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https://github.com/mihakralj/QuanTAlib.git
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94 lines
3.0 KiB
C#
94 lines
3.0 KiB
C#
using System.Runtime.CompilerServices;
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namespace QuanTAlib;
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/// <summary>
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/// PV: Parkinson Volatility
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/// A volatility measure that uses the high and low prices to estimate
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/// volatility, assuming continuous trading and log-normal price distribution.
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/// </summary>
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/// <remarks>
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/// The PV calculation process:
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/// 1. Calculate squared log range for each period
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/// 2. Apply scaling factor (1/4ln2)
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/// 3. Average over specified period
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/// 4. Take square root for final volatility
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///
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/// Key characteristics:
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/// - Range-based volatility
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/// - More efficient than close-to-close
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/// - Assumes continuous trading
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/// - No gap consideration
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/// - Log-normal distribution
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///
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/// Formula:
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/// PV = sqrt(1/(4*ln(2)*n) * Σ(ln(High/Low))²)
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/// where n is the number of periods
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///
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/// Market Applications:
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/// - Volatility estimation
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/// - Risk assessment
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/// - Option pricing
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/// - Trading system development
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/// - Market regime identification
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///
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/// Note: More efficient than traditional volatility measures but sensitive to gaps
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/// </remarks>
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[SkipLocalsInit]
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public sealed class Pv : AbstractBase
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{
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private readonly Sma _ma;
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private readonly double _scaleFactor;
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private const int DefaultPeriod = 10;
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private double _prevValue;
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/// <param name="period">The number of periods for PV calculation (default 10).</param>
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/// <exception cref="ArgumentOutOfRangeException">Thrown when period is less than 1.</exception>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public Pv(int period = DefaultPeriod)
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{
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if (period < 1)
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throw new ArgumentOutOfRangeException(nameof(period));
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_ma = new(period);
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_scaleFactor = 1.0 / (4.0 * Math.Log(2.0));
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WarmupPeriod = period;
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Name = $"PV({period})";
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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 periods for PV calculation.</param>
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public Pv(object source, int period = DefaultPeriod) : this(period)
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{
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var pubEvent = source.GetType().GetEvent("Pub");
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pubEvent?.AddEventHandler(source, new BarSignal(Sub));
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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protected override void ManageState(bool isNew)
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{
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if (isNew)
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_index++;
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining | MethodImplOptions.AggressiveOptimization)]
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protected override double Calculation()
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{
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if (!BarInput.IsNew)
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return _prevValue;
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ManageState(true);
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// Calculate log range squared
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double logRange = Math.Log(BarInput.High / BarInput.Low);
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double logRangeSquared = logRange * logRange;
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// Apply moving average and scaling
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double meanLogRangeSquared = _ma.Calc(logRangeSquared, true);
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// Calculate final volatility
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_prevValue = Math.Sqrt(_scaleFactor * meanLogRangeSquared);
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return _prevValue;
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}
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}
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