Parametric inference for nonsynchronously observed diffusion processes in the presence of market microstructure noise

DOI10.3150/17-BEJ962zbMath1415.62064arXiv1412.8173MaRDI QIDQ1750086

Teppei Ogihara

Publication date: 18 May 2018

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1412.8173

zbMATH Keywords

asymptotic efficiencylocal asymptotic normalitydiffusion processesmarket microstructure noiseparametric estimationnonsynchronous observationsBayes-type estimationmaximum-likelihood-type estimation

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Applications of statistics to economics (62P20) Bayesian inference (62F15) Markov processes: estimation; hidden Markov models (62M05) Diffusion processes (60J60)

Related Items (11)

Parametric estimation for a parabolic linear SPDE model based on discrete observations ⋮ Hybrid estimators for stochastic differential equations from reduced data ⋮ On the Asymptotic Structure of Brownian Motions with a Small Lead-Lag Effect ⋮ Malliavin calculus techniques for local asymptotic mixed normality and their application to hypoelliptic diffusions ⋮ Asymptotically efficient estimation for diffusion processes with nonsynchronous observations ⋮ Unnamed Item ⋮ Hybrid estimation for ergodic diffusion processes based on noisy discrete observations ⋮ Misspecified diffusion models with high-frequency observations and an application to neural networks ⋮ Time endogeneity and an optimal weight function in pre-averaging covariance estimation ⋮ Quasi-likelihood analysis and Bayes-type estimators of an ergodic diffusion plus noise ⋮ Estimation of Correlation Between Latent Processes

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