`Purposely misspecified' posterior inference on the volatility of a jump diffusion process

DOI10.1016/j.spl.2017.10.013zbMath1440.62315OpenAlexW2767437812MaRDI QIDQ1698256

Francois Domagni, Ryan Martin, Cheng Ouyang

Publication date: 15 February 2018

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2017.10.013

zbMATH Keywords

Bernstein-von Mises theoremCramér-Rao lower bounduncertainty quantificationcredible intervalGibbs posterior

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Parametric tolerance and confidence regions (62F25) Bayesian inference (62F15) Diffusion processes (60J60) Markov processes: hypothesis testing (62M02) Jump processes on general state spaces (60J76)

Related Items (2)

Bayesian inference on volatility in the presence of infinite jump activity and microstructure noise ⋮ Statistical inference for misspecified ergodic Lévy driven stochastic differential equation models

Cites Work

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• The Bernstein-von Mises theorem under misspecification
• Information-theoretic upper and lower bounds for statistical estimation
• Asymptotic Statistics
• Full Bayesian Analysis for a Class of Jump-Diffusion Models
• A General Framework for Updating Belief Distributions

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