Misspecified diffusion models with high-frequency observations and an application to neural networks

DOI10.1016/j.spa.2021.08.007zbMath1476.62191arXiv1912.11832OpenAlexW3198746028MaRDI QIDQ2239259

Teppei Ogihara

Publication date: 3 November 2021

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1912.11832

zbMATH Keywords

neural networkdiffusion processeshigh-frequency datamarket microstructure noisemisspecified modelmaximum-likelihood-type estimation

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Artificial neural networks and deep learning (68T07) Diffusion processes (60J60) Neural nets and related approaches to inference from stochastic processes (62M45)

Related Items (1)

Drift estimation for a multi-dimensional diffusion process using deep neural networks

Uses Software

• ADADELTA

Cites Work

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