Files
quantconnect--lean/Algorithm.CSharp/LongOnlyAlphaStreamAlgorithm.cs
Martin Molinero 6ad123ad8c Update regression algorithms stats
- Update regression algorithms stats after making SecurityCache ignore
  QuoteBars for equity for OHCL values and GetLastData(). They were
  affected since the `BenchmarkSecurity` used `.Price` which was QB for
  equities. Order list hashes changed because SubmissionLastPrice will
  now be TB instead of QB
2020-04-08 19:31:42 -03:00

144 lines
5.7 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 QuantConnect.Algorithm.Framework.Alphas;
using QuantConnect.Algorithm.Framework.Execution;
using QuantConnect.Algorithm.Framework.Portfolio;
using QuantConnect.Algorithm.Framework.Selection;
using QuantConnect.Brokerages;
using QuantConnect.Data;
using QuantConnect.Interfaces;
using QuantConnect.Orders;
using System;
using System.Collections.Generic;
using System.Linq;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Basic template framework algorithm uses framework components to define the algorithm.
/// Shows EqualWeightingPortfolioConstructionModel.LongOnly() application
/// </summary>
/// <meta name="tag" content="alpha streams" />
/// <meta name="tag" content="using quantconnect" />
/// <meta name="tag" content="algorithm framework" />
public class LongOnlyAlphaStreamAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
public override void Initialize()
{
// 1. Required:
SetStartDate(2013, 10, 07);
SetEndDate(2013, 10, 11);
// 2. Required: Alpha Streams Models:
SetBrokerageModel(BrokerageName.AlphaStreams);
// 3. Required: Significant AUM Capacity
SetCash(1000000);
// Only SPY will be traded
SetPortfolioConstruction(new EqualWeightingPortfolioConstructionModel(Resolution.Daily, PortfolioBias.Long));
SetExecution(new ImmediateExecutionModel());
// set algorithm framework models
SetUniverseSelection(
new ManualUniverseSelectionModel(
new[] {"SPY", "IBM"}
.Select(x => QuantConnect.Symbol.Create(x, SecurityType.Equity, Market.USA))
)
);
}
public override void OnData(Slice slice)
{
if (Portfolio.Invested) return;
EmitInsights(
Insight.Price("SPY", TimeSpan.FromDays(1), InsightDirection.Up),
Insight.Price("IBM", TimeSpan.FromDays(1), InsightDirection.Down)
);
}
public override void OnOrderEvent(OrderEvent orderEvent)
{
if (orderEvent.Status.IsFill())
{
if (Securities[orderEvent.Symbol].Holdings.IsShort)
{
throw new Exception("Invalid position, should not be short");
}
Debug($"Purchased Stock: {orderEvent}");
}
}
/// <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", "9"},
{"Average Win", "0.99%"},
{"Average Loss", "-0.60%"},
{"Compounding Annual Return", "211.299%"},
{"Drawdown", "2.300%"},
{"Expectancy", "0.319"},
{"Net Profit", "1.462%"},
{"Sharpe Ratio", "7.178"},
{"Probabilistic Sharpe Ratio", "64.689%"},
{"Loss Rate", "50%"},
{"Win Rate", "50%"},
{"Profit-Loss Ratio", "1.64"},
{"Alpha", "-0.35"},
{"Beta", "1.003"},
{"Annual Standard Deviation", "0.22"},
{"Annual Variance", "0.049"},
{"Information Ratio", "-97.49"},
{"Tracking Error", "0.004"},
{"Treynor Ratio", "1.577"},
{"Total Fees", "$293.06"},
{"Fitness Score", "0.999"},
{"Kelly Criterion Estimate", "-6.994"},
{"Kelly Criterion Probability Value", "0.593"},
{"Sortino Ratio", "79228162514264337593543950335"},
{"Return Over Maximum Drawdown", "68.908"},
{"Portfolio Turnover", "1.741"},
{"Total Insights Generated", "10"},
{"Total Insights Closed", "8"},
{"Total Insights Analysis Completed", "8"},
{"Long Insight Count", "5"},
{"Short Insight Count", "5"},
{"Long/Short Ratio", "100%"},
{"Estimated Monthly Alpha Value", "$76052.4902"},
{"Total Accumulated Estimated Alpha Value", "$12252.9012"},
{"Mean Population Estimated Insight Value", "$1531.6126"},
{"Mean Population Direction", "62.5%"},
{"Mean Population Magnitude", "0%"},
{"Rolling Averaged Population Direction", "73.0394%"},
{"Rolling Averaged Population Magnitude", "0%"},
{"OrderListHash", "2007597727"}
};
}
}