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PreprintarXiv licencearXiv

Model-based clustering of diffusion processes with constant volatility coefficients using high-frequency data

Abstract

This paper considers model-based clustering of diffusion processes using high-frequency data. We formulate a finite mixture model for diffusion processes and develop a clustering method based on their constant diffusion coefficients. Using a quasi-likelihood, we propose estimators of the number of clusters, the diffusion coefficients and the cluster labels, and establish their consistency and the asymptotic normality of the diffusion coefficient estimators under high-frequency asymptotics with the number of observed processes fixed. Simulation studies are conducted to investigate the finite-sample performance of the proposed method.

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BibTeX
@misc{kusano2026modelbased,
  title = {{Model-based clustering of diffusion processes with constant volatility coefficients using high-frequency data}},
  author = {Shogo Kusano and Masayuki Uchida},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.37514},
  eprint = {2610.37514},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.37514},
}
RIS
TY  - UNPB
TI  - Model-based clustering of diffusion processes with constant volatility coefficients using high-frequency data
AU  - Shogo Kusano
AU  - Masayuki Uchida
PY  - 2026
DA  - 2026/10/27
PB  - arXiv
DO  - 10.48550/arxiv.2610.37514
UR  - https://arxiv.org/abs/2610.37514
AB  - This paper considers model-based clustering of diffusion processes using high-frequency data. We formulate a finite mixture model for diffusion processes and develop a clustering method based on their constant diffusion coefficients. Using a quasi-likelihood, we propose estimators of the number of clusters, the diffusion coefficients and the cluster labels, and establish their consistency and the asymptotic normality of the diffusion coefficient estimators under high-frequency asymptotics with the number of observed processes fixed. Simulation studies are conducted to investigate the finite-sample performance of the proposed method.
ER  -