Files
quantconnect--lean/Algorithm.CSharp/WarmupLowerResolutionOptionRegressionAlgorithm.cs
T
Martin-Molinero 7540af454c
Build & Test Lean / build (push) Has been cancelled
Regression Tests / build (push) Has been cancelled
Research Regression Tests / build (push) Has been cancelled
Warmup resolution respected (#6467)
* Respect warmup resolution given

- The data feed will respect the warmup resolution given and override
  the resolution used by the algorithm when adding a subscription.
  Updating regression algorithm to keep previous statistics. Adding new
  regression algorithm asserting the desired behavior

* Testing improvements

- Add more unit tests and regresion test
- Add missing data for crypto
- Fix bug with FFed data crossing after the end time of the warmup
  request

* Add more Warmup resolution regression algorithms

- Adding more warmup resolution regression algorithms, using
  Settings.WarmupResolution and an option selection case

* Add more warmup regression tests

- Adding more warmup regression tests.
- Will no longer skip universe selection subscriptions from warmup
  resolution enforcement. Updating regression algorithms data points

* Fix bug with data rounding

- Fix data rounding bug when warmup resolution is set to a different
  value than the original configuration. Updating regression algorithms
  to assert the expected behavior

* Address reviews

- Revert regression algorithms changes to use Resolution during warmup.
  Updating their stats.
- Adding new regression algorithms asserting the behavior warming up
  using a timespan and no warmup resolution
- Fix bug where data used to warmup the 'normal' enumerator will make it
  through into the warmup time span. Updating tests

* Address reviews

- Add missing comments, explaning warmup algorithms time span
  calculations.
- Revert changes in existing `WarmupOptionTimeSpanRegressionAlgorithm`
  to reduce diff to minimum
- Adding new warmup unit tests asseting algorithm warmup start time, for
  different combinations of bar count, timespan, resolution
2022-07-15 13:05:06 -03:00

186 lines
7.2 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;
using QuantConnect.Data.UniverseSelection;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Regression algorithm asserting warming up with a lower resolution for speed is respected using options
/// </summary>
public class WarmupLowerResolutionOptionRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private List<DateTime> _optionWarmupTimes = new();
private const string UnderlyingTicker = "AAPL";
private Symbol _optionSymbol;
public override void Initialize()
{
SetStartDate(2014, 06, 09);
SetEndDate(2014, 06, 09);
var option = AddOption(UnderlyingTicker);
_optionSymbol = option.Symbol;
option.SetFilter(u => u.Strikes(-5, +5).Expiration(0, 180).IncludeWeeklys());
SetWarmUp(TimeSpan.FromDays(3), Resolution.Daily);
}
/// <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 (IsWarmingUp)
{
foreach (var data in slice.Values)
{
var dataSpan = data.EndTime - data.Time;
if (dataSpan != QuantConnect.Time.OneDay)
{
throw new Exception($"Unexpected bar span! {data}: {dataSpan}");
}
}
}
if (slice.OptionChains.TryGetValue(_optionSymbol, out var chain))
{
// we find at the money (ATM) put contract with farthest expiration
var atmContract = chain
.OrderByDescending(x => x.Expiry)
.ThenBy(x => Math.Abs(chain.Underlying.Price - x.Strike))
.ThenByDescending(x => x.Right)
.FirstOrDefault();
if (atmContract != null)
{
if (IsWarmingUp)
{
if (atmContract.LastPrice == 0)
{
throw new Exception("Contract price is not set!");
}
_optionWarmupTimes.Add(Time);
}
else if (!Portfolio.Invested && IsMarketOpen(_optionSymbol))
{
// if found, trade it
MarketOrder(atmContract.Symbol, 1);
MarketOnCloseOrder(atmContract.Symbol, -1);
}
}
}
}
public override void OnSecuritiesChanged(SecurityChanges changes)
{
Debug($"{Time}-{changes}");
}
public override void OnEndOfAlgorithm()
{
var start = new DateTime(2014, 06, 07, 0, 0, 0);
var end = new DateTime(2014, 06, 07, 0, 0, 0);
var count = 0;
do
{
if (_optionWarmupTimes[count] != start)
{
throw new Exception($"Unexpected time {_optionWarmupTimes[count]} expected {start}");
}
count++;
start = start.AddDays(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 long DataPoints => 983246;
/// <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 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", "$5000.00"},
{"Lowest Capacity Asset", "AAPL 2ZTXYMUME0LUU|AAPL R735QTJ8XC9X"},
{"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", "efc14c7d9579c082d72aecd0977ed522"}
};
}
}