Superpositions of CARMA processes

We introduce supCARMA processes, defined as superpositions of Lévy-driven CARMA processes with respect to a Lévy basis, as a natural extension of the superpositions of Ornstein-Uhlenbeck type processes. We then focus on supCAR$(2)$ processes and show that they can be classified into three distinct types determined by the eigenstructure of the underlying CAR$(2)$ matrix. For each type we provide conditions for existence and derive explicit expressions for the correlation function. The resulting correlation structures may exhibit long-range dependence and can be non-monotone. These features make supCAR$(2)$ processes a flexible class for modeling time series with oscillatory correlations or strong dependence.

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Publication Details

Journal
Stochastic Analysis and Applications
Published
2026-09-16
DOI
https://doi.org/10.1080/07362994.2026.2723204
Primary Topic
Financial Risk and Volatility Modeling
Type
article
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article

Superpositions of CARMA processes

Danijel Grahovac, Magdalena Mikić
Stochastic Analysis and Applications
Financial Risk and Volatility Modeling
article

Superpositions of CARMA processes

Danijel Grahovac, Magdalena Mikić
article en

Abstract

We introduce supCARMA processes, defined as superpositions of Lévy-driven CARMA processes with respect to a Lévy basis, as a natural extension of the superpositions of Ornstein-Uhlenbeck type processes. We then focus on supCAR$(2)$ processes and show that they can be classified into three distinct types determined by the eigenstructure of the underlying CAR$(2)$ matrix. For each type we provide conditions for existence and derive explicit expressions for the correlation function. The resulting correlation structures may exhibit long-range dependence and can be non-monotone. These features make supCAR$(2)$ processes a flexible class for modeling time series with oscillatory correlations or strong dependence.

Stochastic Analysis and Applications
Applied Mathematics (United States) (US), University of Osijek (HR)
Openalex Percentile: Top 93%
Financial Risk and Volatility Modeling
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