Files
quantconnect--lean/Algorithm.CSharp/CfdTimeZonesRegressionAlgorithm.cs
T
Colton Sellers d2d99b1f10
Regression Tests / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
Algorithm Sampling and Statistics Fixes (#5936)
* Implement scheduled event sampling solution

* Use UTC time, only update daily portfolio value once a day

* For daily resolutions sample chart always

* Cleanup

* Drop resample daily all together

* Force final sample

* Regression updates

* FIx LiveResultHandler to update portfolio and benchmark values outside of sampling event

* Name the daily sampling event

* Address review pt 1

* Drop force and use reference wrapper

* Adjust tests

* Fix warning for Benchmark Timezone Misalignment and also add test

* Fix for daily resolution orders and test adjustments

* Also warn on universe settings with daily resolution

* Update missed regression

* Fix reference wrapper use

* Update regression after rebase

* Add values back in for Daylight Algo

* Have statistics builder skip day 1 performance

* Regression adjustments

* Test adjustments

* Update regression unit test

* Adjust some regressions starts to show performance values

* Add hourly algorithm for beta comparison

* Address missing Python regression changes

* Remove null comment
2021-10-05 19:31:25 -03:00

123 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>
/// This is a regression algorithm for CFD assets which have the exchange time zone ahead of the data time zone.
/// </summary>
public class CfdTimeZonesRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
{
private Symbol _symbol;
/// <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()
{
SetAccountCurrency("EUR");
SetStartDate(2019, 2, 19);
SetEndDate(2019, 2, 21);
SetCash("EUR", 100000);
_symbol = AddCfd("DE30EUR", Resolution.Minute, Market.Oanda).Symbol;
SetBenchmark(_symbol);
}
/// <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 (Time.Minute % 10 != 0) return;
if (!Portfolio.Invested)
{
MarketOrder(_symbol, 1m);
}
else
{
Liquidate();
}
}
/// <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", "279"},
{"Average Win", "0.01%"},
{"Average Loss", "-0.01%"},
{"Compounding Annual Return", "-33.650%"},
{"Drawdown", "0.300%"},
{"Expectancy", "-0.345"},
{"Net Profit", "-0.337%"},
{"Sharpe Ratio", "-19.772"},
{"Probabilistic Sharpe Ratio", "0%"},
{"Loss Rate", "68%"},
{"Win Rate", "32%"},
{"Profit-Loss Ratio", "1.07"},
{"Alpha", "0"},
{"Beta", "0"},
{"Annual Standard Deviation", "0.014"},
{"Annual Variance", "0"},
{"Information Ratio", "-19.772"},
{"Tracking Error", "0.014"},
{"Treynor Ratio", "0"},
{"Total Fees", "$0.00"},
{"Estimated Strategy Capacity", "$670000.00"},
{"Lowest Capacity Asset", "DE30EUR 8I"},
{"Fitness Score", "0"},
{"Kelly Criterion Estimate", "0"},
{"Kelly Criterion Probability Value", "0"},
{"Sortino Ratio", "-101.587"},
{"Return Over Maximum Drawdown", "-110.633"},
{"Portfolio Turnover", "9.513"},
{"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", "64c098abe3c1e7206424b0c3825b0069"}
};
}
}