Some properties of stochastic volatility model that are induced by its volatility sequence

DOI10.1016/j.stamet.2014.11.002zbMath1486.62274OpenAlexW2028555186MaRDI QIDQ1731258

Narayanaswamy Balakrishnan, Mohsen Rezapour

Publication date: 13 March 2019

Published in: Statistical Methodology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.stamet.2014.11.002

zbMATH Keywords

stochastic volatilitypoint processstationary processmixing conditionfinanceheavy tailvague convergencemultivariate regular variationexponential AR(2) process

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistics of extreme values; tail inference (62G32) Stochastic models in economics (91B70) Interest rates, asset pricing, etc. (stochastic models) (91G30) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Cites Work

• Unnamed Item
• Unnamed Item
• Random difference equations and renewal theory for products of random matrices
• Mixing: Properties and examples
• Regular variation of GARCH processes.
• Point process and partial sum convergence for weakly dependent random variables with infinite variance
• Stochastic volatility models with possible extremal clustering
• Handbook of Financial Time Series
• Extremes of Stochastic Volatility Models
• Heavy-Tail Phenomena