Files
quantconnect--lean/Algorithm.CSharp/HistoryProviderManagerRegressionAlgorithm.cs
T
Ronit Jain f129ab1a09
Build & Test Lean / build (push) Has been cancelled
Regression Tests / build (push) Has been cancelled
Feature implement ExchangeInfoDownloader (#6213)
* add gdax exchange info downloader

* add downloader method to program]

* fetch currency description

* change definition to include headers

* use extension method to make request

* remove log from test

* replace WebRequest

* cleanup

* use relevant name

* implement IExchangeInfoDownloader for bitfinex, initial commit

* add default values

* use default market value

* use correct attribute for lotsize

* don't skip missing values

* handle multiple downloaders

* add gdax and bitfinex exchange downloader

* follow LEAN data directory structure

* update SPDB

* order tickers

* order tickers

* add exchange info downloader test template

* delete files

* update SPDB

* use currency mapping

* update bitfinex symbols

* update currency mapping

* sort result after old currency symbols are used

* use market of the respective brokerage

* no more unknown symbol

* change minimum order size value

* direct conversion possible

* update bitfinex symbols

* change user-agent

* add test for indirect conversion

* update stats
2022-02-22 13:00:54 -03:00

121 lines
4.7 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.Data;
using QuantConnect.Interfaces;
using System;
using System.Collections.Generic;
namespace QuantConnect.Algorithm.CSharp
{
/// <summary>
/// Test algorithm to verify the corret working of <see cref="HistoryProviderManager"/>
/// </summary>
public class HistoryProviderManagerRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private bool _onDataTriggered = new();
/// <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(2017, 12, 17);
AddCrypto("BTCUSD");
SetWarmup(1000000);
}
/// <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)
{
_onDataTriggered = true;
}
public override void OnEndOfAlgorithm()
{
if (IsWarmingUp)
{
throw new Exception("Warm up not complete");
}
if (!_onDataTriggered)
{
throw new Exception("No data received is OnData method");
}
}
/// <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>
/// 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", "0"},
{"Average Win", "0%"},
{"Average Loss", "0%"},
{"Compounding Annual Return", "0%"},
{"Drawdown", "0%"},
{"Expectancy", "0"},
{"Net Profit", "0%"},
{"Sharpe 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", "-0.56"},
{"Tracking Error", "0.164"},
{"Treynor Ratio", "0"},
{"Total Fees", "$0.00"},
{"Estimated Strategy Capacity", "$0"},
{"Lowest Capacity Asset", ""},
{"Fitness Score", "0"},
{"Kelly Criterion Estimate", "0"},
{"Kelly Criterion Probability Value", "0"},
{"Sortino Ratio", "79228162514264337593543950335"},
{"Return Over Maximum Drawdown", "79228162514264337593543950335"},
{"Portfolio Turnover", "0"},
{"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", "d41d8cd98f00b204e9800998ecf8427e"}
};
}
}