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chore: import upstream snapshot with attribution

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Algorithm.CSharp/SingleOptionPositionGroupBuyingPowerModelRegressionAlgorithm.cs
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/*
* 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;
using QuantConnect.Securities;
using QuantConnect.Securities.Positions;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Regression algorithm asserting that for single-asset position groups, the buying power models
/// (<see cref="PositionGroupBuyingPowerModel"/>, <see cref="SecurityPositionGroupBuyingPowerModel"/>, and <see cref="BuyingPowerModel"/>)
/// compute the same quantity for a given delta buying power.
/// </summary>
public class SingleOptionPositionGroupBuyingPowerModelRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private Symbol _optionSymbol;
public override void Initialize()
{
SetStartDate(2015, 12, 23);
SetEndDate(2015, 12, 30);
SetCash(1000000);
var equitySymbol = AddEquity("GOOG").Symbol;
var option = AddOption(equitySymbol);
_optionSymbol = option.Symbol;
option.SetFilter(u => u.StandardsOnly().Strikes(-2, +2).Expiration(0, 180));
}
public override void OnData(Slice slice)
{
if (Portfolio.Invested || !slice.OptionChains.TryGetValue(_optionSymbol, out var chain))
{
return;
}
var callContracts = chain.Where(contract => contract.Right == OptionRight.Call)
.GroupBy(x => x.Expiry)
.OrderBy(grouping => grouping.Key)
.First()
.OrderByDescending(x => x.Strike)
.ToList();
var contractSymbol = callContracts[0].Symbol;
// 1. Test starting from a long position
var quantity = 10;
MarketOrder(contractSymbol, quantity);
var security = Securities[contractSymbol];
var positionGroup = Portfolio.Positions.Groups.Single();
TestQuantityForDeltaBuyingPowerForPositionGroup(positionGroup, security);
// 2. Test starting from a short position
quantity = -10;
MarketOrder(contractSymbol, quantity - positionGroup.Quantity);
positionGroup = Portfolio.Positions.Groups.Single();
if (positionGroup.Positions.Single().Quantity != quantity)
{
throw new RegressionTestException($@"Expected position group quantity to be {quantity} but was {positionGroup.Quantity}");
}
TestQuantityForDeltaBuyingPowerForPositionGroup(positionGroup, security);
}
private void TestQuantityForDeltaBuyingPowerForPositionGroup(IPositionGroup positionGroup, Security security)
{
var absQuantity = Math.Abs(positionGroup.Quantity);
var initialMarginPerUnit = positionGroup.BuyingPowerModel.GetInitialMarginRequirement(Portfolio, positionGroup) / absQuantity;
for (var expectedQuantity = 1; expectedQuantity <= absQuantity; expectedQuantity++)
{
// Test going in the same direction (longer or shorter):
// positive delta and expected quantity, to increment the position towards the current side
var deltaBuyingPower = initialMarginPerUnit * expectedQuantity * 1.05m;
// Adjust the delta buying power:
// GetMaximumLotsForDeltaBuyingPower will add the delta buying power to the maintenance margin and used that as a target margin,
// but then GetMaximumLotsForTargetBuyingPower will work with initial margin requirement so we make sure the resulting quantity
// can be ordered. In order to match this, we need to adjust the delta buying power by the difference between the initial margin
// requirement and maintenance margin.
PerfomQuantityCalculations(positionGroup, security, expectedQuantity, deltaBuyingPower, increasing: true);
// Test going towards the opposite side until liquidated:
// negative delta and expected quantity to reduce the position
deltaBuyingPower = -initialMarginPerUnit * expectedQuantity * 0.95m;
PerfomQuantityCalculations(positionGroup, security, -expectedQuantity, deltaBuyingPower, increasing: false);
}
}
private void PerfomQuantityCalculations(IPositionGroup positionGroup, Security security, int expectedQuantity,
decimal deltaBuyingPower, bool increasing)
{
var absQuantity = Math.Abs(positionGroup.Quantity);
var initialMarginPerUnit = positionGroup.BuyingPowerModel.GetInitialMarginRequirement(Portfolio, positionGroup) / absQuantity;
var maintenanceMarginPerUnit = positionGroup.BuyingPowerModel.GetMaintenanceMargin(Portfolio, positionGroup) / absQuantity;
var deltaBuyingPowerAdjustment = (initialMarginPerUnit - maintenanceMarginPerUnit) * absQuantity;
var positionQuantityForDeltaWithPositionGroupBuyingPowerModel = positionGroup.BuyingPowerModel
.GetMaximumLotsForDeltaBuyingPower(new GetMaximumLotsForDeltaBuyingPowerParameters(Portfolio, positionGroup,
deltaBuyingPower + deltaBuyingPowerAdjustment, minimumOrderMarginPortfolioPercentage: 0)).NumberOfLots;
Debug($"Expected quantity: {expectedQuantity} -- Actual: {positionQuantityForDeltaWithPositionGroupBuyingPowerModel}");
if (positionQuantityForDeltaWithPositionGroupBuyingPowerModel != expectedQuantity)
{
throw new RegressionTestException($@"Expected position quantity for delta buying power to be {expectedQuantity} but was {positionQuantityForDeltaWithPositionGroupBuyingPowerModel}");
}
var position = positionGroup.Positions.Single();
var sign = (increasing ? +1 : -1) * Math.Sign(position.Quantity);
var signedDeltaBuyingPower = sign * Math.Abs(deltaBuyingPower);
var positionQuantityForDeltaWithSecurityPositionGroupBuyingPowerModel = new SecurityPositionGroupBuyingPowerModel()
.GetMaximumLotsForDeltaBuyingPower(new GetMaximumLotsForDeltaBuyingPowerParameters(Portfolio, positionGroup,
signedDeltaBuyingPower + deltaBuyingPowerAdjustment, minimumOrderMarginPortfolioPercentage: 0)).NumberOfLots;
var positionQuantityForDeltaWithSecurityBuyingPowerModel = security.BuyingPowerModel.GetMaximumOrderQuantityForDeltaBuyingPower(
new GetMaximumOrderQuantityForDeltaBuyingPowerParameters(Portfolio, security, signedDeltaBuyingPower + deltaBuyingPowerAdjustment,
minimumOrderMarginPortfolioPercentage: 0)).Quantity;
var expectedSingleSecurityModelsQuantity = sign * Math.Abs(expectedQuantity);
if (positionQuantityForDeltaWithSecurityPositionGroupBuyingPowerModel != expectedSingleSecurityModelsQuantity ||
positionQuantityForDeltaWithSecurityBuyingPowerModel != expectedSingleSecurityModelsQuantity)
{
throw new RegressionTestException($@"Expected order quantity for delta buying power calls from default buying power models to return {expectedSingleSecurityModelsQuantity}. Results were:" +
$" \nSecurityPositionGroupBuyingPowerModel: {positionQuantityForDeltaWithSecurityPositionGroupBuyingPowerModel}" +
$" \nBuyingPowerModel: {positionQuantityForDeltaWithSecurityBuyingPowerModel}\n");
}
}
/// <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 List<Language> Languages { get; } = new() { Language.CSharp };
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 47108;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 0;
/// <summary>
/// Final status of the algorithm
/// </summary>
public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
/// <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 Orders", "2"},
{"Average Win", "0%"},
{"Average Loss", "-0.11%"},
{"Compounding Annual Return", "-2.788%"},
{"Drawdown", "0.300%"},
{"Expectancy", "-1"},
{"Start Equity", "1000000"},
{"End Equity", "999380.5"},
{"Net Profit", "-0.062%"},
{"Sharpe Ratio", "-8.624"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "0%"},
{"Loss Rate", "100%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "-0.032"},
{"Beta", "0.007"},
{"Annual Standard Deviation", "0.004"},
{"Annual Variance", "0"},
{"Information Ratio", "-0.051"},
{"Tracking Error", "0.084"},
{"Treynor Ratio", "-4.737"},
{"Total Fees", "$19.50"},
{"Estimated Strategy Capacity", "$47000.00"},
{"Lowest Capacity Asset", "GOOCV W78ZFMML4BUU|GOOCV VP83T1ZUHROL"},
{"Portfolio Turnover", "0.45%"},
{"Drawdown Recovery", "0"},
{"OrderListHash", "8b8bafd11c0c2a868dbbc28db36d4ce0"}
};
}
}