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September 10, 2026Stochastic Systems2 citationsOpen Access

State Spaces of Multifactor Approximations of Nonnegative Volterra Processes

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EJEduardo Abi JaberCBChristian BayerSBSimon Breneis

Key Points

  • Characterize the state spaces of multifactor Markovian systems that approximate nonnegative Volterra processes and determine their geometric structure.
  • Analyzed the mathematical structure and domain constraints of multifactor Markovian approximations derived from nonnegative Volterra systems.
  • Formulated explicit coordinate transformations connecting the system state spaces to the standard nonnegative orthant.
  • Proved that the state spaces of these multifactor Markovian approximations are explicit linear transformations of the nonnegative orthant.
  • Demonstrated practical utility by establishing direct applications to stochastic simulation schemes and partial differential equation methods for nonnegative Volterra processes.

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.

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Cite This Study

Jaber et al. (2026) studied this question.

synapsesocial.com/papers/6aa27a0b58559d80afc72a92https://doi.org/10.1287/stsy.2025.0101
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