Files
quantconnect--lean/Algorithm.CSharp/WarmupConversionRatesRegressionAlgorithm.cs
T
Ricardo Andrés Marino Rojas cce8945fe8
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Api Clean up, Documentation and Standarization part two (#7964)
* Add improvements

* Add improvments and unit tests

* Add XML comments

* Nit changes

* Add unit tests for OrderJsonConverter

* Improve unit tests

* Address requested changes

* Fix bugs

* Fix bugs

* Fix bugs and self-review

* Fix bugs

* Address requested changes

* Fix unit test bug

* Fix bugs

* Improve unit tests

* Solve bugs
2024-04-26 13:17:34 -03:00

126 lines
4.9 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 QuantConnect.Brokerages;
using QuantConnect.Data;
using QuantConnect.Interfaces;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// This regression algorithm is a test case for validation of conversion rates during warm up.
/// </summary>
public class WarmupConversionRatesRegressionAlgorithm : 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(2018, 4, 5);
SetEndDate(2018, 4, 5);
SetBrokerageModel(BrokerageName.GDAX, AccountType.Cash);
SetCash(10000);
SetWarmUp(TimeSpan.FromDays(1));
AddCrypto("BTCEUR");
AddCrypto("LTCUSD");
}
/// <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.CashBook["EUR"].ConversionRate == 0
|| Portfolio.CashBook["BTC"].ConversionRate == 0
|| Portfolio.CashBook["LTC"].ConversionRate == 0)
{
Log($"BTCEUR current price: {Securities["BTCEUR"].Price}");
Log($"LTCUSD current price: {Securities["LTCUSD"].Price}");
Log($"EUR conversion rate: {Portfolio.CashBook["EUR"].ConversionRate}");
Log($"BTC conversion rate: {Portfolio.CashBook["BTC"].ConversionRate}");
Log($"LTC conversion rate: {Portfolio.CashBook["LTC"].ConversionRate}");
throw new Exception("Conversion rate is 0");
}
if (IsWarmingUp) return;
if (!Portfolio.Invested)
{
SetHoldings("LTCUSD", 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 };
/// <summary>
/// Data Points count of all timeslices of algorithm
/// </summary>
public long DataPoints => 17277;
/// <summary>
/// Data Points count of the algorithm history
/// </summary>
public int AlgorithmHistoryDataPoints => 180;
/// <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 Orders", "1"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "0%"},
{"Drawdown", "0%"},
{"Expectancy", "0"},
{"Start Equity", "10000.00"},
{"End Equity", "9884.48"},
{"Net Profit", "0%"},
{"Sharpe Ratio", "0"},
{"Sortino Ratio", "0"},
{"Probabilistic Sharpe Ratio", "0%"},
{"Loss Rate", "0%"},
{"Win Rate", "0%"},
{"Profit-Loss Ratio", "0"},
{"Alpha", "0"},
{"Beta", "0"},
{"Annual Standard Deviation", "0"},
{"Annual Variance", "0"},
{"Information Ratio", "0"},
{"Tracking Error", "0"},
{"Treynor Ratio", "0"},
{"Total Fees", "$29.84"},
{"Estimated Strategy Capacity", "$410000.00"},
{"Lowest Capacity Asset", "LTCUSD 2XR"},
{"Portfolio Turnover", "100.61%"},
{"OrderListHash", "716b5757844f607d1402a5571f015aea"}
};
}
}