Stochastic tail index model for high frequency financial data with Bayesian analysis

DOI10.1016/j.jeconom.2018.03.019zbMath1452.62781OpenAlexW2802174541WikidataQ129915196 ScholiaQ129915196MaRDI QIDQ1644258

Zhengjun Zhang, Guangyu Mao

Publication date: 21 June 2018

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jeconom.2018.03.019

zbMATH Keywords

extreme valuesBayesian statisticstail indexstate space modelhigh frequency

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Bayesian inference (62F15) Statistics of extreme values; tail inference (62G32)

Related Items

On studying extreme values and systematic risks with nonlinear time series models and tail dependence measures ⋮ Rejoinder of “On studying extreme values and systematic risks with nonlinear time series models and tail dependence measures” ⋮ New extreme value theory for maxima of maxima ⋮ Adaptive robust large volatility matrix estimation based on high-frequency financial data ⋮ Dynamic tail inference with log-Laplace volatility ⋮ Volatility models for stylized facts of high‐frequency financial data

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