Fractional interacting particle system: Drift parameter estimation via Malliavin calculus

We address the problem of estimating the drift parameter in a system of N interacting particles driven by additive fractional Brownian motion of Hurst index H ≥ 1/2. Considering continuous observation of the interacting particles over a fixed interval [0, T ], we examine the asymptotic regime as N → ∞. Our main tool is a random variable reminiscent of the least squares estimator but unobservable due to its reliance on the Skorohod integral. We demonstrate that this object is consistent and asymptotically normal by establishing a quantitative propagation of chaos for Malliavin derivatives, which holds for any H ∈ (0, 1). Leveraging a connection between the divergence integral and the Young integral, we construct computable estimators of the drift parameter. These estimators are shown to be consistent and asymptotically Gaussian. Finally, a numerical study highlights the strong performance of the proposed estimators.

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Publication Details

Journal
Stochastic Processes and their Applications
Published
2025-12-25
DOI
https://doi.org/10.1016/j.spa.2025.104857
Primary Topic
Fractional Differential Equations Solutions
Type
article
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article

Fractional interacting particle system: Drift parameter estimation via Malliavin calculus

Ivan Nourdin, Chiara Amorino, Radomyra Shevchenko
Stochastic Processes and their Applications
Fractional Differential Equations Solutions
article

Fractional interacting particle system: Drift parameter estimation via Malliavin calculus

Ivan Nourdin, Chiara Amorino, Radomyra Shevchenko
article en

Abstract

We address the problem of estimating the drift parameter in a system of N interacting particles driven by additive fractional Brownian motion of Hurst index H ≥ 1/2. Considering continuous observation of the interacting particles over a fixed interval [0, T ], we examine the asymptotic regime as N → ∞. Our main tool is a random variable reminiscent of the least squares estimator but unobservable due to its reliance on the Skorohod integral. We demonstrate that this object is consistent and asymptotically normal by establishing a quantitative propagation of chaos for Malliavin derivatives, which holds for any H ∈ (0, 1). Leveraging a connection between the divergence integral and the Young integral, we construct computable estimators of the drift parameter. These estimators are shown to be consistent and asymptotically Gaussian. Finally, a numerical study highlights the strong performance of the proposed estimators.

Stochastic Processes and their ApplicationsVol. 195
Centre National de la Recherche Scientifique (FR), Universitat Pompeu Fabra (ES), University of Luxembourg (LU), Laboratoire Jean-Alexandre Dieudonné (FR), Barcelona School of Economics (ES)
Openalex Percentile: Top 34%
Fractional Differential Equations Solutions
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Fractional interacting particle system: Drift parameter estimation via Malliavin calculus — Ivan Nourdin, Chiara Amorino, et al. · Stochastic Processes and their Applications (2025) | TGRS Research Map | TGRS