Alexandre Catarino
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.
103 lines
4.1 KiB
C#
103 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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using System;
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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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using QuantConnect.Orders;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Regression Algorithm for testing engine behavior with throwing errors in OnOrderEvent
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/// Should result in a RunTimeError status.
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/// Reference GH Issue #4947
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/// </summary>
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public class OnOrderEventExceptionRegression : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Symbol _spy = QuantConnect.Symbol.Create("SPY", SecurityType.Equity, Market.USA);
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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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SetStartDate(2013, 10, 07);
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SetEndDate(2013, 10, 11);
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AddEquity("SPY", Resolution.Minute);
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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 (!Portfolio.Invested)
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{
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SetHoldings(_spy, 1);
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Debug("Purchased Stock");
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}
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}
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/// <summary>
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/// OnOrderEvent is called whenever an order is updated
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/// </summary>
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/// <param name="orderEvent">Order Event</param>
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public override void OnOrderEvent(OrderEvent orderEvent)
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{
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throw new Exception("OnOrderEvent exception");
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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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{"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", "0"},
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{"Return Over Maximum Drawdown", "0"},
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{"Portfolio Turnover", "0"},
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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", "9e4bfd2eb0b81ee5bc1b197a87ccedbe"}
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};
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}
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}
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