5bf72d2432
Build & Test Lean / build (push) Has been cancelled
* Adjust TradeBar volume for splits * Refactor solution to centralized function `Scale` * Expand BaseData scale/adjust/normalize tests to assert volume behavior * Add regression algorithm * Update regression statistics * Address review * NOP to trigger cloud build * adjust QuoteBar ask and bid size * adjust broken regression * Update tests to include QuoteBar adjustments * nit cleanup * Adjust Quote Tick bid and ask sizes * Round volume and size values to nearest int in scale() * nit * Adjust regressions
124 lines
5.1 KiB
C#
124 lines
5.1 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.Data.Consolidators;
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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 algorithm reproduces GH issue 2404, exception: `This is a forward only indicator`
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/// </summary>
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public class WarmupIndicatorRegressionAlgorithm : QCAlgorithm, IRegressionAlgorithmDefinition
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{
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private Symbol _spy;
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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, 11, 1);
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SetEndDate(2013, 12, 10); //Set End Date
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SetWarmup(TimeSpan.FromDays(30));
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_spy = AddEquity("SPY", Resolution.Daily).Symbol;
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var renkoConsolidator = new RenkoConsolidator(2m);
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renkoConsolidator.DataConsolidated += (sender, consolidated) =>
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{
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if (IsWarmingUp) return;
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if (!Portfolio.Invested)
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{
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SetHoldings(_spy, 1.0);
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}
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Log($"CLOSE - {consolidated.Time:o} - {consolidated.Open} {consolidated.Close}");
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};
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var sma = new SimpleMovingAverage("SMA", 3);
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RegisterIndicator(_spy, sma, renkoConsolidator);
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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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}
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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", "1"},
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{"Average Win", "0%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "11.988%"},
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{"Drawdown", "1.200%"},
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{"Expectancy", "0"},
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{"Net Profit", "1.237%"},
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{"Sharpe Ratio", "1.934"},
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{"Probabilistic Sharpe Ratio", "63.185%"},
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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", "0.095"},
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{"Beta", "0.009"},
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{"Annual Standard Deviation", "0.05"},
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{"Annual Variance", "0.003"},
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{"Information Ratio", "-1.293"},
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{"Tracking Error", "0.091"},
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{"Treynor Ratio", "10.428"},
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{"Total Fees", "$3.23"},
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{"Estimated Strategy Capacity", "$600000000.00"},
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{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
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{"Fitness Score", "0.027"},
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{"Kelly Criterion Estimate", "0"},
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{"Kelly Criterion Probability Value", "0"},
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{"Sortino Ratio", "5.644"},
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{"Return Over Maximum Drawdown", "10.205"},
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{"Portfolio Turnover", "0.029"},
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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", "194dca16ef78574bf9c65e3173f87a77"}
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};
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}
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}
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