wehub-resource-sync
119 lines
4.6 KiB
C#
119 lines
4.6 KiB
C#
/*
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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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using System.Collections.Generic;
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using QuantConnect.Interfaces;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Rebalances between SPY and BND. Tests capacity of the weakest link, which in this
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/// case is BND, dragging down the capacity estimate.
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/// </summary>
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public class SpyBondPortfolioRebalance : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Symbol _spy;
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public override void Initialize()
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{
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SetStartDate(2020, 1, 1);
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SetEndDate(2020, 3, 31);
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SetCash(10000);
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_spy = AddEquity("SPY", Resolution.Hour).Symbol;
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var bnd = AddEquity("BND", Resolution.Hour).Symbol;
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Schedule.On(DateRules.EveryDay(_spy), TimeRules.AfterMarketOpen(_spy, 1, false), () =>
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{
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SetHoldings(_spy, 0.5m);
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SetHoldings(bnd, 0.5m);
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});
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}
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/// <summary>
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/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
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/// </summary>
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public bool CanRunLocally { get; } = false;
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/// <summary>
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/// This is used by the regression test system to indicate which languages this algorithm is written in.
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/// </summary>
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public List<Language> Languages { get; } = new() { Language.CSharp };
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/// <summary>
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/// Data Points count of all timeslices of algorithm
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/// </summary>
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public long DataPoints => 0;
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/// </summary>
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/// Data Points count of the algorithm history
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/// </summary>
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public int AlgorithmHistoryDataPoints => 0;
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/// <summary>
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/// Final status of the algorithm
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/// </summary>
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public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
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/// <summary>
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/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
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/// </summary>
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public Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Orders", "21"},
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{"Average Win", "0.02%"},
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{"Average Loss", "-0.03%"},
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{"Compounding Annual Return", "-33.564%"},
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{"Drawdown", "19.700%"},
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{"Expectancy", "-0.140"},
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{"Net Profit", "-9.655%"},
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{"Sharpe Ratio", "-0.99"},
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{"Probabilistic Sharpe Ratio", "13.754%"},
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{"Loss Rate", "50%"},
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{"Win Rate", "50%"},
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{"Profit-Loss Ratio", "0.72"},
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{"Alpha", "-0.022"},
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{"Beta", "0.538"},
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{"Annual Standard Deviation", "0.309"},
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{"Annual Variance", "0.096"},
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{"Information Ratio", "0.826"},
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{"Tracking Error", "0.269"},
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{"Treynor Ratio", "-0.569"},
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{"Total Fees", "$21.00"},
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{"Estimated Strategy Capacity", "$1100000.00"},
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{"Fitness Score", "0.005"},
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{"Kelly Criterion Estimate", "0"},
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{"Kelly Criterion Probability Value", "0"},
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{"Sortino Ratio", "-1.524"},
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{"Return Over Maximum Drawdown", "-1.688"},
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{"Portfolio Turnover", "0.02"},
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{"Total Insights Generated", "0"},
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{"Total Insights Closed", "0"},
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{"Total Insights Analysis Completed", "0"},
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{"Long Insight Count", "0"},
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{"Short Insight Count", "0"},
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{"Long/Short Ratio", "100%"},
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{"Estimated Monthly Alpha Value", "$0"},
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{"Total Accumulated Estimated Alpha Value", "$0"},
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{"Mean Population Estimated Insight Value", "$0"},
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{"Mean Population Direction", "0%"},
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{"Mean Population Magnitude", "0%"},
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{"Rolling Averaged Population Direction", "0%"},
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{"Rolling Averaged Population Magnitude", "0%"},
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{"OrderListHash", "95a130426900aaf227a08a5d1c617b2b"}
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};
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}
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}
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