CATEGORY
Volatility nodes
20 Volatility building blocks in the Algovex node library. Each is a node you can drop on the visual canvas, connect into a strategy, backtest and export. No code required.
ATR
Average True Range — measures volatility based on true range. Uses Wilder smoothing. The high_volatility and expanding triggers fire rising-edge when an ADAPTIVE volatility regime (the ATR reading vs its own EMA baseline) first turns high, so they are sparse and meaningful on any instrument or timeframe. Used for stop sizing and volatility filtering.
Bollinger Bands
SMA ± N standard deviations. Shows upper, middle (basis), and lower bands with filled area. Includes %B, bandwidth, and squeeze detection.
Chaikin Volatility
Measures the rate of change of the EMA-smoothed trading range (high minus low). Rising values indicate expanding volatility; falling values indicate contraction.
Donchian Channels
Highest high / lowest low over N bars forming a breakout channel. Used in Turtle trading and trend-following systems.
Donchian Width
Width of the Donchian channel (highest high - lowest low) with percent normalization. Expanding and contracting triggers use an adaptive/relative volatility regime (width vs its own recent baseline with hysteresis), not a fixed bar-to-bar compare.
Garman-Klass Volatility
OHLC-based volatility estimator more efficient than close-to-close.
Historical Volatility
Annualized standard deviation of logarithmic returns. Options-style volatility measurement with an adaptive (relative-to-baseline) regime classification.
Keltner Channels
EMA-based channel with ATR bands. Smoother than Bollinger Bands. Used for trend direction and squeeze detection.
Keltner Width
Width of Keltner Channel as percentage of middle band. The expanding and contracting triggers fire rising-edge off an ADAPTIVE width regime (channel width vs its own EMA baseline), so they are sparse and meaningful on any instrument or timeframe.
NATR
Normalized ATR expressed as percentage of price. Useful for cross-asset volatility comparison.
Parkinson Volatility
Extreme-value volatility estimator using high-low range. More efficient than close-to-close.
Price Envelope
Moving average plus/minus percentage bands. Creates fixed-width channel around MA.
Rogers-Satchell Volatility
Volatility estimator that accounts for drift. More efficient than Parkinson.
Standard Deviation
Price standard deviation over a lookback period. Measures dispersion from mean with Z-score and an ADAPTIVE volatility regime (stddev vs its own EMA baseline). high_vol fires rising-edge when the regime turns high; zscore_extreme fires rising-edge when the Z-score first exceeds the extreme threshold and is direction-coded.
Standard Error Bands
Linear regression channel using standard error. Narrows when price follows regression closely, widens during erratic movement.
STARC Bands
Stoller Average Range Channel: SMA +/- multiplier * ATR.
True Range
Raw (unsmoothed) True Range: max(H-L, |H-prevC|, |L-prevC|).
Volatility Price Channel
HH/LL Donchian channel (lagged by Offset, default 1) with width-as-volatility metrics AND trade triggers: breakout / band_cross on a close beyond the channel, plus squeeze / expansion on the width regime. Also outputs widthRegime, atrNormalizedWidth, widthPercentile, expansionRate for use as a regime filter / confluence input.
Volatility Ratio
VR = TrueRange / EMA(TrueRange). Oscillates around 1.0 with a drawn Expand line (expandThreshold) and a symmetric Contract line (1/expandThreshold). Every trigger fires on a CROSS of one of those visible lines: expansion = cross up through Expand (vol surge), contraction = cross down through Contract (vol drying up), both = either.
Yang-Zhang Volatility
Most efficient combined estimator: overnight + open-to-close + Rogers-Satchell.
Explore other categories