Some Recent Developments in Ambit Stochastics

DOI10.1007/978-3-319-23425-0_1zbMath1382.60003OpenAlexW2229395820MaRDI QIDQ2801788

Emil Hedevang, Benedykt Szozda, Jürgen Schmiegel, Ole Eiler Barndorff-Nielsen

Publication date: 22 April 2016

Published in: Stochastics of Environmental and Financial Economics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/978-3-319-23425-0_1

zbMATH Keywords

turbulenceuniversalityfinancetime-changeextended subordinationambit stochasticsmetatimesstochastic volatility/intermittency

Mathematics Subject Classification ID

Random fields (60G60) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Stochastic models in economics (91B70) Applications of stochastic analysis (to PDEs, etc.) (60H30) Random measures (60G57) Research exposition (monographs, survey articles) pertaining to probability theory (60-02)

Related Items (6)

Volterra-type Ornstein-Uhlenbeck processes in space and time ⋮ Pathwise Decompositions of Brownian Semistationary Processes ⋮ Weak dependence and GMM estimation of supOU and mixed moving average processes ⋮ Lévy-driven causal CARMA random fields ⋮ Hybrid simulation scheme for volatility modulated moving average fields ⋮ Gamma Kernels and BSS/LSS Processes

Cites Work

• The random integral representation conjecture: a quarter of a century later
• Assessing relative volatility/ intermittency/energy dissipation
• Stationary infinitely divisible processes
• Operator-selfdecomposable distributions as limit distributions of processes of Ornstein-Uhlenbeck type
• Infinite divisibility for stochastic processes and time change
• Spectral representations of infinitely divisible processes
• Processes of normal inverse Gaussian type
• Asymptotic theory for Brownian semi-stationary processes with application to turbulence
• Non-Gaussian Ornstein–Uhlenbeck-based Models and Some of Their Uses in Financial Economics
• Integer-valued Trawl Processes: A Class of Stationary Infinitely Divisible Processes
• Change of Time and Change of Measure
• A Stochastic Differential Equation Framework for the Timewise Dynamics of Turbulent Velocities
• Meta-Times and Extended Subordination
• On stochastic integration for volatility modulated Brownian-driven Volterra processes via white noise analysis

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