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 System;
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using System.Linq;
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using QuantConnect.Data;
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using QuantConnect.Indicators;
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using QuantConnect.Interfaces;
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using System.Collections.Generic;
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namespace QuantConnect.Algorithm.CSharp
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{
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/// <summary>
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/// Constructs a displaced moving average ribbon and buys when all are lined up, liquidates when they all line down
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/// Ribbons are great for visualizing trends
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/// Signals are generated when they all line up in a paricular direction
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/// A buy signal is when the values of the indicators are increasing (from slowest to fastest).
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/// A sell signal is when the values of the indicators are decreasing (from slowest to fastest).
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/// </summary>
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public class DisplacedMovingAverageRibbon : 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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private IndicatorBase<IndicatorDataPoint>[] _ribbon;
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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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/// <meta name="tag" content="charting" />
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/// <meta name="tag" content="plotting indicators" />
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/// <seealso cref="QCAlgorithm.SetStartDate(System.DateTime)"/>
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/// <seealso cref="QCAlgorithm.SetEndDate(System.DateTime)"/>
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/// <seealso cref="QCAlgorithm.SetCash(decimal)"/>
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public override void Initialize()
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{
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SetStartDate(2009, 01, 01);
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SetEndDate(2015, 01, 01);
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AddSecurity(SecurityType.Equity, "SPY", Resolution.Daily);
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const int count = 6;
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const int offset = 5;
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const int period = 15;
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// define our sma as the base of the ribbon
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var sma = new SimpleMovingAverage(period);
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_ribbon = Enumerable.Range(0, count).Select(x =>
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{
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// define our offset to the zero sma, these various offsets will create our 'displaced' ribbon
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var delay = new Delay(offset*(x+1));
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// define an indicator that takes the output of the sma and pipes it into our delay indicator
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var delayedSma = delay.Of(sma);
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// register our new 'delayedSma' for automatic updates on a daily resolution
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RegisterIndicator(_spy, delayedSma, Resolution.Daily, data => data.Value);
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return delayedSma;
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}).ToArray();
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}
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private DateTime _previous;
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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">TradeBars IDictionary object with your stock data</param>
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public override void OnData(Slice slice)
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{
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// wait for our entire ribbon to be ready
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if (!_ribbon.All(x => x.IsReady)) return;
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// only once per day
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if (_previous.Date == Time.Date) return;
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var data = slice[_spy];
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if (data == null)
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{
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// at midnight we can get dividend call, not price data
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return;
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}
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Plot("Ribbon", "Price", data.Price);
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Plot("Ribbon", _ribbon);
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// check for a buy signal
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var values = _ribbon.Select(x => x.Current.Value).ToArray();
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var holding = Portfolio[_spy];
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if (holding.Quantity <= 0 && IsAscending(values))
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{
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SetHoldings(_spy, 1.0);
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}
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else if (holding.Quantity > 0 && IsDescending(values))
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{
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Liquidate(_spy);
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}
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_previous = Time;
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}
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/// <summary>
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/// Returns true if the specified values are in ascending order
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/// </summary>
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private bool IsAscending(IEnumerable<decimal> values)
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{
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decimal? last = null;
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foreach (var val in values)
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{
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if (last == null)
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{
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last = val;
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continue;
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}
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if (last.Value < val)
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{
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return false;
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}
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last = val;
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}
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return true;
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}
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/// <summary>
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/// Returns true if the specified values are in descending order
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/// </summary>
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private bool IsDescending(IEnumerable<decimal> values)
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{
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decimal? last = null;
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foreach (var val in values)
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{
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if (last == null)
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{
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last = val;
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continue;
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}
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if (last.Value > val)
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{
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return false;
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}
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last = val;
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}
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return true;
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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, Language.Python };
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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 long DataPoints => 12073;
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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 Dictionary<string, string> ExpectedStatistics => new Dictionary<string, string>
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{
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{"Total Orders", "7"},
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{"Average Win", "19.17%"},
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{"Average Loss", "0%"},
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{"Compounding Annual Return", "16.731%"},
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{"Drawdown", "12.400%"},
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{"Expectancy", "0"},
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{"Start Equity", "100000"},
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{"End Equity", "253075.04"},
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{"Net Profit", "153.075%"},
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{"Sharpe Ratio", "1.05"},
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{"Sortino Ratio", "1.078"},
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{"Probabilistic Sharpe Ratio", "48.708%"},
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{"Loss Rate", "0%"},
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{"Win Rate", "100%"},
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{"Profit-Loss Ratio", "0"},
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{"Alpha", "0.051"},
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{"Beta", "0.507"},
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{"Annual Standard Deviation", "0.107"},
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{"Annual Variance", "0.011"},
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{"Information Ratio", "-0.083"},
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{"Tracking Error", "0.105"},
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{"Treynor Ratio", "0.221"},
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{"Total Fees", "$49.40"},
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{"Estimated Strategy Capacity", "$1100000000.00"},
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{"Lowest Capacity Asset", "SPY R735QTJ8XC9X"},
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{"Portfolio Turnover", "0.32%"},
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{"Drawdown Recovery", "268"},
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{"OrderListHash", "1ea790ca8afdcad02b98c70e89652562"}
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};
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}
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}
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