Chaptergreen2011

Ambit Processes and Stochastic Partial Differential Equations

Ole Eiler Barndorff-Nielsen · Fred Espen Benth · Almut E. D. Veraart

50 citations0/0 files storedSpringer eBooks

No readable copy stored yet — this record is metadata only.

Stochastic processes and financial applications Nonlinear Differential Equations Analysis Stochastic processes and statistical mechanics

Abstract

Ambit processes are general stochastic processes based on stochastic integrals with respect to Lévy bases. Due to their flexible structure, they have great potential for providing realistic models for various applications such as in turbulence and finance. This papers studies the connection between ambit processes and solutions to stochastic partial differential equations. We investigate this relationship from two angles: from the Walsh theory of martingale measures and from the viewpoint of the Lévy noise analysis.

Citations in this library

Stored only when both papers are in the corpus — 50 citations exist upstream.

References

2006An introduction to stochastic partial differential equations 2015Proof that Properly Anticipated Prices Fluctuate Randomly 2004Power and Bipower Variation with Stochastic Volatility and Jumps 2007Stochastic Partial Differential Equations with Levy Noise 1997Stochastic Partial Differential Equations: A Modeling, White Noise Functional Approach.2007Asymptotic properties of realized power variations and related functionals of semimartingales 2006A Central Limit Theorem for Realised Power and Bipower Variations of Continuous Semimartingales 2006Limit theorems for multipower variation in the presence of jumps

Cited by

2014Modelling Electricity Futures by Ambit Fields 2021Linear-quadratic control for a class of stochastic Volterra equations: Solvability and approximation 2014Integer‐valued Trawl Processes: A Class of Stationary Infinitely Divisible Processes

Imported from OpenAlex (CC0) — nothing here is generated.