2b0fd2e607
* Fixes Double to Decimal Cast in GetAnnualPerformance `GetAnnualPerformance` raises an exception if the `AnnualPerformance` calculation returns a double that cannot be cast to decimal (smaller than `decimal.MinValue` or bigger than `decimal.MaxValue`). See `ProbabilisticSharpeRatio` where the same solution was applied. * Updates SPY Market Data SPY is a key asset since it is the default benchmark, and any change can lead to different `Alpha` and `Beta` * Updates Unit Tests to Reflect Data Update * Updates Regression Tests to Reflect Data Update I Most of the regression tests change because of updated data (market and factors) of SPY (default benchmark) while the total trade remain the same. * Updates Regression Tests to Reflect Data Update II The following regression tests were changed to adapt to adjusted prices and keep the total trades: - `BacktestingBrokerageRegressionAlgorithm` - `LimitIfTouchedRegressionAlgorithm` - `PortfolioRebalanceOnCustomFuncRegressionAlgorithm` - `SetAccountCurrencySecurityMarginModelRegressionAlgorithm` - `StopLossOnOrderEventRegressionAlgorithm` - `TimeInForceAlgorithm` The following regression tests have more trades since adjusted prices allowed more 1-2 shares trades that were rounded down to zero before: - `FreePortfolioValueRegressionAlgorithm` 2 -> 3 - `PortfolioRebalanceOnDateRulesRegressionAlgorithm` 291 -> 298 - `TrailingStopRiskFrameworkAlgorithm` 5 -> 7 Especial cases: - `AutoRegressiveIntegratedMovingAverageRegressionAlgorithm` 65 -> 52 - ARIMA model sensibility - `BlackLittermanPortfolioOptimizationFrameworkAlgorithm` 18 -> 19 - BLM model sensibility - `ExtendedMarketHoursHistoryRegressionAlgorithm` 20 -> 18 - Less minute bars before market opens * Addresses Peer-Review Fix `BacktestingBrokerageRegressionAlgorithm` to use `CalculateOrderQuantity` and round down `quantity` to an even number to pass a value assertion and update the expected value from 50 to 52. The quantity calculated by `CalculateOrderQuantity` has changed from 50 to 53 because of factor file update.
158 lines
5.6 KiB
C#
158 lines
5.6 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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*/
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using System;
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using QuantConnect.Data;
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using System.Collections.Generic;
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using QuantConnect.Indicators;
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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 example demonstrates how to add index asset types.
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/// </summary>
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/// <meta name="tag" content="using data" />
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/// <meta name="tag" content="benchmarks" />
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/// <meta name="tag" content="indexes" />
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public class BasicTemplateIndexAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Symbol _spx;
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private Symbol _spxOption;
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private ExponentialMovingAverage _emaSlow;
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private ExponentialMovingAverage _emaFast;
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/// <summary>
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/// Initialize your algorithm and add desired assets.
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/// </summary>
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public override void Initialize()
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{
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SetStartDate(2021, 1, 4);
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SetEndDate(2021, 1, 15);
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SetCash(1000000);
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// Use indicator for signal; but it cannot be traded
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_spx = AddIndex("SPX", Resolution.Minute).Symbol;
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// Trade on SPX ITM calls
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_spxOption = QuantConnect.Symbol.CreateOption(
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_spx,
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Market.USA,
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OptionStyle.European,
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OptionRight.Call,
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3200m,
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new DateTime(2021, 1, 15));
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AddIndexOptionContract(_spxOption, Resolution.Minute);
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_emaSlow = EMA(_spx, 80);
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_emaFast = EMA(_spx, 200);
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}
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/// <summary>
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/// Index EMA Cross trading underlying.
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/// </summary>
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public override void OnData(Slice slice)
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{
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if (!slice.Bars.ContainsKey(_spx) || !slice.Bars.ContainsKey(_spxOption))
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{
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return;
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}
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// Warm up indicators
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if (!_emaSlow.IsReady)
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{
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return;
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}
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if (_emaFast > _emaSlow)
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{
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SetHoldings(_spxOption, 1);
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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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public override void OnEndOfAlgorithm()
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{
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if (Portfolio[_spx].TotalSaleVolume > 0)
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{
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throw new Exception("Index is not tradable.");
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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, Language.Python };
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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", "4"},
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{"Average Win", "0%"},
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{"Average Loss", "-53.10%"},
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{"Compounding Annual Return", "-96.172%"},
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{"Drawdown", "10.100%"},
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{"Expectancy", "-1"},
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{"Net Profit", "-9.915%"},
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{"Sharpe Ratio", "-4.217"},
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{"Probabilistic Sharpe Ratio", "0.052%"},
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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", "-0.908"},
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{"Beta", "0.468"},
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{"Annual Standard Deviation", "0.139"},
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{"Annual Variance", "0.019"},
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{"Information Ratio", "-9.003"},
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{"Tracking Error", "0.142"},
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{"Treynor Ratio", "-1.251"},
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{"Total Fees", "$0.00"},
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{"Estimated Strategy Capacity", "$14000000.00"},
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{"Fitness Score", "0.044"},
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{"Kelly Criterion Estimate", "0"},
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{"Kelly Criterion Probability Value", "0"},
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{"Sortino Ratio", "-1.96"},
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{"Return Over Maximum Drawdown", "-10.171"},
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{"Portfolio Turnover", "0.34"},
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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", "52521ab779446daf4d38a7c9bbbdd893"}
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};
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}
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}
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