Files
quantconnect--lean/Algorithm.CSharp/BasicTemplateFuturesAlgorithm.cs
T

173 lines
7.2 KiB
C#

/*
* 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.Future;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// This example demonstrates how to add futures for a given underlying asset.
/// It also shows how you can prefilter contracts easily based on expirations, and how you
/// can inspect the futures chain to pick a specific contract to trade.
/// </summary>
/// <meta name="tag" content="using data" />
/// <meta name="tag" content="benchmarks" />
/// <meta name="tag" content="futures" />
public class BasicTemplateFuturesAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private Symbol _contractSymbol;
// S&P 500 EMini futures
private const string RootSP500 = Futures.Indices.SP500EMini;
public Symbol SP500 = QuantConnect.Symbol.Create(RootSP500, SecurityType.Future, Market.USA);
// Gold futures
private const string RootGold = Futures.Metals.Gold;
public Symbol Gold = QuantConnect.Symbol.Create(RootGold, SecurityType.Future, Market.USA);
/// <summary>
/// Initialize your algorithm and add desired assets.
/// </summary>
public override void Initialize()
{
SetStartDate(2013, 10, 08);
SetEndDate(2013, 10, 10);
SetCash(1000000);
var futureSP500 = AddFuture(RootSP500);
var futureGold = AddFuture(RootGold);
// set our expiry filter for this futures chain
// SetFilter method accepts TimeSpan objects or integer for days.
// The following statements yield the same filtering criteria
futureSP500.SetFilter(TimeSpan.Zero, TimeSpan.FromDays(182));
futureGold.SetFilter(0, 182);
var benchmark = AddEquity("SPY");
SetBenchmark(benchmark.Symbol);
}
/// <summary>
/// Event - v3.0 DATA EVENT HANDLER: (Pattern) Basic template for user to override for receiving all subscription data in a single event
/// </summary>
/// <param name="slice">The current slice of data keyed by symbol string</param>
public override void OnData(Slice slice)
{
if (!Portfolio.Invested)
{
foreach(var chain in slice.FutureChains)
{
// find the front contract expiring no earlier than in 90 days
var contract = (
from futuresContract in chain.Value.OrderBy(x => x.Expiry)
where futuresContract.Expiry > Time.Date.AddDays(90)
select futuresContract
).FirstOrDefault();
// if found, trade it
if (contract != null)
{
_contractSymbol = contract.Symbol;
MarketOrder(_contractSymbol, 1);
}
}
}
else
{
Liquidate();
}
}
public override void OnEndOfAlgorithm()
{
// Get the margin requirements
var buyingPowerModel = Securities[_contractSymbol].BuyingPowerModel;
var futureMarginModel = buyingPowerModel as FutureMarginModel;
if (buyingPowerModel == null)
{
throw new Exception($"Invalid buying power model. Found: {buyingPowerModel.GetType().Name}. Expected: {nameof(FutureMarginModel)}");
}
var initialOvernight = futureMarginModel.InitialOvernightMarginRequirement;
var maintenanceOvernight = futureMarginModel.MaintenanceOvernightMarginRequirement;
var initialIntraday = futureMarginModel.InitialIntradayMarginRequirement;
var maintenanceIntraday = futureMarginModel.MaintenanceIntradayMarginRequirement;
}
/// <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 Language[] Languages { get; } = { Language.CSharp, Language.Python };
/// <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 Trades", "8220"},
{"Average Win", "0.00%"},
{"Average Loss", "0.00%"},
{"Compounding Annual Return", "-100.000%"},
{"Drawdown", "13.500%"},
{"Expectancy", "-0.818"},
{"Net Profit", "-13.517%"},
{"Sharpe Ratio", "-23.826"},
{"Probabilistic Sharpe Ratio", "0%"},
{"Loss Rate", "89%"},
{"Win Rate", "11%"},
{"Profit-Loss Ratio", "0.69"},
{"Alpha", "-7.042"},
{"Beta", "-0.992"},
{"Annual Standard Deviation", "0.373"},
{"Annual Variance", "0.139"},
{"Information Ratio", "-21.379"},
{"Tracking Error", "0.503"},
{"Treynor Ratio", "8.964"},
{"Total Fees", "$15207.00"},
{"Fitness Score", "0.033"},
{"Kelly Criterion Estimate", "-36.472"},
{"Kelly Criterion Probability Value", "0.82"},
{"Sortino Ratio", "-8.62"},
{"Return Over Maximum Drawdown", "-7.81"},
{"Portfolio Turnover", "302.321"},
{"Total Insights Generated", "8220"},
{"Total Insights Closed", "8218"},
{"Total Insights Analysis Completed", "8218"},
{"Long Insight Count", "4110"},
{"Short Insight Count", "0"},
{"Long/Short Ratio", "100%"},
{"Estimated Monthly Alpha Value", "$79.81579"},
{"Total Accumulated Estimated Alpha Value", "$8.425"},
{"Mean Population Estimated Insight Value", "$0.001025189"},
{"Mean Population Direction", "38.7618%"},
{"Mean Population Magnitude", "0%"},
{"Rolling Averaged Population Direction", "34.5315%"},
{"Rolling Averaged Population Magnitude", "0%"},
{"OrderListHash", "1557894762"}
};
}
}