Work

Statistical inference for ergodic diffusion with Markovian switching

Year: 2025

Type: article

Abstract: This study explores a Gaussian quasi-likelihood approach for estimating parameters of diffusion processes with Markovian regime switching. Assuming the ergodicity under high-frequency sampling, we will show the asymptotic normality of the unknown parameters contained in the drift and diffusion coefficients and present a consistent explicit estimator for the generator of the Markov chain. Simulation experiments are conducted to illustrate the theoretical results obtained.

Source: Discrete and Continuous Dynamical Systems - B

DOI: 10.3934/dcdsb.2025056

Authors: Yuzhong Cheng, Hiroki Masuda

Institutions: Kyushu University, The University of Tokyo

Language: English

Topic: Stochastic processes and financial applications

Subfield: Finance

Field: Economics, Econometrics and Finance

Domain: Social Sciences

Open Access status: diamond

Funders: Ministry of Education, Culture, Sports, Science and Technology, Japan Society for the Promotion of Science, Core Research for Evolutional Science and Technology

Awards: Deepening and developing statistical theory for dependent data based on Levy noise, G6718509927, G7879866177, G7939374355