"},
{"Fitness Score", "0"},
{"Kelly Criterion Estimate", "0"},
{"Kelly Criterion Probability Value", "0"},
{"Sortino Ratio", "79228162514264337593543950335"},
{"Return Over Maximum Drawdown", "79228162514264337593543950335"},
{"Portfolio Turnover", "0"},
{"Total Insights Generated", "0"},
{"Total Insights Closed", "0"},
{"Total Insights Analysis Completed", "0"},
{"Long Insight Count", "0"},
{"Short Insight Count", "0"},
{"Long/Short Ratio", "100%"},
{"Estimated Monthly Alpha Value", "$0"},
{"Total Accumulated Estimated Alpha Value", "$0"},
{"Mean Population Estimated Insight Value", "$0"},
{"Mean Population Direction", "0%"},
{"Mean Population Magnitude", "0%"},
{"Rolling Averaged Population Direction", "0%"},
{"Rolling Averaged Population Magnitude", "0%"},
{"OrderListHash", "9d9f9248ee8fe30d87ff0a6f6fea5112"}
};
}
}