chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
@@ -0,0 +1,173 @@
|
||||
/*
|
||||
* 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.Algorithm.Framework.Alphas;
|
||||
using QuantConnect.Algorithm.Framework.Execution;
|
||||
using QuantConnect.Algorithm.Framework.Portfolio;
|
||||
using QuantConnect.Algorithm.Framework.Selection;
|
||||
using QuantConnect.Orders;
|
||||
using QuantConnect.Interfaces;
|
||||
using QuantConnect.Securities;
|
||||
|
||||
namespace QuantConnect.Algorithm.CSharp
|
||||
{
|
||||
/// <summary>
|
||||
/// Regression algorithm testing portfolio construction model control over rebalancing,
|
||||
/// specifying a custom rebalance function that returns null in some cases, see GH 4075.
|
||||
/// </summary>
|
||||
public class PortfolioRebalanceOnCustomFuncRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
|
||||
{
|
||||
private DateTime _lastRebalanceTime;
|
||||
|
||||
/// <summary>
|
||||
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
|
||||
/// </summary>
|
||||
public override void Initialize()
|
||||
{
|
||||
UniverseSettings.Resolution = Resolution.Daily;
|
||||
|
||||
// Order margin value has to have a minimum of 0.5% of Portfolio value, allows filtering out small trades and reduce fees.
|
||||
// Commented so regression algorithm is more sensitive
|
||||
//Settings.MinimumOrderMarginPortfolioPercentage = 0.005m;
|
||||
|
||||
SetStartDate(2015, 1, 1);
|
||||
SetEndDate(2018, 1, 1);
|
||||
|
||||
Settings.RebalancePortfolioOnInsightChanges = false;
|
||||
Settings.RebalancePortfolioOnSecurityChanges = false;
|
||||
|
||||
SetUniverseSelection(new CustomUniverseSelectionModel("CustomUniverseSelectionModel",
|
||||
time => new List<string> { "AAPL", "IBM", "FB", "SPY", "AIG", "BAC", "BNO" }
|
||||
));
|
||||
SetAlpha(new ConstantAlphaModel(InsightType.Price, InsightDirection.Up, TimeSpan.FromMinutes(20), 0.025, null));
|
||||
SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel(
|
||||
time =>
|
||||
{
|
||||
// for performance only run rebalance logic once a week
|
||||
if (time.DayOfWeek != DayOfWeek.Monday)
|
||||
{
|
||||
return null;
|
||||
}
|
||||
|
||||
if (_lastRebalanceTime == default(DateTime))
|
||||
{
|
||||
// initial rebalance
|
||||
_lastRebalanceTime = time;
|
||||
return time;
|
||||
}
|
||||
|
||||
var deviation = 0m;
|
||||
var count = Securities.Values.Count(security => security.Invested);
|
||||
if (count > 0)
|
||||
{
|
||||
_lastRebalanceTime = time;
|
||||
var portfolioValuePerSecurity = Portfolio.TotalPortfolioValue / count;
|
||||
foreach (var security in Securities.Values.Where(security => security.Invested))
|
||||
{
|
||||
var reservedBuyingPowerForCurrentPosition = security.BuyingPowerModel.GetReservedBuyingPowerForPosition(
|
||||
new ReservedBuyingPowerForPositionParameters(security)).AbsoluteUsedBuyingPower
|
||||
// see GH issue 4107
|
||||
* security.BuyingPowerModel.GetLeverage(security);
|
||||
// we sum up deviation for each security
|
||||
deviation += (portfolioValuePerSecurity - reservedBuyingPowerForCurrentPosition) / portfolioValuePerSecurity;
|
||||
}
|
||||
|
||||
// if securities are deviated 1.5% from their theoretical share of TotalPortfolioValue we rebalance
|
||||
if (deviation >= 0.015m)
|
||||
{
|
||||
return time;
|
||||
}
|
||||
}
|
||||
return null;
|
||||
}));
|
||||
SetExecution(new ImmediateExecutionModel());
|
||||
}
|
||||
|
||||
public override void OnOrderEvent(OrderEvent orderEvent)
|
||||
{
|
||||
Debug($"{orderEvent}");
|
||||
if (orderEvent.Status == OrderStatus.Submitted)
|
||||
{
|
||||
if (UtcTime - _lastRebalanceTime > TimeSpan.Zero || UtcTime.DayOfWeek != DayOfWeek.Monday)
|
||||
{
|
||||
throw new RegressionTestException($"{UtcTime} {orderEvent.Symbol} {UtcTime - _lastRebalanceTime}");
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
/// <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, Language.Python };
|
||||
|
||||
/// <summary>
|
||||
/// Data Points count of all timeslices of algorithm
|
||||
/// </summary>
|
||||
public long DataPoints => 11379;
|
||||
|
||||
/// <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", "16"},
|
||||
{"Average Win", "0.02%"},
|
||||
{"Average Loss", "0.00%"},
|
||||
{"Compounding Annual Return", "13.451%"},
|
||||
{"Drawdown", "24.500%"},
|
||||
{"Expectancy", "6.478"},
|
||||
{"Start Equity", "100000"},
|
||||
{"End Equity", "145958.59"},
|
||||
{"Net Profit", "45.959%"},
|
||||
{"Sharpe Ratio", "0.697"},
|
||||
{"Sortino Ratio", "0.77"},
|
||||
{"Probabilistic Sharpe Ratio", "24.141%"},
|
||||
{"Loss Rate", "25%"},
|
||||
{"Win Rate", "75%"},
|
||||
{"Profit-Loss Ratio", "8.97"},
|
||||
{"Alpha", "0.01"},
|
||||
{"Beta", "1.1"},
|
||||
{"Annual Standard Deviation", "0.127"},
|
||||
{"Annual Variance", "0.016"},
|
||||
{"Information Ratio", "0.285"},
|
||||
{"Tracking Error", "0.06"},
|
||||
{"Treynor Ratio", "0.081"},
|
||||
{"Total Fees", "$24.50"},
|
||||
{"Estimated Strategy Capacity", "$3600000.00"},
|
||||
{"Lowest Capacity Asset", "BNO UN3IMQ2JU1YD"},
|
||||
{"Portfolio Turnover", "0.10%"},
|
||||
{"Drawdown Recovery", "489"},
|
||||
{"OrderListHash", "47fb0abc2f7af436ed0faeb8eb64eeb3"}
|
||||
};
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user