Journal of Time Series Analysis

1980 - 2022

Current editor(s): M.B. Priestley

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Volume 43, issue 3, 2022

A new volatility model: GQARCH‐ItÔ model pp. 345-370

Huiling Yuan, Yulei Sun, Lu Xu, Yong Zhou and Xiangyu Cui

Asymmetric linear double autoregression pp. 371-388

Songhua Tan and Qianqian Zhu

Structural change tests under heteroskedasticity: Joint estimation versus two‐steps methods pp. 389-411

Pierre Perron and Yohei Yamamoto

On cointegration for processes integrated at different frequencies pp. 412-435

Tomás del Barrio Castro, Gianluca Cubadda and Denise R. Osborn

Stationarity and ergodicity of Markov switching positive conditional mean models pp. 436-459

Abdelhakim Aknouche and Christian Francq

Modeling normalcy‐dominant ordinal time series: An application to air quality level pp. 460-478

Mengya Liu, Fukang Zhu and Ke Zhu

The spectral analysis of the Hodrick–Prescott filter pp. 479-489

Neslihan Sakarya and Robert M. de Jong

A new GJR‐GARCH model for ℤ‐valued time series pp. 490-500

Yue Xu and Fukang Zhu

The factor analytical approach in trending near unit root panels pp. 501-508

Joakim Westerlund, Milda Norkutė and Ovidijus Stauskas

Volume 43, issue 2, 2022

Autoregressive density modeling with the Gaussian process mixture transition distribution pp. 157-177

Matthew Heiner and Athanasios Kottas

On causal and non‐causal cointegrated vector autoregressive time series pp. 178-196

Anders Rygh Swensen

Seasonal functional autoregressive models pp. 197-218

Atefeh Zamani, Hossein Haghbin, Maryam Hashemi and Rob Hyndman

A two‐step procedure for testing partial parameter stability in cointegrated regression models pp. 219-237

Mohitosh Kejriwal, Pierre Perron and Xuewen Yu

Maxima of linear processes with heavy‐tailed innovations and random coefficients pp. 238-262

Danijel Krizmanić

Regular multidimensional stationary time series pp. 263-284

Tamás Szabados

Generalized binary vector autoregressive processes pp. 285-311

Carsten Jentsch and Lena Reichmann

Variable length Markov chain with exogenous covariates pp. 312-328

Adriano Zanin Zambom, Seonjin Kim and Nancy Lopes Garcia

Autoregressive spectral estimates under ignored changes in the mean pp. 329-340

Matei Demetrescu and Mehdi Hosseinkouchack

TIME SERIES: A FIRST COURSE WITH BOOTSTRAP STARTER, by Tucker S.McElroy and Dimitris N.Politis. Published by CRC Press, 2020. 586 pp. ISBN: 9781439876510 pp. 341-342

Alexander Aue

Volume 43, issue 1, 2022

Editorial Announcement: Professor Michael McAleer pp. 3-3

Robert Taylor

Editorial Announcement: Journal of Time Series Analysis Distinguished Authors 2021 pp. 4-4

Robert Taylor

Periodic autoregressive conditional duration pp. 5-29

Abdelhakim Aknouche, Bader Almohaimeed and Stefanos Dimitrakopoulos

Wasserstein autoregressive models for density time series pp. 30-52

Chao Zhang, Piotr Kokoszka and Alexander Petersen

Double Smoothed Volatility Estimation of Potentially Non‐stationary Jump‐diffusion Model of Shibor pp. 53-82

Yuping Song, Weijie Hou and Zhengyan Lin

Oracle Efficient Estimation of Structural Breaks in Cointegrating Regressions pp. 83-104

Karsten Schweikert

State Heterogeneity Analysis of Financial Volatility using high‐frequency Financial Data pp. 105-124

Dohyun Chun and Donggyu Kim

Generalized autoregressive moving average models with GARCH errors pp. 125-146

Tingguo Zheng, Han Xiao and Rong Chen

On the Relationship between Uhlig Extended and beta‐Bartlett Processes pp. 147-153

Víctor Peña and Kaoru Irie

Review of the book Stochastic Models for Time Series by Paul Doukhan pp. 154-154

Efstathios Paparoditis

Volume 42, issue 5-6, 2021

Preface to the Murray Rosenblatt memorial special issue of JTSA pp. 495-498

Richard C. Bradley, Richard A. Davis and Dimitris N. Politis

On some basic features of strictly stationary, reversible Markov chains pp. 499-533

Richard C. Bradley

Simultaneous inference for autocovariances based on autoregressive sieve bootstrap pp. 534-553

Alexander Braumann, Jens‐Peter Kreiss and Marco Meyer

Sparsity concepts and estimation procedures for high‐dimensional vector autoregressive models pp. 554-579

Jonas Krampe and Efstathios Paparoditis

Consistent autoregressive spectral estimates: Nonlinear time series and large autocovariance matrices pp. 580-596

Jiang Wang and Dimitris N. Politis

Spectral methods for small sample time series: A complete periodogram approach pp. 597-621

Sourav Das, Suhasini Subba Rao and Junho Yang

Extensions of Rosenblatt's results on the asymptotic behavior of the prediction error for deterministic stationary sequences pp. 622-652

Nikolay M. Babayan, Mamikon S. Ginovyan and Murad S. Taqqu

Indirect inference for time series using the empirical characteristic function and control variates pp. 653-684

Richard A. Davis, Thiago do Rêgo Sousa and Claudia Klüppelberg

Local Whittle estimation of long‐range dependence for functional time series pp. 685-695

Degui Li, Peter M. Robinson and Han Lin Shang

A local limit theorem for linear random fields pp. 696-710

Timothy Fortune, Magda Peligrad and Hailin Sang

On the Estimation of Periodicity or Almost Periodicity in Inhomogeneous Gamma Point‐Process Data pp. 711-736

Rodrigo Saul Gaitan and Keh‐Shin Lii

Integer‐valued asymmetric garch modeling pp. 737-751

Xiaofei Hu and Beth Andrews

Asymptotic theory for QMLE for the real‐time GARCH(1,1) model pp. 752-776

Ekaterina Smetanina and Wei Biao Wu

Aspects of non‐causal and non‐invertible CARMA processes pp. 777-790

Peter J. Brockwell and Alexander Lindner

Volume 42, issue 4, 2021

Quasi‐maximum likelihood and the kernel block bootstrap for nonlinear dynamic models pp. 377-405

Paulo Parente and Richard J. Smith

Threshold model with a time‐varying threshold based on Fourier approximation pp. 406-430

Lixiong Yang, Chingnun Lee and I‐Po Chen

Identifiability of structural singular vector autoregressive models pp. 431-441

Bernd Funovits and Alexander Braumann

Parsimonious time series modeling for high frequency climate data pp. 442-470

Paul L. Anderson, Farzad Sabzikar and Mark M. Meerschaert

Jointly determining the state dimension and lag order for Markov‐switching vector autoregressive models pp. 471-491

Nan Li and Simon Sai Man Kwok

Corrigendum to “A Generalised Fractional Differencing Bootstrap for Long Memory Processes” Journal of Time Series Analysis 40: 467‐492 (2019) DOI: 10.1111/jtsa.12460 pp. 492-492

George Kapetanios, Fotis Papailias and Robert Taylor

Volume 42, issue 3, 2021

Quasi‐maximum likelihood estimation of conditional autoregressive Wishart models pp. 271-294

Manabu Asai and Mike K. P. So

Prediction of Singular VARs and an Application to Generalized Dynamic Factor Models pp. 295-313

Siegfried Hörmann and Gilles Nisol

Asymptotic Behavior of Delay Times of Bubble Monitoring Tests pp. 314-337

Eiji Kurozumi

To infinity and beyond: Efficient computation of ARCH(∞) models pp. 338-354

Morten Nielsen and Antoine Noël

Extensions to the invariance property of maximum likelihood estimation for affine‐transformed state‐space models pp. 355-371

Adrian Pizzinga and Marcelo Fernandes

Statistical foundations of data science by jianqing Fan, Runze Li, Chun‐Hui Zhang, Hui Zou. Published by Taylor & Francis Group. Total number of pages: 729. ISBN: 978‐1‐466‐51084‐5 pp. 372-373

Weining Wang

Volume 42, issue 2, 2021

Editorial Announcement pp. 139-139

Robert Taylor

Necessary and sufficient conditions for the identifiability of observation‐driven models pp. 140-160

Randal Douc, François Roueff and Tepmony Sim

Long range dependence for stable random processes pp. 161-185

Vitalii Makogin, Marco Oesting, Albert Rapp and Evgeny Spodarev

A Note on Efficient Fitting of Stochastic Volatility Models pp. 186-200

Chen Gong and David S. Stoffer

Estimating wold matrices and vector moving average processes pp. 201-221

Jonas Krampe and Timothy L. McMurry

Empirical likelihood test for the application of swqmele in fitting an arma‐garch model pp. 222-239

Mo Zhou, Liang Peng and Rongmao Zhang

A simple nearly unbiased estimator of cross‐covariances pp. 240-266

Yifan Li and Yao Rao

Volume 42, issue 1, 2021

Editorial announcement: Journal of Time Series Analysis Distinguished Authors 2020 pp. 3-3

Robert Taylor

Robust empirical likelihood for time series pp. 4-18

Kun Chen and Rui Huang

Independent block identification in multivariate time series pp. 19-33

Florencia Leonardi, Matías Lopez‐Rosenfeld, Daniela Rodriguez, Magno T. F. Severino and Mariela Sued

Robust discrimination between long‐range dependence and a change in mean pp. 34-62

Carina Gerstenberger

A new approach for open‐end sequential change point monitoring pp. 63-84

Josua Gösmann, Tobias Kley and Holger Dette

Unit root testing with slowly varying trends pp. 85-106

Sven Otto

Mixtures of Nonlinear Poisson Autoregressions pp. 107-135

Paul Doukhan, Konstantinos Fokianos and Joseph Rynkiewicz