using System.Runtime.CompilerServices;
using System.Runtime.InteropServices;
namespace QuanTAlib;
///
/// EWMA: Exponentially Weighted Moving Average Volatility
///
///
/// EWMA Volatility calculates volatility using an exponentially weighted moving average
/// of squared log returns. This approach gives more weight to recent observations while
/// still considering historical data, making it responsive to market changes.
///
/// Formula:
/// r_t = ln(Close_t / Close_{t-1})
/// RMA_t = (RMA_{t-1} × (period - 1) + r²_t) / period
/// BiasCorrection = 1 - (1 - 1/period)^n
/// CorrectedVariance = RMA_t / BiasCorrection
/// EWMA = √(CorrectedVariance × AnnualPeriods)
///
/// Key properties:
/// - Uses RMA (Running Moving Average) for exponential smoothing
/// - Includes bias correction for accurate early estimates
/// - Can be annualized or returned as periodic volatility
/// - More responsive than simple moving average approaches
///
[SkipLocalsInit]
public sealed class Ewma : AbstractBase
{
private readonly int _period;
private readonly bool _annualize;
private readonly int _annualPeriods;
private readonly double _decay;
private const double MinPrice = 1e-10;
private const double Epsilon = 1e-10;
[StructLayout(LayoutKind.Auto)]
private record struct State(
double RawRmaSqRet,
double BiasE,
double PrevClose,
double LastValid,
int Count);
private State _s;
private State _ps;
///
/// Creates EWMA Volatility indicator with specified parameters.
///
/// The period for EWMA calculation (must be > 0)
/// Whether to annualize the volatility output (default: true)
/// Number of periods in a year for annualization (default: 252 for daily data)
/// Thrown when parameters are invalid
public Ewma(int period = 20, bool annualize = true, int annualPeriods = 252)
{
if (period <= 0)
{
throw new ArgumentException("Period must be greater than 0", nameof(period));
}
if (annualize && annualPeriods <= 0)
{
throw new ArgumentException("Annual periods must be greater than 0 when annualizing", nameof(annualPeriods));
}
_period = period;
_annualize = annualize;
_annualPeriods = annualPeriods;
_decay = 1.0 - (1.0 / period);
Name = annualize ? $"Ewma({period},{annualPeriods})" : $"Ewma({period})";
WarmupPeriod = period;
_s = new State(0.0, 1.0, double.NaN, 0.0, 0);
_ps = _s;
}
///
/// Creates EWMA Volatility indicator with specified source and parameters.
///
public Ewma(ITValuePublisher source, int period = 20, bool annualize = true, int annualPeriods = 252)
: this(period, annualize, annualPeriods)
{
source.Pub += Handle;
}
private void Handle(object? sender, in TValueEventArgs e) => Update(e.Value, e.IsNew);
///
/// True if the indicator has completed the warmup period.
///
public override bool IsHot => _s.Count >= _period;
///
/// Period for EWMA calculation.
///
public int Period => _period;
///
/// Whether volatility is annualized.
///
public bool Annualize => _annualize;
///
/// Number of periods per year for annualization.
///
public int AnnualPeriods => _annualPeriods;
///
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public override TValue Update(TValue input, bool isNew = true)
{
double close = input.Value;
if (isNew)
{
_ps = _s;
}
else
{
_s = _ps;
}
var s = _s;
// Sanitize input - use state's LastValid for consistency
double lastValid = double.IsFinite(s.LastValid) && s.LastValid > 0 ? s.LastValid : 1.0;
if (!double.IsFinite(close) || close <= 0)
{
close = lastValid;
}
else if (isNew)
{
s.LastValid = close;
}
double safeClose = Math.Max(close, MinPrice);
double safePrevClose = double.IsFinite(s.PrevClose) && s.PrevClose > 0 ? s.PrevClose : safeClose;
// Calculate log return
double logReturn = 0.0;
if (safeClose > 0.0 && safePrevClose > 0.0)
{
logReturn = Math.Log(safeClose / safePrevClose);
}
double squaredReturn = logReturn * logReturn;
// RMA calculation: raw_rma_sq_ret = (raw_rma_sq_ret * (period - 1) + squaredReturn) / period
double rawRmaSqRet;
double biasE;
if (s.Count == 0)
{
// First value: initialize with squared return
rawRmaSqRet = squaredReturn;
biasE = _decay;
}
else
{
// RMA update: (prev * (period - 1) + current) / period
rawRmaSqRet = Math.FusedMultiplyAdd(s.RawRmaSqRet, _period - 1, squaredReturn) / _period;
// Update bias correction factor: e = (1 - alpha) * e_prev
biasE = _decay * s.BiasE;
}
// Bias correction: corrected = raw / (1 - e)
double biasCorrection = 1.0 - biasE;
double correctedRmaSqRet = biasCorrection > Epsilon ? rawRmaSqRet / biasCorrection : rawRmaSqRet;
// Ensure non-negative variance
double currentEwmaSqReturns = Math.Max(correctedRmaSqRet, 0.0);
// Calculate volatility
double volatility = Math.Sqrt(currentEwmaSqReturns);
// Annualize if requested
double result = _annualize ? volatility * Math.Sqrt(_annualPeriods) : volatility;
if (isNew)
{
s.RawRmaSqRet = rawRmaSqRet;
s.BiasE = biasE;
s.PrevClose = safeClose;
s.Count++;
_s = s;
}
if (!double.IsFinite(result))
{
result = 0.0;
}
Last = new TValue(input.Time, result);
PubEvent(Last, isNew);
return Last;
}
///
public override TSeries Update(TSeries source)
{
int len = source.Count;
var t = new List(len);
var v = new List(len);
CollectionsMarshal.SetCount(t, len);
CollectionsMarshal.SetCount(v, len);
var tSpan = CollectionsMarshal.AsSpan(t);
var vSpan = CollectionsMarshal.AsSpan(v);
Batch(source.Values, vSpan, _period, _annualize, _annualPeriods);
source.Times.CopyTo(tSpan);
// Update internal state to match final position
for (int i = 0; i < len; i++)
{
Update(new TValue(source.Times[i], source.Values[i]), isNew: true);
}
return new TSeries(t, v);
}
///
public override void Prime(ReadOnlySpan source, TimeSpan? step = null)
{
for (int i = 0; i < source.Length; i++)
{
Update(new TValue(DateTime.UtcNow, source[i]), isNew: true);
}
}
///
public override void Reset()
{
_s = new State(0.0, 1.0, double.NaN, 0.0, 0);
_ps = _s;
Last = default;
}
///
/// Calculates EWMA Volatility for entire series.
///
public static TSeries Batch(TSeries source, int period = 20, bool annualize = true, int annualPeriods = 252)
{
if (period <= 0)
{
throw new ArgumentException("Period must be greater than 0", nameof(period));
}
if (annualize && annualPeriods <= 0)
{
throw new ArgumentException("Annual periods must be greater than 0 when annualizing", nameof(annualPeriods));
}
int len = source.Count;
var t = new List(len);
var v = new List(len);
CollectionsMarshal.SetCount(t, len);
CollectionsMarshal.SetCount(v, len);
var tSpan = CollectionsMarshal.AsSpan(t);
var vSpan = CollectionsMarshal.AsSpan(v);
Batch(source.Values, vSpan, period, annualize, annualPeriods);
source.Times.CopyTo(tSpan);
return new TSeries(t, v);
}
///
/// Batch EWMA Volatility calculation.
///
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static void Batch(ReadOnlySpan source, Span output, int period = 20, bool annualize = true, int annualPeriods = 252)
{
if (source.Length != output.Length)
{
throw new ArgumentException("Source and output must have the same length", nameof(output));
}
if (period <= 0)
{
throw new ArgumentException("Period must be greater than 0", nameof(period));
}
if (annualize && annualPeriods <= 0)
{
throw new ArgumentException("Annual periods must be greater than 0 when annualizing", nameof(annualPeriods));
}
int len = source.Length;
if (len == 0)
{
return;
}
double alpha = 1.0 / period;
double decay = 1.0 - alpha;
double annualFactor = annualize ? Math.Sqrt(annualPeriods) : 1.0;
double rawRmaSqRet = 0.0;
double biasE = 1.0;
double prevClose = double.NaN;
double lastValidClose = 1.0;
for (int i = 0; i < len; i++)
{
double close = source[i];
// Sanitize input
if (!double.IsFinite(close) || close <= 0)
{
close = lastValidClose;
}
else
{
lastValidClose = close;
}
double safeClose = Math.Max(close, MinPrice);
double safePrevClose = double.IsFinite(prevClose) && prevClose > 0 ? prevClose : safeClose;
// Calculate log return
double logReturn = 0.0;
if (safeClose > 0.0 && safePrevClose > 0.0)
{
logReturn = Math.Log(safeClose / safePrevClose);
}
double squaredReturn = logReturn * logReturn;
// RMA calculation
if (i == 0)
{
rawRmaSqRet = squaredReturn;
biasE = decay;
}
else
{
rawRmaSqRet = Math.FusedMultiplyAdd(rawRmaSqRet, period - 1, squaredReturn) / period;
biasE = decay * biasE;
}
// Bias correction
double biasCorrection = 1.0 - biasE;
double correctedRmaSqRet = biasCorrection > Epsilon ? rawRmaSqRet / biasCorrection : rawRmaSqRet;
// Calculate volatility
double currentEwmaSqReturns = Math.Max(correctedRmaSqRet, 0.0);
double volatility = Math.Sqrt(currentEwmaSqReturns);
double result = volatility * annualFactor;
prevClose = safeClose;
output[i] = double.IsFinite(result) ? result : 0.0;
}
}
public static (TSeries Results, Ewma Indicator) Calculate(TSeries source, int period = 20, bool annualize = true, int annualPeriods = 252)
{
var indicator = new Ewma(period, annualize, annualPeriods);
TSeries results = indicator.Update(source);
return (results, indicator);
}
}