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https://github.com/mihakralj/QuanTAlib.git
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Miha
116 lines
3.3 KiB
C#
116 lines
3.3 KiB
C#
using System;
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using System.Linq;
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namespace QuanTAlib;
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/// <summary>
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/// ZSCORE: Standardized Distance Measure
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/// A statistical measure that indicates how many standard deviations an observation
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/// is from the mean. Z-scores normalize data to a standard scale, making it useful
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/// for comparing values across different distributions.
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/// </summary>
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/// <remarks>
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/// The Zscore calculation process:
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/// 1. Calculates mean of the period
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/// 2. Computes standard deviation
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/// 3. Measures distance from mean
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/// 4. Normalizes by standard deviation
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///
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/// Key characteristics:
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/// - Scale-independent measure
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/// - Symmetric around zero
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/// - Normal distribution context
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/// - Outlier identification
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/// - Comparative analysis tool
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///
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/// Formula:
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/// Z = (x - μ) / σ
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/// where:
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/// x = current value
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/// μ = mean
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/// σ = standard deviation
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///
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/// Market Applications:
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/// - Mean reversion strategies
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/// - Overbought/oversold signals
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/// - Volatility breakouts
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/// - Cross-asset comparison
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/// - Statistical arbitrage
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///
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/// Sources:
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/// https://en.wikipedia.org/wiki/Standard_score
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/// "Statistical Analysis in Trading" - Technical Analysis
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///
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/// Note: Assumes approximately normal distribution
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/// </remarks>
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public class Zscore : AbstractBase
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{
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private readonly int Period;
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private readonly CircularBuffer _buffer;
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/// <param name="period">The number of points to consider for Z-score calculation.</param>
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/// <exception cref="ArgumentOutOfRangeException">Thrown when period is less than 2.</exception>
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public Zscore(int period)
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{
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if (period < 2)
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{
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throw new ArgumentOutOfRangeException(nameof(period),
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"Period must be greater than or equal to 2 for Z-score calculation.");
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}
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Period = period;
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WarmupPeriod = 2;
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_buffer = new CircularBuffer(period);
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Name = $"ZScore(period={period})";
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Init();
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}
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/// <param name="source">The data source object that publishes updates.</param>
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/// <param name="period">The number of points to consider for Z-score calculation.</param>
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public Zscore(object source, int period) : this(period)
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{
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var pubEvent = source.GetType().GetEvent("Pub");
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pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
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}
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public override void Init()
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{
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base.Init();
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_buffer.Clear();
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}
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protected override void ManageState(bool isNew)
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{
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if (isNew)
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{
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_lastValidValue = Input.Value;
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_index++;
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}
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}
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protected override double Calculation()
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{
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ManageState(Input.IsNew);
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_buffer.Add(Input.Value, Input.IsNew);
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double zScore = 0;
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if (_buffer.Count >= 2) // Need at least 2 points for standard deviation
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{
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var values = _buffer.GetSpan().ToArray();
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double mean = values.Average();
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double n = values.Length;
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// Calculate sample standard deviation
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double sumSquaredDeviations = values.Sum(x => Math.Pow(x - mean, 2));
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double standardDeviation = Math.Sqrt(sumSquaredDeviations / (n - 1));
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if (standardDeviation != 0) // Avoid division by zero
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{
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zScore = (Input.Value - mean) / standardDeviation;
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}
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}
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IsHot = _buffer.Count >= Period;
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return zScore;
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}
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}
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