Jump-Diffusion Process
A class of stochastic process models that superimpose discrete jump components onto continuous Brownian motion (diffusion components), used to describe system dynamics characterized by continuous drift and abrupt jumps. The framework is widely applied in financial engineering, physics, and biological modeling.
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The arXiv:2610.09045v1 study proposes using conditional diffusion models to learn the transition kernel of time-homogeneous jump-diffusion processes in a data-driven manner and to generate new sample paths
The latent jump problem exists for jump-diffusion processes under discrete observation settings, making likelihood-based estimation analytically intractable in most cases
All Facts (2)
The arXiv:2610.09045v1 study proposes using conditional diffusion models to learn the transition kernel of time-homogeneous jump-diffusion processes in a data-driven manner and to generate new sample paths
50%UnverifiedThe latent jump problem exists for jump-diffusion processes under discrete observation settings, making likelihood-based estimation analytically intractable in most cases
50%