9690acfd25
Keeps the original overloads in the comments.
172 lines
7.2 KiB
C#
172 lines
7.2 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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*/
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using System;
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using System.Collections.Generic;
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using System.Linq;
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using QuantConnect.Data;
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using QuantConnect.Interfaces;
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using QuantConnect.Securities;
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using QuantConnect.Securities.Future;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// This example demonstrates how to add futures for a given underlying asset.
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/// It also shows how you can prefilter contracts easily based on expirations, and how you
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/// can inspect the futures chain to pick a specific contract to trade.
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/// </summary>
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/// <meta name="tag" content="using data" />
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/// <meta name="tag" content="benchmarks" />
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/// <meta name="tag" content="futures" />
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public class BasicTemplateFuturesAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Symbol _contractSymbol;
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// S&P 500 EMini futures
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private const string RootSP500 = Futures.Indices.SP500EMini;
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public Symbol SP500 = QuantConnect.Symbol.Create(RootSP500, SecurityType.Future, Market.USA);
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// Gold futures
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private const string RootGold = Futures.Metals.Gold;
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public Symbol Gold = QuantConnect.Symbol.Create(RootGold, SecurityType.Future, Market.USA);
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/// <summary>
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/// Initialize your algorithm and add desired assets.
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/// </summary>
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public override void Initialize()
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{
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SetStartDate(2013, 10, 08);
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SetEndDate(2013, 10, 10);
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SetCash(1000000);
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var futureSP500 = AddFuture(RootSP500);
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var futureGold = AddFuture(RootGold);
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// set our expiry filter for this futures chain
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// SetFilter method accepts TimeSpan objects or integer for days.
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// The following statements yeild the same filtering criteria
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futureSP500.SetFilter(TimeSpan.Zero, TimeSpan.FromDays(182));
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futureGold.SetFilter(0, 182);
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var benchmark = AddEquity("SPY");
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SetBenchmark(benchmark.Symbol);
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}
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/// <summary>
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/// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event
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/// </summary>
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/// <param name="slice">The current slice of data keyed by symbol string</param>
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public override void OnData(Slice slice)
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{
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if (!Portfolio.Invested)
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{
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foreach(var chain in slice.FutureChains)
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{
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// find the front contract expiring no earlier than in 90 days
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var contract = (
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from futuresContract in chain.Value.OrderBy(x => x.Expiry)
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where futuresContract.Expiry > Time.Date.AddDays(90)
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select futuresContract
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).FirstOrDefault();
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// if found, trade it
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if (contract != null)
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{
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_contractSymbol = contract.Symbol;
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MarketOrder(_contractSymbol, 1);
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}
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}
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}
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else
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{
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Liquidate();
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}
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}
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public override void OnEndOfAlgorithm()
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{
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// Get the margin requirements
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var buyingPowerModel = Securities[_contractSymbol].BuyingPowerModel;
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var futureMarginModel = buyingPowerModel as FutureMarginModel;
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if (buyingPowerModel == null)
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{
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throw new Exception($"Invalid buying power model. Found: {buyingPowerModel.GetType().Name}. Expected: {nameof(FutureMarginModel)}");
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}
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var initialOvernight = futureMarginModel.InitialOvernightMarginRequirement;
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var maintenanceOvernight = futureMarginModel.MaintenanceOvernightMarginRequirement;
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var initialIntraday = futureMarginModel.InitialIntradayMarginRequirement;
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var maintenanceIntraday = futureMarginModel.MaintenanceIntradayMarginRequirement;
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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, Language.Python };
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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", "8220"},
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{"Average Win", "0.00%"},
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{"Average Loss", "0.00%"},
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{"Compounding Annual Return", "-100.000%"},
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{"Drawdown", "13.500%"},
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{"Expectancy", "-0.818"},
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{"Net Profit", "-13.517%"},
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{"Sharpe Ratio", "-23.826"},
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{"Probabilistic Sharpe Ratio", "0%"},
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{"Loss Rate", "89%"},
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{"Win Rate", "11%"},
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{"Profit-Loss Ratio", "0.69"},
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{"Alpha", "-7.042"},
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{"Beta", "-0.992"},
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{"Annual Standard Deviation", "0.373"},
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{"Annual Variance", "0.139"},
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{"Information Ratio", "-21.379"},
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{"Tracking Error", "0.503"},
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{"Treynor Ratio", "8.964"},
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{"Total Fees", "$15207.00"},
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{"Fitness Score", "0.033"},
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{"Kelly Criterion Estimate", "-36.472"},
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{"Kelly Criterion Probability Value", "0.82"},
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{"Sortino Ratio", "-8.62"},
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{"Return Over Maximum Drawdown", "-7.81"},
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{"Portfolio Turnover", "302.321"},
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{"Total Insights Generated", "8220"},
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{"Total Insights Closed", "8218"},
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{"Total Insights Analysis Completed", "8218"},
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{"Long Insight Count", "4110"},
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{"Short Insight Count", "0"},
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{"Long/Short Ratio", "100%"},
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{"Estimated Monthly Alpha Value", "$79.81579"},
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{"Total Accumulated Estimated Alpha Value", "$8.425"},
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{"Mean Population Estimated Insight Value", "$0.001025189"},
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{"Mean Population Direction", "38.7618%"},
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{"Mean Population Magnitude", "0%"},
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{"Rolling Averaged Population Direction", "34.5315%"},
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{"Rolling Averaged Population Magnitude", "0%"}
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};
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}
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}
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