New and fast block bootstrap-based prediction intervals for GARCH(1,1) process with application to exchange rates

DOI10.1007/s13171-017-0098-2zbMath1387.62098OpenAlexW2616159918MaRDI QIDQ1744731

Xianqiang Yang

Publication date: 19 April 2018

Published in: Sankhyā. Series A (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s13171-017-0098-2

zbMATH Keywords

predictionSpearman's rank correlationfinancial time seriesresampling methods

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to actuarial sciences and financial mathematics (62P05) Nonparametric statistical resampling methods (62G09)

Related Items (4)

Robust bootstrap prediction intervals for univariate and multivariate autoregressive time series models ⋮ Construction of multi-step forecast regions of VAR processes using ordered block bootstrap ⋮ Bootstrap based multi-step ahead joint forecast densities for financial interval-valued time series ⋮ Testing for local covariate trend effects in volatility models

Uses Software

• dtw

Cites Work

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