// Relative Volatility Index (RVI) Indicator — Revised (1995) version // Averages original RVI computed on High and Low series separately using System.Runtime.CompilerServices; using System.Runtime.InteropServices; namespace QuanTAlib; /// /// RVI: Relative Volatility Index (Revised) /// Computes original RVI on the High series and on the Low series, then averages. /// Each channel classifies stddev direction based on its own price change. /// /// /// Calculation steps (per channel — High and Low independently): /// /// Calculate population standard deviation over stdevLength /// Classify by price change: if up, upStd = stddev; if down, downStd = stddev /// Smooth upStd and downStd with RMA (Wilder's smoothing with bias correction) /// channelRVI = 100 × avgUpStd / (avgUpStd + avgDownStd) /// /// Final: RVI = (RVI_high + RVI_low) / 2 /// /// Sources: /// Donald Dorsey (1993, original; 1995, revised). Technical Analysis of Stocks & Commodities. /// FM Labs: https://www.fmlabs.com/reference/RVI.htm /// [SkipLocalsInit] public sealed class Rvi : AbstractBase { private const double Epsilon = 1e-10; private readonly int _stdevLength; private readonly int _rmaLength; private readonly double _alpha; private readonly RingBuffer _hiBuf; private readonly RingBuffer _loBuf; [StructLayout(LayoutKind.Auto)] private record struct ChState( double PrevPrice, double Sum, double SumSq, double RawRmaUp, double EUp, double RawRmaDown, double EDown, int FillCount ); private ChState _hi, _phi; private ChState _lo, _plo; private double _lastValue, _pLastValue; public Rvi(int stdevLength = 10, int rmaLength = 14) { if (stdevLength < 2) { throw new ArgumentException("Standard deviation length must be at least 2", nameof(stdevLength)); } if (rmaLength < 1) { throw new ArgumentException("RMA length must be at least 1", nameof(rmaLength)); } _stdevLength = stdevLength; _rmaLength = rmaLength; _alpha = 1.0 / rmaLength; _hiBuf = new RingBuffer(stdevLength); _loBuf = new RingBuffer(stdevLength); WarmupPeriod = stdevLength + rmaLength; Name = $"Rvi({stdevLength},{rmaLength})"; var init = new ChState(double.NaN, 0, 0, 0, 1.0, 0, 1.0, 0); _hi = _phi = init; _lo = _plo = init; _lastValue = _pLastValue = 50.0; } public Rvi(ITValuePublisher source, int stdevLength = 10, int rmaLength = 14) : this(stdevLength, rmaLength) { source.Pub += Handle; } private void Handle(object? sender, in TValueEventArgs e) => Update(e.Value, e.IsNew); public override bool IsHot => _hi.FillCount >= _stdevLength; public int StdevLength => _stdevLength; public int RmaLength => _rmaLength; [MethodImpl(MethodImplOptions.AggressiveInlining)] public override TValue Update(TValue input, bool isNew = true) { return UpdateCore(input.Time, input.Value, input.Value, isNew); } [MethodImpl(MethodImplOptions.AggressiveInlining)] public TValue Update(TBar bar, bool isNew = true) { return UpdateCore(bar.Time, bar.High, bar.Low, isNew); } public TSeries Update(TBarSeries source) { if (source.Count == 0) { return []; } 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); Span highs = len <= 128 ? stackalloc double[len] : new double[len]; Span lows = len <= 128 ? stackalloc double[len] : new double[len]; for (int i = 0; i < len; i++) { highs[i] = source[i].High; lows[i] = source[i].Low; tSpan[i] = source[i].Time; } BatchDual(highs, lows, vSpan, _stdevLength, _rmaLength); // Sync internal state for (int i = 0; i < len; i++) { Update(source[i], isNew: true); } return new TSeries(t, v); } public override TSeries Update(TSeries source) { if (source.Count == 0) { return []; } 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); // Single-price series: same value to both channels Batch(source.Values, vSpan, _stdevLength, _rmaLength); source.Times.CopyTo(tSpan); for (int i = 0; i < len; i++) { Update(new TValue(source.Times[i], source.Values[i]), isNew: true); } return new TSeries(t, v); } [MethodImpl(MethodImplOptions.AggressiveInlining)] private TValue UpdateCore(long timeTicks, double hiPrice, double loPrice, bool isNew) { if (isNew) { _phi = _hi; _plo = _lo; _pLastValue = _lastValue; _hiBuf.Snapshot(); _loBuf.Snapshot(); } else { _hi = _phi; _lo = _plo; _lastValue = _pLastValue; _hiBuf.Restore(); _loBuf.Restore(); } // Handle non-finite if (!double.IsFinite(hiPrice) || !double.IsFinite(loPrice)) { Last = new TValue(timeTicks, _lastValue); PubEvent(Last, isNew); return Last; } double rviHi = UpdateChannel(ref _hi, _hiBuf, hiPrice); double rviLo = UpdateChannel(ref _lo, _loBuf, loPrice); double rviValue = (rviHi + rviLo) * 0.5; if (!double.IsFinite(rviValue)) { rviValue = _lastValue; } else { _lastValue = rviValue; } Last = new TValue(timeTicks, rviValue); PubEvent(Last, isNew); return Last; } [MethodImpl(MethodImplOptions.AggressiveInlining)] private double UpdateChannel(ref ChState s, RingBuffer buf, double price) { if (double.IsNaN(s.PrevPrice)) { buf.Add(price); s = s with { PrevPrice = price, Sum = price, SumSq = price * price, FillCount = 1 }; return 50.0; } double priceChange = price - s.PrevPrice; double oldSum = s.Sum; double oldSumSq = s.SumSq; int oldCount = s.FillCount; if (buf.Count == _stdevLength) { double oldest = buf[0]; oldSum -= oldest; oldSumSq -= oldest * oldest; oldCount--; } buf.Add(price); double newSum = oldSum + price; double newSumSq = oldSumSq + (price * price); int newCount = oldCount + 1; double currentStdDev = 0.0; if (newCount > 1) { double mean = newSum / newCount; double variance = (newSumSq / newCount) - (mean * mean); variance = Math.Max(0.0, variance); currentStdDev = Math.Sqrt(variance); } double upStdVal = 0.0; double downStdVal = 0.0; if (priceChange > 0) { upStdVal = currentStdDev; } else if (priceChange < 0) { downStdVal = currentStdDev; } double rawRmaUp = Math.FusedMultiplyAdd(s.RawRmaUp, _rmaLength - 1, upStdVal) / _rmaLength; double eUp = (1 - _alpha) * s.EUp; double avgUpStd = eUp > Epsilon ? rawRmaUp / (1.0 - eUp) : rawRmaUp; double rawRmaDown = Math.FusedMultiplyAdd(s.RawRmaDown, _rmaLength - 1, downStdVal) / _rmaLength; double eDown = (1 - _alpha) * s.EDown; double avgDownStd = eDown > Epsilon ? rawRmaDown / (1.0 - eDown) : rawRmaDown; double sumAvgStd = avgUpStd + avgDownStd; double rvi = sumAvgStd > Epsilon ? (100.0 * avgUpStd / sumAvgStd) : 50.0; s = new ChState(price, newSum, newSumSq, rawRmaUp, eUp, rawRmaDown, eDown, newCount); return rvi; } 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() { var init = new ChState(double.NaN, 0, 0, 0, 1.0, 0, 1.0, 0); _hi = _phi = init; _lo = _plo = init; _lastValue = _pLastValue = 50.0; _hiBuf.Clear(); _loBuf.Clear(); Last = default; } // --- Static Batch methods --- /// /// Batch RVI for a single-price series (same value to both channels → original behavior). /// public static TSeries Batch(TSeries source, int stdevLength = 10, int rmaLength = 14) { if (stdevLength < 2) { throw new ArgumentException("Standard deviation length must be at least 2", nameof(stdevLength)); } if (rmaLength < 1) { throw new ArgumentException("RMA length must be at least 1", nameof(rmaLength)); } int len = source.Count; var t = new List(len); var v = new List(len); CollectionsMarshal.SetCount(t, len); CollectionsMarshal.SetCount(v, len); Batch(source.Values, CollectionsMarshal.AsSpan(v), stdevLength, rmaLength); source.Times.CopyTo(CollectionsMarshal.AsSpan(t)); return new TSeries(t, v); } /// /// Batch RVI for a bar series (revised: high+low average). /// public static TSeries Batch(TBarSeries source, int stdevLength = 10, int rmaLength = 14) { var rvi = new Rvi(stdevLength, rmaLength); return rvi.Update(source); } /// /// Span-based batch for single-price series. Same price to both channels → original behavior. /// public static void Batch( ReadOnlySpan prices, Span output, int stdevLength = 10, int rmaLength = 14) { if (stdevLength < 2) { throw new ArgumentException("Standard deviation length must be at least 2", nameof(stdevLength)); } if (rmaLength < 1) { throw new ArgumentException("RMA length must be at least 1", nameof(rmaLength)); } if (output.Length < prices.Length) { throw new ArgumentException("Output span must be at least as long as prices span", nameof(output)); } // Single-price: feed same data to both channels, average = original BatchDual(prices, prices, output, stdevLength, rmaLength); } /// /// Span-based batch for dual-channel (high + low) revised RVI. /// public static void BatchDual( ReadOnlySpan highs, ReadOnlySpan lows, Span output, int stdevLength = 10, int rmaLength = 14) { if (stdevLength < 2) { throw new ArgumentException("Standard deviation length must be at least 2", nameof(stdevLength)); } if (rmaLength < 1) { throw new ArgumentException("RMA length must be at least 1", nameof(rmaLength)); } int len = highs.Length; if (len == 0) { return; } if (output.Length < len) { throw new ArgumentException("Output span must be at least as long as input span", nameof(output)); } // Allocate temp buffers for each channel's RVI output Span rviHi = len <= 256 ? stackalloc double[len] : new double[len]; Span rviLo = len <= 256 ? stackalloc double[len] : new double[len]; BatchSingleChannel(highs, rviHi, stdevLength, rmaLength); BatchSingleChannel(lows, rviLo, stdevLength, rmaLength); // Average for (int i = 0; i < len; i++) { output[i] = (rviHi[i] + rviLo[i]) * 0.5; } } /// /// Computes original (single-channel) RVI for one price series. /// private static void BatchSingleChannel( ReadOnlySpan prices, Span output, int stdevLength, int rmaLength) { int len = prices.Length; if (len == 0) { return; } double alpha = 1.0 / rmaLength; Span priceBuffer = stdevLength <= 256 ? stackalloc double[stdevLength] : new double[stdevLength]; int head = 0; int count = 0; double sum = 0; double sumSq = 0; double prevPrice = double.NaN; double lastValue = 50.0; double rawRmaUp = 0; double eUp = 1.0; double rawRmaDown = 0; double eDown = 1.0; for (int i = 0; i < len; i++) { double price = prices[i]; if (double.IsNaN(prevPrice)) { if (!double.IsFinite(price)) { output[i] = lastValue; continue; } if (count < stdevLength) { count++; } else { double oldest = priceBuffer[head]; sum -= oldest; sumSq -= oldest * oldest; } priceBuffer[head] = price; head = (head + 1) % stdevLength; sum += price; sumSq += price * price; prevPrice = price; output[i] = 50.0; continue; } if (!double.IsFinite(price)) { output[i] = lastValue; continue; } double priceChange = price - prevPrice; prevPrice = price; if (count < stdevLength) { count++; } else { double oldest = priceBuffer[head]; sum -= oldest; sumSq -= oldest * oldest; } priceBuffer[head] = price; head = (head + 1) % stdevLength; sum += price; sumSq += price * price; double currentStdDev = 0.0; if (count > 1) { double mean = sum / count; double variance = (sumSq / count) - (mean * mean); variance = Math.Max(0.0, variance); currentStdDev = Math.Sqrt(variance); } double upStdVal = 0.0; double downStdVal = 0.0; if (priceChange > 0) { upStdVal = currentStdDev; } else if (priceChange < 0) { downStdVal = currentStdDev; } rawRmaUp = Math.FusedMultiplyAdd(rawRmaUp, rmaLength - 1, upStdVal) / rmaLength; eUp = (1 - alpha) * eUp; double avgUpStd = eUp > Epsilon ? rawRmaUp / (1.0 - eUp) : rawRmaUp; rawRmaDown = Math.FusedMultiplyAdd(rawRmaDown, rmaLength - 1, downStdVal) / rmaLength; eDown = (1 - alpha) * eDown; double avgDownStd = eDown > Epsilon ? rawRmaDown / (1.0 - eDown) : rawRmaDown; double sumAvgStd = avgUpStd + avgDownStd; double rviValue = sumAvgStd > Epsilon ? (100.0 * avgUpStd / sumAvgStd) : 50.0; if (!double.IsFinite(rviValue)) { rviValue = lastValue; } else { lastValue = rviValue; } output[i] = rviValue; } } public static (TSeries Results, Rvi Indicator) Calculate(TSeries source, int stdevLength = 10, int rmaLength = 14) { var indicator = new Rvi(stdevLength, rmaLength); TSeries results = indicator.Update(source); return (results, indicator); } }