Convert AlphaStreamsPortfolio to data source
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Martin-Molinero
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/*
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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;
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using QuantConnect.Data;
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using QuantConnect.Util;
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using QuantConnect.Orders;
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using QuantConnect.Interfaces;
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using System.Collections.Generic;
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using System.Linq;
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using QuantConnect.Data.UniverseSelection;
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using QuantConnect.Data.Custom.AlphaStreams;
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using QuantConnect.Algorithm.Framework.Alphas;
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using QuantConnect.Algorithm.Framework.Execution;
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using QuantConnect.Algorithm.Framework.Portfolio;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Example algorithm consuming an alpha streams portfolio state and trading based on it
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/// </summary>
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public class AlphaStreamsBasicTemplateAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private List<Symbol> _currentSymbols;
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/// <summary>
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/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
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/// </summary>
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public override void Initialize()
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{
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SetStartDate(2018, 04, 04);
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SetEndDate(2018, 04, 06);
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_currentSymbols = new List<Symbol>();
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SetExecution(new ImmediateExecutionModel());
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Settings.MinimumOrderMarginPortfolioPercentage = 0.01m;
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SetPortfolioConstruction(new SecurityTargetPortfolioConstructionModel());
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var alpha = AddData<AlphaStreamsPortfolioState>("623b06b231eb1cc1aa3643a46");
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}
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/// <summary>
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/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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/// </summary>
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/// <param name="data">Slice object keyed by symbol containing the stock data</param>
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public override void OnData(Slice data)
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{
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if (data.ContainsKey("623b06b231eb1cc1aa3643a46"))
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{
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var portfolioState = (AlphaStreamsPortfolioState)data["623b06b231eb1cc1aa3643a46"];
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var newSymbols = new List<Symbol>();
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if (!portfolioState.PositionGroups.IsNullOrEmpty())
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{
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var portfolioValueFactor = Portfolio.TotalPortfolioValue / portfolioState.TotalPortfolioValue * 1;
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foreach (var positionGroup in portfolioState.PositionGroups)
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{
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foreach (var position in positionGroup.Positions)
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{
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var security = AddSecurity(position.Symbol, Resolution.Minute);
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security.Holdings.Target = new PortfolioTarget(position.Symbol, position.Quantity * portfolioValueFactor);
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newSymbols.Add(position.Symbol);
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_currentSymbols.Remove(position.Symbol);
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}
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}
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}
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foreach (var symbol in _currentSymbols)
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{
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Securities[symbol].Holdings.Target = null;
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Liquidate(symbol);
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RemoveSecurity(symbol);
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}
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_currentSymbols = newSymbols;
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}
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}
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public override void OnOrderEvent(OrderEvent orderEvent)
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{
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Debug($"OnOrderEvent: {orderEvent}");
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}
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public override void OnEndOfAlgorithm()
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{
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if (Portfolio.Invested)
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{
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throw new Exception("Should not be invested at end of algorithm");
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}
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}
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private class SecurityTargetPortfolioConstructionModel : IPortfolioConstructionModel
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{
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public IEnumerable<IPortfolioTarget> CreateTargets(QCAlgorithm algorithm, Insight[] insights)
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{
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foreach (var symbol in algorithm.Securities.Keys.Where(symbol => symbol.SecurityType == SecurityType.Base))
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{
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if (algorithm.CurrentSlice.ContainsKey(symbol))
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{
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var portfolioState = (AlphaStreamsPortfolioState)algorithm.CurrentSlice["623b06b231eb1cc1aa3643a46"];
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}
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}
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foreach (var security in algorithm.Securities.Values)
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{
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if (security.Holdings.Target != null && security.Holdings.Target.Quantity != security.Holdings.Quantity)
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{
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yield return security.Holdings.Target;
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}
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}
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}
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public void OnSecuritiesChanged(QCAlgorithm algorithm, SecurityChanges changes)
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{
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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; } = true;
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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 Language[] Languages { get; } = { Language.CSharp };
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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 Trades", "2"},
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{"Average Win", "0%"},
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{"Average Loss", "-0.23%"},
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{"Compounding Annual Return", "-27.348%"},
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{"Drawdown", "0.300%"},
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{"Expectancy", "-1"},
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{"Net Profit", "-0.233%"},
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{"Sharpe Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "0%"},
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{"Loss Rate", "100%"},
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{"Win Rate", "0%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "0"},
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{"Beta", "0"},
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{"Annual Standard Deviation", "0"},
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{"Annual Variance", "0"},
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{"Information Ratio", "2.474"},
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{"Tracking Error", "0.339"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$0.00"},
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{"Estimated Strategy Capacity", "$83000.00"},
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{"Lowest Capacity Asset", "BTCUSD XJ"},
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{"Fitness Score", "0.034"},
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{"Kelly Criterion Estimate", "0"},
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{"Kelly Criterion Probability Value", "0"},
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{"Sortino Ratio", "79228162514264337593543950335"},
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{"Return Over Maximum Drawdown", "-127.431"},
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{"Portfolio Turnover", "0.069"},
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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", "d10390e3426c62b1dc637b7b893e34b6"}
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};
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}
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}
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