chore: import upstream snapshot with attribution
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wehub-resource-sync
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/*
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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 QuantConnect.Data;
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using QuantConnect.Interfaces;
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using System.Collections.Generic;
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using System;
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using QuantConnect.Securities;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Regression algorithm asserting that the current price of the security is adjusted after a split.
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/// Specific for minute resolution.
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/// </summary>
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public class EquitySplitHoldingsMinuteRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Security _aapl;
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private decimal _aaplPriceBeforeSplit;
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private decimal _aaplVolumeBeforeSplit;
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private decimal _aaplOpenBeforeSplit;
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private decimal _aaplCloseBeforeSplit;
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private decimal _aaplHighBeforeSplit;
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private decimal _aaplLowBeforeSplit;
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private decimal _aaplAskPriceBeforeSplit;
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private decimal _aaplBidPriceBeforeSplit;
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private decimal _aaplAskSizeBeforeSplit;
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private decimal _aaplBidSizeBeforeSplit;
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private bool _splitOccurred;
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protected virtual Resolution Resolution => Resolution.Minute;
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public override void Initialize()
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{
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SetStartDate(2014, 6, 5);
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SetEndDate(2014, 6, 11);
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SetCash(100000);
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_aapl = AddEquity("AAPL", Resolution, dataNormalizationMode: DataNormalizationMode.Raw);
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}
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public override void OnData(Slice slice)
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{
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if (!Portfolio.Invested && !_splitOccurred)
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{
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SetHoldings(_aapl.Symbol, -1);
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}
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if (slice.Splits.TryGetValue(_aapl.Symbol, out var split) && split.Type == SplitType.SplitOccurred)
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{
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_splitOccurred = true;
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if (!_aapl.Holdings.Invested)
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{
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throw new RegressionTestException("AAPL is not invested after split occurred");
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}
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if (_aapl.Holdings.Price != _aapl.Price)
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{
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throw new RegressionTestException($"AAPL price is not equal to AAPL holdings price. " +
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$"AAPL price: {_aapl.Price}, AAPL holdings price: {_aapl.Holdings.Price}");
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}
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AssertFactorChange("Price check", _aaplPriceBeforeSplit, _aapl.Price, split.SplitFactor);
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AssertFactorChange("Open price check", _aaplOpenBeforeSplit, _aapl.Open, split.SplitFactor);
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AssertFactorChange("Close price check", _aaplCloseBeforeSplit, _aapl.Close, split.SplitFactor);
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AssertFactorChange("High price check", _aaplHighBeforeSplit, _aapl.High, split.SplitFactor);
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AssertFactorChange("Low price check", _aaplLowBeforeSplit, _aapl.Low, split.SplitFactor);
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AssertFactorChange("Volume check", _aaplVolumeBeforeSplit, _aapl.Volume, 1 / split.SplitFactor);
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if (Resolution < Resolution.Hour)
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{
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AssertFactorChange("Ask price check", _aaplAskPriceBeforeSplit, _aapl.AskPrice, split.SplitFactor);
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AssertFactorChange("Bid price check", _aaplBidPriceBeforeSplit, _aapl.BidPrice, split.SplitFactor);
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AssertFactorChange("Ask size check", _aaplAskSizeBeforeSplit, _aapl.AskSize, 1 / split.SplitFactor);
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AssertFactorChange("Bid size check", _aaplBidSizeBeforeSplit, _aapl.BidSize, 1 / split.SplitFactor);
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}
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}
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else
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{
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_aaplPriceBeforeSplit = _aapl.Price;
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_aaplOpenBeforeSplit = _aapl.Open;
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_aaplCloseBeforeSplit = _aapl.Close;
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_aaplHighBeforeSplit = _aapl.High;
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_aaplLowBeforeSplit = _aapl.Low;
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_aaplVolumeBeforeSplit = _aapl.Volume;
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_aaplAskPriceBeforeSplit = _aapl.AskPrice;
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_aaplBidPriceBeforeSplit = _aapl.BidPrice;
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_aaplAskSizeBeforeSplit = _aapl.AskSize;
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_aaplBidSizeBeforeSplit = _aapl.BidSize;
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}
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}
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private static void AssertFactorChange(string messagePrefix, decimal priceBeforeSplit, decimal priceAfterSplit, decimal splitFactor)
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{
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if (Math.Abs(priceAfterSplit / priceBeforeSplit - splitFactor) >= 0.0001m)
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{
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throw new RegressionTestException($"{messagePrefix}: split factor is not correct. Expected: {splitFactor}, " +
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$"Actual: {priceAfterSplit / priceBeforeSplit}");
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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 (!_splitOccurred)
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{
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throw new RegressionTestException("Split did not occur");
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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 List<Language> Languages { get; } = new() { 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 virtual long DataPoints => 3945;
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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 int AlgorithmHistoryDataPoints => 0;
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/// <summary>
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/// Final status of the algorithm
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/// </summary>
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public AlgorithmStatus AlgorithmStatus => AlgorithmStatus.Completed;
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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 virtual Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Orders", "1"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "-56.234%"},
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{"Drawdown", "2.200%"},
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{"Expectancy", "0"},
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{"Start Equity", "100000"},
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{"End Equity", "98502.10"},
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{"Net Profit", "-1.498%"},
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{"Sharpe Ratio", "-4.002"},
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{"Sortino Ratio", "0"},
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{"Probabilistic Sharpe Ratio", "7.613%"},
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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", "-0.447"},
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{"Beta", "0.159"},
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{"Annual Standard Deviation", "0.108"},
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{"Annual Variance", "0.012"},
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{"Information Ratio", "-4.67"},
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{"Tracking Error", "0.113"},
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{"Treynor Ratio", "-2.711"},
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{"Total Fees", "$1.00"},
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{"Estimated Strategy Capacity", "$41000000.00"},
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{"Lowest Capacity Asset", "AAPL R735QTJ8XC9X"},
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{"Portfolio Turnover", "14.24%"},
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{"Drawdown Recovery", "4"},
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{"OrderListHash", "5d7b0658b66b331ba8159011aa2ec5b4"}
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};
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}
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}
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