Jhonathan Abreu
c81f5d7d1a
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* Add SeedInitialPrices algorithm setting This is true by default and indicates that the engine will seed initial prices right after the security is added or selected * Update regression algorithms * Update regression algorithms * Update regression algorithms * Refactor default securities seeding * Minor fix * Minro fixes * Cleanup * Updated and add regression algorithms * Address peer review * Centralize logic to get last known data for multiple securities * Some cleanup * Minor build fix * Minor fixes * More logic centralization * Some more cleanup * Cleanup * Update regression algorithms and minor fixes * Update regression algorithms * Minor fix * More minor fixes * Update regression algorithms * Cleanup * Minor test fix * Address peer review * Minor fix and performance improvement * Fix to seed open interest data * Minor test fixes * Address peer review * Minor change * Minor revert * Minor fixes and improvements * Disable initial seeding by default * Minor fixes * Cleanup * Cleanup * Minor fix
70 lines
2.6 KiB
C#
70 lines
2.6 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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using System.Collections.Generic;
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namespace QuantConnect.Algorithm.CSharp
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{
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public class DailyResolutionVsTimeSpanWithSecondEquityAlgorithm : DailyResolutionVsTimeSpanRegressionAlgorithm
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{
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protected override void InitializeBaseSettings()
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{
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SetStartDate(2013, 10, 07);
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SetEndDate(2013, 10, 08);
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Spy = AddEquity("SPY", Resolution.Second).Symbol;
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}
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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 => 93622;
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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", "0"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "0%"},
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{"Drawdown", "0%"},
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{"Expectancy", "0"},
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{"Start Equity", "100000"},
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{"End Equity", "100000"},
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{"Net Profit", "0%"},
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{"Sharpe Ratio", "0"},
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{"Sortino Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "0%"},
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{"Loss Rate", "0%"},
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{"Win Rate", "0%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "0"},
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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"},
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{"Tracking Error", "0"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$0.00"},
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{"Estimated Strategy Capacity", "$0"},
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{"Lowest Capacity Asset", ""},
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{"Portfolio Turnover", "0%"},
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{"Drawdown Recovery", "0"},
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{"OrderListHash", "d41d8cd98f00b204e9800998ecf8427e"}
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};
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}
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}
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