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QuanTAlib/lib/statistics/Skew.cs
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2024-10-05 15:20:13 -07:00

109 lines
4.0 KiB
C#

namespace QuanTAlib;
/// <summary>
/// Represents a skewness calculator that measures the asymmetry of the probability
/// distribution of a real-valued random variable about its mean.
/// </summary>
/// <remarks>
/// The Skew class uses a circular buffer to store values and calculates the skewness
/// efficiently. It uses the adjusted Fisher-Pearson standardized moment coefficient
/// for sample skewness calculation. A minimum of 3 data points is required for the
/// calculation.
/// </remarks>
public class Skew : AbstractBase {
private readonly int Period;
private readonly CircularBuffer _buffer;
/// <summary>
/// Initializes a new instance of the Skew class with the specified period.
/// </summary>
/// <param name="period">The period over which to calculate the skewness.</param>
/// <exception cref="ArgumentOutOfRangeException">
/// Thrown when period is less than 3.
/// </exception>
public Skew(int period) : base() {
if (period < 3) {
throw new ArgumentOutOfRangeException(nameof(period), "Period must be greater than or equal to 3 for skewness calculation.");
}
Period = period;
WarmupPeriod = 3;
_buffer = new CircularBuffer(period);
Name = $"Skew(period={period})";
Init();
}
/// <summary>
/// Initializes a new instance of the Skew class with the specified source and period.
/// </summary>
/// <param name="source">The source object to subscribe to for value updates.</param>
/// <param name="period">The period over which to calculate the skewness.</param>
public Skew(object source, int period) : this(period) {
var pubEvent = source.GetType().GetEvent("Pub");
pubEvent?.AddEventHandler(source, new ValueSignal(Sub));
}
/// <summary>
/// Initializes the Skew instance by clearing the buffer.
/// </summary>
public override void Init() {
base.Init();
_buffer.Clear();
}
/// <summary>
/// Manages the state of the Skew instance based on whether a new value is being processed.
/// </summary>
/// <param name="isNew">Indicates whether the current input is a new value.</param>
protected override void ManageState(bool isNew) {
if (isNew) {
_lastValidValue = Input.Value;
_index++;
}
}
/// <summary>
/// Performs the skewness calculation for the current period.
/// </summary>
/// <returns>
/// The calculated skewness value for the current period.
/// </returns>
/// <remarks>
/// This method uses the adjusted Fisher-Pearson standardized moment coefficient
/// to calculate the sample skewness. It requires at least 3 data points for the
/// calculation. If there are fewer than 3 data points, or if the standard
/// deviation is zero, the method returns 0.
/// </remarks>
protected override double Calculation() {
ManageState(Input.IsNew);
_buffer.Add(Input.Value, Input.IsNew);
double skew = 0;
if (_buffer.Count >= 3) { // We need at least 3 data points for skewness
var values = _buffer.GetSpan().ToArray();
double mean = values.Average();
double n = values.Length;
double sumCubedDeviations = 0;
double sumSquaredDeviations = 0;
foreach (var value in values) {
double deviation = value - mean;
sumCubedDeviations += Math.Pow(deviation, 3);
sumSquaredDeviations += Math.Pow(deviation, 2);
}
// Calculate sample skewness using the adjusted Fisher-Pearson standardized moment coefficient
double m3 = sumCubedDeviations / n;
double m2 = sumSquaredDeviations / n;
double s3 = Math.Pow(m2, 1.5);
if (s3 != 0) { // Avoid division by zero
skew = (Math.Sqrt(n * (n - 1)) / (n - 2)) * (m3 / s3);
}
}
IsHot = _buffer.Count >= Period;
return skew;
}
}