Martin-Molinero
d4e7f584f6
* Daily data Time & EndTime Improvement - Adjust daily data Time & EndTime to actually reflect the time of the data used, for example US Equity from 9.30 to 4PM. Adding new unit and regression tests * Refactor solution to use enumerator - Refactor daily strict end times solution to be through enumerator usage, so it applies for history providers too * Minor fixes * Revert fill forward enumerator change - Revert FillForward enumerator causing stats changing, enhancing unit tests * Some cleanup * Improve handling of live trading FF enumerator - Improve handling of live trading FF enumerator, by adding support for bars to arrive with a delay so we can handle auction close/option prices or data providers which might have some delay making the data available. Adding new unit tests asserting the behavior
112 lines
4.1 KiB
C#
112 lines
4.1 KiB
C#
/*
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* QUANTCONNECT.COM - Democratizing Finance, Empowering Individuals.
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* Lean Algorithmic Trading Engine v2.0. Copyright 2014 QuantConnect Corporation.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*
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*/
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using System.Linq;
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using QuantConnect.Data;
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using System.Collections.Generic;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Regression for running an IndexOptions algorithm with Daily data
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/// </summary>
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public class BasicTemplateIndexOptionsDailyAlgorithm : BasicTemplateIndexOptionsAlgorithm
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{
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protected override Resolution Resolution => Resolution.Daily;
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protected override int StartDay => 1;
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/// <summary>
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/// Index EMA Cross trading index options of the index.
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/// </summary>
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public override void OnData(Slice slice)
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{
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foreach (var chain in slice.OptionChains.Values)
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{
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// Select the contract with the lowest AskPrice
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var contract = chain.Contracts.OrderBy(x => x.Value.AskPrice).FirstOrDefault().Value;
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if (contract == null)
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{
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return;
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}
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if (Portfolio.Invested)
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{
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Liquidate();
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}
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else
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{
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MarketOrder(contract.Symbol, 1);
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}
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}
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}
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/// <summary>
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/// This is used by the regression test system to indicate if the open source Lean repository has the required data to run this algorithm.
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/// </summary>
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public override bool CanRunLocally { get; } = true;
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/// <summary>
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/// This is used by the regression test system to indicate which languages this algorithm is written in.
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/// </summary>
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public override Language[] Languages { get; } = { Language.CSharp };
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/// <summary>
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/// Data Points count of all timeslices of algorithm
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/// </summary>
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public override long DataPoints => 378;
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/// <summary>
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/// Data Points count of the algorithm history
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/// </summary>
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public override int AlgorithmHistoryDataPoints => 0;
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/// <summary>
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/// This is used by the regression test system to indicate what the expected statistics are from running the algorithm
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/// </summary>
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public override Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Orders", "11"},
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{"Average Win", "0%"},
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{"Average Loss", "-0.01%"},
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{"Compounding Annual Return", "-0.092%"},
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{"Drawdown", "0.000%"},
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{"Expectancy", "-1"},
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{"Start Equity", "1000000"},
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{"End Equity", "999920"},
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{"Net Profit", "-0.008%"},
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{"Sharpe Ratio", "-19.865"},
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{"Sortino Ratio", "-175397.15"},
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{"Probabilistic Sharpe Ratio", "0.013%"},
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{"Loss Rate", "100%"},
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{"Win Rate", "0%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "-0.003"},
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{"Beta", "0"},
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{"Annual Standard Deviation", "0"},
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{"Annual Variance", "0"},
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{"Information Ratio", "-0.454"},
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{"Tracking Error", "0.138"},
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{"Treynor Ratio", "-44.954"},
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{"Total Fees", "$0.00"},
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{"Estimated Strategy Capacity", "$0"},
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{"Lowest Capacity Asset", "SPX XL80P59H5E6M|SPX 31"},
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{"Portfolio Turnover", "0.00%"},
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{"OrderListHash", "285cec32c0947f0e8cf90ccb672cfa43"}
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};
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}
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}
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