Files
quantconnect--lean/Algorithm.CSharp/BasicTemplateAtreyuAlgorithm.cs
T
Martin-Molinero 5ebf451fb3
Build & Test Lean / build (push) Has been cancelled
Regression Tests / build (push) Has been cancelled
Fix for python SetHoldings precision loss (#5879)
- After https://github.com/QuantConnect/Lean/pull/5872 trading API
  changes numpy float64 was not converted correctly by pythonNet and
  used an int. Reverting API changes and adding regression test. This
  should be fixed at pythonNet layer
2021-08-25 15:25:39 -03:00

131 lines
5.6 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.Data;
using QuantConnect.Orders;
using QuantConnect.Interfaces;
using QuantConnect.Brokerages;
using System.Collections.Generic;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Basic template algorithm for the Atreyu brokerage
/// </summary>
/// <meta name="tag" content="using data" />
/// <meta name="tag" content="using quantconnect" />
/// <meta name="tag" content="trading and orders" />
public class BasicTemplateAtreyuAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
/// <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, 07);
SetEndDate(2013, 10, 11);
SetCash(100000);
SetBrokerageModel(BrokerageName.Atreyu);
AddEquity("SPY", Resolution.Minute);
DefaultOrderProperties = new AtreyuOrderProperties
{
// Can specify the default exchange to execute an order on.
// If not specified will default to the primary exchange
Exchange = Exchange.NASDAQ,
// Currently only support order for the day
TimeInForce = TimeInForce.Day
};
}
/// <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)
{
// will set 25% of our buying power with a market order that will be routed to exchange set in the default order properties (NASDAQ)
SetHoldings("SPY", 0.25m);
// will increase our SPY holdings to 50% of our buying power with a market order that will be routed to ARCA
SetHoldings("SPY", 0.50m, orderProperties: new AtreyuOrderProperties { Exchange = Exchange.ARCA });
Debug("Purchased SPY!");
}
}
/// <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", "2"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "93.443%"},
{"Drawdown", "1.100%"},
{"Expectancy", "0"},
{"Net Profit", "0.847%"},
{"Sharpe Ratio", "6.515"},
{"Probabilistic Sharpe Ratio", "67.535%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0"},
{"Beta", "0"},
{"Annual Standard Deviation", "0.11"},
{"Annual Variance", "0.012"},
{"Information Ratio", "6.515"},
{"Tracking Error", "0.11"},
{"Treynor Ratio", "0"},
{"Total Fees", "$0.52"},
{"Estimated Strategy Capacity", "$8600000.00"},
{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
{"Fitness Score", "0.124"},
{"Kelly Criterion Estimate", "0"},
{"Kelly Criterion Probability Value", "0"},
{"Sortino Ratio", "79228162514264337593543950335"},
{"Return Over Maximum Drawdown", "78.376"},
{"Portfolio Turnover", "0.124"},
{"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", "cb542eaaeab5eac3bcae5d915ded30da"}
};
}
}