d2d99b1f10
Regression Tests / build (push) Has been cancelled
Build & Test Lean / build (push) Has been cancelled
* 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
123 lines
4.8 KiB
C#
123 lines
4.8 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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using QuantConnect.Data;
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using QuantConnect.Interfaces;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// This is a regression algorithm for CFD assets which have the exchange time zone ahead of the data time zone.
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/// </summary>
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public class CfdTimeZonesRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Symbol _symbol;
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/// <summary>
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/// Initialise the data and resolution required, as well as the cash and start-end dates for your algorithm. All algorithms must initialized.
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/// </summary>
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public override void Initialize()
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{
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SetAccountCurrency("EUR");
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SetStartDate(2019, 2, 19);
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SetEndDate(2019, 2, 21);
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SetCash("EUR", 100000);
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_symbol = AddCfd("DE30EUR", Resolution.Minute, Market.Oanda).Symbol;
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SetBenchmark(_symbol);
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}
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/// <summary>
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/// OnData event is the primary entry point for your algorithm. Each new data point will be pumped in here.
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/// </summary>
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/// <param name="data">Slice object keyed by symbol containing the stock data</param>
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public override void OnData(Slice data)
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{
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if (Time.Minute % 10 != 0) return;
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if (!Portfolio.Invested)
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{
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MarketOrder(_symbol, 1m);
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}
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else
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{
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Liquidate();
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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 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 Language[] Languages { get; } = { Language.CSharp };
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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 Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Trades", "279"},
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{"Average Win", "0.01%"},
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{"Average Loss", "-0.01%"},
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{"Compounding Annual Return", "-33.650%"},
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{"Drawdown", "0.300%"},
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{"Expectancy", "-0.345"},
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{"Net Profit", "-0.337%"},
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{"Sharpe Ratio", "-19.772"},
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{"Probabilistic Sharpe Ratio", "0%"},
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{"Loss Rate", "68%"},
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{"Win Rate", "32%"},
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{"Profit-Loss Ratio", "1.07"},
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{"Alpha", "0"},
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{"Beta", "0"},
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{"Annual Standard Deviation", "0.014"},
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{"Annual Variance", "0"},
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{"Information Ratio", "-19.772"},
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{"Tracking Error", "0.014"},
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{"Treynor Ratio", "0"},
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{"Total Fees", "$0.00"},
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{"Estimated Strategy Capacity", "$670000.00"},
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{"Lowest Capacity Asset", "DE30EUR 8I"},
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{"Fitness Score", "0"},
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{"Kelly Criterion Estimate", "0"},
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{"Kelly Criterion Probability Value", "0"},
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{"Sortino Ratio", "-101.587"},
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{"Return Over Maximum Drawdown", "-110.633"},
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{"Portfolio Turnover", "9.513"},
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{"Total Insights Generated", "0"},
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{"Total Insights Closed", "0"},
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{"Total Insights Analysis Completed", "0"},
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{"Long Insight Count", "0"},
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{"Short Insight Count", "0"},
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{"Long/Short Ratio", "100%"},
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{"Estimated Monthly Alpha Value", "€0"},
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{"Total Accumulated Estimated Alpha Value", "€0"},
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{"Mean Population Estimated Insight Value", "€0"},
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{"Mean Population Direction", "0%"},
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{"Mean Population Magnitude", "0%"},
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{"Rolling Averaged Population Direction", "0%"},
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{"Rolling Averaged Population Magnitude", "0%"},
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{"OrderListHash", "64c098abe3c1e7206424b0c3825b0069"}
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};
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}
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}
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