Files
quantconnect--lean/Algorithm.CSharp/AddOptionContractFromUniverseRegressionAlgorithm.cs
T
Gerardo Salazar 8c6aa6a3b3 Refactors Capacity Estimation and moves estimation to main event loop (#5351)
* Adds CapacityEstimate and SymbolCapacity

  The capacity estimation has been moved from
  the report generator and wired directly into
  Lean via the ResultHandler. In addition,
  the capacity estimation strategy has changed
  to account for errors in the previous iteration
  of the capacity estimation.

  Many many thanks to Jared for being much of the
  mastermind behind this project. It would have
  been harder to complete without him to bounce ideas
  off of.

  * Moves old tests to regression algorithms
  * Adds Estimated Capacity statistic
  * Removes old capacity estimation tests

Final report capacity estimation. Pushing to save state

* Fixes bugs, cleans up code and adds comments

  * Adds forced sampling to Capacity Estimation
  * Misc. bug fixes for daily data

* Updates capacity test cases' Estimated Strategy Capacity statistic

* Adds Capacity Estimate to all regression algorithms

* Removes Report's StrategyCapacity class and fixes bug in tests

  * Adds null check in BacktestingResultHandler to fix
    BacktestingTransactionHandler failing tests

  * Deletes old capacity estimation classes

  * Retrieve capacity estimates from backtest statistics results
    instead of calculating at runtime

* Make $0.00 capacity return as "-" and Result = 0 in report

* Adds capacity to runtime statistics

* Converts capacity to number denoted by financial figures in RuntimeStats

* Addresses review: code cleanup for Capacity and adds comments to regression tests
2021-03-02 18:46:31 -03:00

218 lines
9.8 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.Collections.Generic;
using System.Linq;
using QuantConnect.Data;
using QuantConnect.Data.UniverseSelection;
using QuantConnect.Interfaces;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// We add an option contract using <see cref="QCAlgorithm.AddOptionContract"/> and place a trade, the underlying
/// gets deselected from the universe selection but should still be present since we manually added the option contract.
/// Later we call <see cref="QCAlgorithm.RemoveOptionContract"/> and expect both option and underlying to be removed.
/// </summary>
public class AddOptionContractFromUniverseRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private DateTime _expiration = new DateTime(2014, 06, 21);
private SecurityChanges _securityChanges = SecurityChanges.None;
private Symbol _option;
private Symbol _aapl;
private Symbol _twx;
private bool _traded;
public override void Initialize()
{
_twx = QuantConnect.Symbol.Create("TWX", SecurityType.Equity, Market.USA);
_aapl = QuantConnect.Symbol.Create("AAPL", SecurityType.Equity, Market.USA);
UniverseSettings.Resolution = Resolution.Minute;
UniverseSettings.DataNormalizationMode = DataNormalizationMode.Raw;
SetStartDate(2014, 06, 05);
SetEndDate(2014, 06, 09);
AddUniverse(enumerable => new[] { Time.Date <= new DateTime(2014, 6, 5) ? _twx : _aapl },
enumerable => new[] { Time.Date <= new DateTime(2014, 6, 5) ? _twx : _aapl });
}
public override void OnData(Slice data)
{
if (_option != null && Securities[_option].Price != 0 && !_traded)
{
_traded = true;
Buy(_option, 1);
}
if (Time.Date > new DateTime(2014, 6, 5))
{
if (Time < new DateTime(2014, 6, 6, 14, 0, 0))
{
var configs = SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(_twx);
// assert underlying still there after the universe selection removed it, still used by the manually added option contract
if (!configs.Any())
{
throw new Exception($"Was expecting configurations for {_twx}" +
$" even after it has been deselected from coarse universe because we still have the option contract.");
}
}
else if (Time == new DateTime(2014, 6, 6, 14, 0, 0))
{
// liquidate & remove the option
RemoveOptionContract(_option);
}
// assert underlying was finally removed
else if(Time > new DateTime(2014, 6, 6, 14, 0, 0))
{
foreach (var symbol in new[] { _option, _option.Underlying })
{
var configs = SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(symbol);
if (configs.Any())
{
throw new Exception($"Unexpected configuration for {symbol} after it has been deselected from coarse universe and option contract is removed.");
}
}
}
}
}
public override void OnSecuritiesChanged(SecurityChanges changes)
{
if (_securityChanges.RemovedSecurities.Intersect(changes.RemovedSecurities).Any())
{
throw new Exception($"SecurityChanges.RemovedSecurities intersect {changes.RemovedSecurities}. We expect no duplicate!");
}
if (_securityChanges.AddedSecurities.Intersect(changes.AddedSecurities).Any())
{
throw new Exception($"SecurityChanges.AddedSecurities intersect {changes.RemovedSecurities}. We expect no duplicate!");
}
// keep track of all removed and added securities
_securityChanges += changes;
if (changes.AddedSecurities.Any(security => security.Symbol.SecurityType == SecurityType.Option))
{
return;
}
foreach (var addedSecurity in changes.AddedSecurities)
{
var option = OptionChainProvider.GetOptionContractList(addedSecurity.Symbol, Time)
.OrderBy(symbol => symbol.ID.Symbol)
.First(optionContract => optionContract.ID.Date == _expiration
&& optionContract.ID.OptionRight == OptionRight.Call
&& optionContract.ID.OptionStyle == OptionStyle.American);
AddOptionContract(option);
foreach (var symbol in new[] { option, option.Underlying })
{
var config = SubscriptionManager.SubscriptionDataConfigService.GetSubscriptionDataConfigs(symbol).ToList();
if (!config.Any())
{
throw new Exception($"Was expecting configurations for {symbol}");
}
if (config.Any(dataConfig => dataConfig.DataNormalizationMode != DataNormalizationMode.Raw))
{
throw new Exception($"Was expecting DataNormalizationMode.Raw configurations for {symbol}");
}
}
// just keep the first we got
if (_option == null)
{
_option = option;
}
}
}
public override void OnEndOfAlgorithm()
{
if (SubscriptionManager.Subscriptions.Any(dataConfig => dataConfig.Symbol == _twx || dataConfig.Symbol.Underlying == _twx))
{
throw new Exception($"Was NOT expecting any configurations for {_twx} or it's options, since we removed the contract");
}
if (SubscriptionManager.Subscriptions.All(dataConfig => dataConfig.Symbol != _aapl))
{
throw new Exception($"Was expecting configurations for {_aapl}");
}
if (SubscriptionManager.Subscriptions.All(dataConfig => dataConfig.Symbol.Underlying != _aapl))
{
throw new Exception($"Was expecting options configurations for {_aapl}");
}
}
/// <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, Language.Python };
/// <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", "-0.23%"},
{"Compounding Annual Return", "-15.596%"},
{"Drawdown", "0.200%"},
{"Expectancy", "-1"},
{"Net Profit", "-0.232%"},
{"Sharpe Ratio", "-7.739"},
{"Probabilistic Sharpe Ratio", "1.216%"},
{"Loss Rate", "100%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0.027"},
{"Beta", "-0.174"},
{"Annual Standard Deviation", "0.006"},
{"Annual Variance", "0"},
{"Information Ratio", "-11.586"},
{"Tracking Error", "0.042"},
{"Treynor Ratio", "0.286"},
{"Total Fees", "$2.00"},
{"Estimated Strategy Capacity", "$1400000.00"},
{"Fitness Score", "0"},
{"Kelly Criterion Estimate", "0"},
{"Kelly Criterion Probability Value", "0"},
{"Sortino Ratio", "-19.883"},
{"Return Over Maximum Drawdown", "-67.224"},
{"Portfolio Turnover", "0.014"},
{"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", "ae0b430e9c728966e3736fb352a689c6"}
};
}
}