Volatilitylike
Volatilitylike is a term used in time-series analysis and related disciplines to describe patterns in data that resemble volatility without necessarily implying a formal stochastic volatility process. In practice, volatilitylike describes sequences where the magnitude of fluctuations varies over time in a persistent, sometimes clustered, fashion. The concept emphasizes the observable similarity to volatility in markets or other dynamic systems, while remaining agnostic about the underlying generative mechanism.
Key characteristics typically associated with volatilitylike include clustering of large moves, heavy tails, time-varying dispersion, and
Detection and analysis of volatilitylike rely on measures of variability that adapt over time. Techniques include
Applications of the concept appear in finance, climatology, engineering, and neuroscience, wherever signals display irregular yet