An extended sparse max-linear moving model with application to high-frequency financial data
From MaRDI portal
Publication:5880168
DOI10.1080/24754269.2017.1346852OpenAlexW3121687452MaRDI QIDQ5880168
Publication date: 7 March 2023
Published in: Statistical Theory and Related Fields (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/24754269.2017.1346852
time seriesextreme value theoryBayesian inferencemax-stable processeshigh-frequency financial datamax-linear models
Related Items (3)
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
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Large Sample Properties of Generalized Method of Moments Estimators
- Copula structured M4 processes with application to high-frequency financial data
- Bivariate extreme statistics. I
- Asymptotically (in)dependent multivariate maxima of moving maxima process
- Extremal financial risk models and portfolio evaluation
- Point processes and multivariate extreme values
- Moving-maximum models for extrema of time series
- Sparse moving maxima models for tail dependence in multivariate financial time series
- On the estimation and application of max-stable processes
- Sur la distribution limite du terme maximum d'une série aléatoire
- Efficient estimation and particle filter for max-stable processes
- Basic properties and prediction of max-ARMA processes
- Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
- Diagnostics for Dependence within Time Series Extremes
- Equation of State Calculations by Fast Computing Machines
- Monte Carlo sampling methods using Markov chains and their applications
This page was built for publication: An extended sparse max-linear moving model with application to high-frequency financial data
