Martin Molinero
114 lines
4.8 KiB
C#
114 lines
4.8 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.Collections.Generic;
|
|
using QuantConnect.Data;
|
|
using QuantConnect.Interfaces;
|
|
|
|
namespace QuantConnect.Algorithm.CSharp
|
|
{
|
|
/// <summary>
|
|
/// Demonstration of requesting daily resolution data for US Equities.
|
|
/// This is a simple regression test algorithm using a skeleton algorithm and requesting daily data.
|
|
/// </summary>
|
|
/// <meta name="tag" content="using data" />
|
|
public class BasicTemplateDailyAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
|
|
{
|
|
private Symbol _spy = QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA);
|
|
|
|
/// <summary>
|
|
/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
|
|
/// </summary>
|
|
public override void Initialize()
|
|
{
|
|
SetStartDate(2013, 10, 08); //Set Start Date
|
|
SetEndDate(2013, 10, 17); //Set End Date
|
|
SetCash(100000); //Set Strategy Cash
|
|
// Find more symbols here: http://quantconnect.com/data
|
|
AddEquity("SPY", Resolution.Daily);
|
|
}
|
|
|
|
/// <summary>
|
|
/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
|
|
/// </summary>
|
|
/// <param name="data">Slice object keyed by symbol containing the stock data</param>
|
|
public override void OnData(Slice data)
|
|
{
|
|
if (!Portfolio.Invested)
|
|
{
|
|
SetHoldings(_spy, 1);
|
|
Debug("Purchased Stock");
|
|
}
|
|
}
|
|
|
|
/// <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", "1"},
|
|
{"Average Win", "0%"},
|
|
{"Average Loss", "0%"},
|
|
{"Compounding Annual Return", "246.000%"},
|
|
{"Drawdown", "1.100%"},
|
|
{"Expectancy", "0"},
|
|
{"Net Profit", "3.459%"},
|
|
{"Sharpe Ratio", "10.11"},
|
|
{"Probabilistic Sharpe Ratio", "83.150%"},
|
|
{"Loss Rate", "0%"},
|
|
{"Win Rate", "0%"},
|
|
{"Profit-Loss Ratio", "0"},
|
|
{"Alpha", "1.935"},
|
|
{"Beta", "-0.119"},
|
|
{"Annual Standard Deviation", "0.16"},
|
|
{"Annual Variance", "0.026"},
|
|
{"Information Ratio", "-4.556"},
|
|
{"Tracking Error", "0.221"},
|
|
{"Treynor Ratio", "-13.568"},
|
|
{"Total Fees", "$3.26"},
|
|
{"Fitness Score", "0.111"},
|
|
{"Kelly Criterion Estimate", "0"},
|
|
{"Kelly Criterion Probability Value", "0"},
|
|
{"Sortino Ratio", "52.533"},
|
|
{"Return Over Maximum Drawdown", "214.75"},
|
|
{"Portfolio Turnover", "0.111"},
|
|
{"Total Insights Generated", "0"},
|
|
{"Total Insights Closed", "0"},
|
|
{"Total Insights Analysis Completed", "0"},
|
|
{"Long Insight Count", "0"},
|
|
{"Short Insight Count", "0"},
|
|
{"Long/Short Ratio", "100%"},
|
|
{"Estimated Monthly Alpha Value", "$0"},
|
|
{"Total Accumulated Estimated Alpha Value", "$0"},
|
|
{"Mean Population Estimated Insight Value", "$0"},
|
|
{"Mean Population Direction", "0%"},
|
|
{"Mean Population Magnitude", "0%"},
|
|
{"Rolling Averaged Population Direction", "0%"},
|
|
{"Rolling Averaged Population Magnitude", "0%"},
|
|
{"OrderListHash", "1268340653"}
|
|
};
|
|
}
|
|
}
|