Stochastic Systems· 2026Q1
State Spaces of Multifactor Approximations of Nonnegative Volterra Processes
- 2citations
- Q1SCImago
- 2026year
Short summary
The state spaces of multifactor Markovian processes approximating nonnegative Volterra processes are shown to be explicit linear transformations of the nonnegative orthant.
AI-generated from the title and abstract; the full text is not read.
Key points
- Identifies the structure of state spaces for multifactor Markovian approximations of nonnegative Volterra processes.
- Demonstrates these state spaces are linear transformations of the nonnegative orthant.
- Highlights the utility of this result for simulation and PDE methods.
AI-generated from the title and abstract; the full text is not read.
Abstract
We show that the state spaces of multifactor Markovian processes, coming from approximations of nonnegative Volterra processes, are given by explicit linear transformations of the nonnegative orthant. We demonstrate the usefulness of this result for applications, including simulation schemes and partial differential equation methods for nonnegative Volterra processes. Funding: E. Abi Jaber gratefully acknowledges financial support from the Chaires Laboratoire de Finance des Marchés de l’Énergie-Finance et Développement Durable and Financial Risks at École Polytechnique. C. Bayer and S. Breneis gratefully acknowledge the support by the International Research Training Group 2544 “Stochastic Analysis in Interaction.” C. Bayer also acknowledges support from Deutsche Forschungsgemeinschaft Collaborative Research Center/Transregio 388 “Rough Analysis, Stochastic Dynamics and Related Fields” [Project B02].
The authors' abstract, as published at the source. Stochastic Systems, 2026 · DOI ↗
Continue with a free account
Ask the paper: 3 free questions a day about this paper; save it, get its citation, new summaries every day for your field. Takeaways are Premium.
Continue free on the webSign in with Google or Apple; no card needed. You come back to this paper.
On your phone:
Field: Control and Systems Engineering
Control and Systems EngineeringEngineering