Nonparametric moment method for scalar McKean–Vlasov stochastic differential equations

We study the nonparametric estimation of both the potential and the interaction terms of a scalar McKean–Vlasov stochastic differential equation (SDE) in stationary regime from a continuous observation on a time interval [0, T], with asymptotic framework T → +∞. To estimate the two functions, we consider the observation of four i.i.d. sample paths. The observation of two sample paths could be enough at the cost of much more computations. Estimators of the potential and the interaction functions are built using a combination of a moment method and a projection method on sieves. The potential and the interaction term do not belong to 𝕃2(ℝ), so we define a specific risk fitted to this estimation problem and obtain a bound for it. A nonparametric estimator of the invariant density also is proposed. The method is implemented on simulated data for several examples of McKean–Vlasov SDEs and a model selection procedure is experimented.

Publication Details

Journal
Springer Link (Chiba Institute of Technology)
Published
2025-09-22
DOI
https://doi.org/10.1051/ps/2025012/pdf
Primary Topic
Stochastic processes and financial applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Nonparametric moment method for scalar McKean–Vlasov stochastic differential equations

Springer Link (Chiba Institute of Technology)
Stochastic processes and financial applications
article

Nonparametric moment method for scalar McKean–Vlasov stochastic differential equations

article en

Abstract

We study the nonparametric estimation of both the potential and the interaction terms of a scalar McKean–Vlasov stochastic differential equation (SDE) in stationary regime from a continuous observation on a time interval [0, T], with asymptotic framework T → +∞. To estimate the two functions, we consider the observation of four i.i.d. sample paths. The observation of two sample paths could be enough at the cost of much more computations. Estimators of the potential and the interaction functions are built using a combination of a moment method and a projection method on sieves. The potential and the interaction term do not belong to 𝕃2(ℝ), so we define a specific risk fitted to this estimation problem and obtain a bound for it. A nonparametric estimator of the invariant density also is proposed. The method is implemented on simulated data for several examples of McKean–Vlasov SDEs and a model selection procedure is experimented.

Springer Link (Chiba Institute of Technology)
Openalex Percentile: Top 50%
Stochastic processes and financial applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.