Journal of Time Series Analysis

1980 - 2025

Current editor(s): M.B. Priestley

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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

Volume 41, issue 6, 2020

Tests for conditional heteroscedasticity of functional data pp. 733-758

Gregory Rice, Tony Wirjanto and Yuqian Zhao

Efficient Bayesian PARCOR approaches for dynamic modeling of multivariate time series pp. 759-784

Wenjie Zhao and Raquel Prado

Measures of Cross‐Dependence for Bidimensional Periodic AR(1) Model with α‐Stable Distribution pp. 785-807

Aleksandra Grzesiek, Prashant Giri, S. Sundar and Agnieszka WyŁomańska

Models for circular data from time series spectra pp. 808-829

Masanobu Taniguchi, Shogo Kato, Hiroaki Ogata and Arthur Pewsey

Conway–Maxwell–Poisson Autoregressive Moving Average Model for Equidispersed, Underdispersed, and Overdispersed Count Data pp. 830-857

Moizes Melo and Airlane Alencar

Functional lagged regression with sparse noisy observations pp. 858-882

Tomáš Rubín and Victor M. Panaretos

On the three‐step non‐Gaussian quasi‐maximum likelihood estimation of heavy‐tailed double autoregressive models pp. 883-891

Huan Gong and Dong Li

On the limit theory of mixed to unity VARs: Panel setting with weakly dependent errors pp. 892-898

Ovidijus Stauskas

Correction to: Random Coefficient Autoregressive Processes: a Markov Chain Analysis of Stationarity and Finiteness of Moments by Paul D. Feigin and Richard L. Tweedie J. Time Series Anal., Vol. 6, No. 1 (1985) pp. 899-900

Paul D. Feigin

Volume 41, issue 5, 2020

Backtesting portfolio value‐at‐risk with estimated portfolio weights pp. 605-619

Zaichao Du and Pei Pei

Robust estimation of stationary continuous‐time arma models via indirect inference pp. 620-651

Vicky Fasen‐Hartmann and Sebastian Kimmig

Missing not at random and the nonparametric estimation of the spectral density pp. 652-675

Sam Efromovich

Bootstrap procedures for detecting multiple persistence shifts in heteroskedastic time series pp. 676-690

Mohitosh Kejriwal, Xuewen Yu and Pierre Perron

A family of multivariate non‐gaussian time series models pp. 691-721

Tevfik Aktekin, Nicholas G. Polson and Refik Soyer

A Portmanteau Test for Smooth Transition Autoregressive Models pp. 722-730

Qiang Xia, Zhiqiang Zhang and Wai Keung Li

Volume 41, issue 4, 2020

Editorial Announcement: Journal of Time Series Analysis Distinguished Authors pp. 489-490

Robert Taylor

Modeling the Variance of Return Intervals Toward Volatility Prediction pp. 492-519

Yan Sun, Guanghua Lian, Zudi Lu, Jennifer Loveland and Isaac Blackhurst

Estimating Long Memory in Panel Random‐Coefficient AR(1) Data pp. 520-535

Remigijus Leipus, Anne Philippe, Vytautė Pilipauskaitė and Donatas Surgailis

An Asymptotic F Test for Uncorrelatedness in the Presence of Time Series Dependence pp. 536-550

Xuexin Wang and Yixiao Sun

Two‐Step Estimation for Time Varying Arch Models pp. 551-570

Yuanyuan Zhang, Rong Liu, Qin Shao and Lijian Yang

Testing equality of autocovariance operators for functional time series pp. 571-589

Dimitrios Pilavakis, Efstathios Paparoditis and Theofanis Sapatinas

Filling the gap between Continuous and Discrete Time Dynamics of Autoregressive Processes pp. 590-602

Valerie Girardin and Rachid Senoussi

Volume 41, issue 3, 2020

Nonlinear Factor‐Augmented Predictive Regression Models with Functional Coefficients pp. 367-386

Degui Li, Jiraroj Tosasukul and Wenyang Zhang

Location Multiplicative Error Models with Quasi Maximum Likelihood Estimation pp. 387-405

Qian Li

On the Stationary Marginal Distributions of Subclasses of Multivariate Setar Processes of Order One pp. 406-420

Soumya Das and Marc G. Genton

Consistency of the Hill Estimator for Time Series Observed with Measurement Errors pp. 421-435

Mihyun Kim and Piotr Kokoszka

A Flexible Univariate Autoregressive Time‐Series Model for Dispersed Count Data pp. 436-453

Kimberly F. Sellers, Stephen J. Peng and Ali Arab

Spatio‐Temporal Dependence Measures for Bivariate AR(1) Models with α‐Stable Noise pp. 454-475

Aleksandra Grzesiek, Grzegorz Sikora, Marek Teuerle and Agnieszka Wyłomańska

The Marginal Density of a TMA(1) Process pp. 476-484

Dong Li and Jiaming Qiu

Time Series: a Data Analysis Approach Using R By Robert H. Shumway and David S. Stoffer. Published by Taylor & Francis Group, LLC, Boca Raton, London, New York, 2019. ISBN: 9780367221096 (Hardback) pp. 485-486

Matthew Nunes

Volume 41, issue 2, 2020

A Stationary Spatio‐Temporal GARCH Model pp. 177-209

Sondre Hølleland and Hans Arnfinn Karlsen

Estimating the Mean Direction of Strongly Dependent Circular Time Series pp. 210-228

Jan Beran and Sucharita Ghosh

Robust Linear Interpolation and Extrapolation of Stationary Time Series in Lp pp. 229-248

Yan Liu, Yujie Xue and Masanobu Taniguchi

Mixed First‐ and Second‐Order Cointegrated Continuous Time Models with Mixed Stock and Flow Data pp. 249-267

Milena Hoyos

Modeling bivariate long‐range dependence with general phase pp. 268-292

Stefanos Kechagias and Vladas Pipiras

Extracting Conditionally Heteroskedastic Components using Independent Component Analysis pp. 293-311

Jari Miettinen, Markus Matilainen, Klaus Nordhausen and Sara Taskinen

Walsh Fourier Transform of Locally Stationary Time Series pp. 312-340

Zhelin Huang and Ngai Hang Chan

On the limit theory of the Gaussian SQMLE in the EGARCH(1,1) model pp. 341-350

Stelios Arvanitis and Sofia Anyfantaki

The Limiting Distribution of a Non‐Stationary Integer Valued GARCH(1,1) Process pp. 351-356

Jon Michel

Further Results on Pseudo‐Maximum Likelihood Estimation and Testing in the Constant Elasticity of Variance Continuous Time Model pp. 357-364

Emma Iglesias and Garry D. A. Phillips

Volume 41, issue 1, 2020

Higher‐Order Accurate Spectral Density Estimation of Functional Time Series pp. 3-20

Tingyi Zhu and Dimitris N. Politis

Bootstrap Inference for Garch Models by the Least Absolute Deviation Estimation pp. 21-40

Qianqian Zhu, Ruochen Zeng and Guodong Li

Harmonically Weighted Processes pp. 41-66

Uwe Hassler and Mehdi Hosseinkouchack

On Singular Spectrum Analysis And Stepwise Time Series Reconstruction pp. 67-94

Donald Poskitt

Volatility asymmetry in functional threshold GARCH model pp. 95-109

Hao Sun and Bo Yu

Empirical Characteristic Functions‐Based Estimation and Distance Correlation for Locally Stationary Processes pp. 110-133

Carsten Jentsch, Anne Leucht, Marco Meyer and Carina Beering

Deterministic Parameter Change Models in Continuous and Discrete Time pp. 134-145

Marcus Chambers and Robert Taylor

Properties of the Power Envelope for Tests Against Both Stationary and Explosive Alternatives: The Effect of Trends pp. 146-153

Patrick Marsh

Inference for asymmetric exponentially weighted moving average models pp. 154-162

Dong Li and Ke Zhu

Self‐Weighted Lad‐Based Inference for Heavy‐Tailed Continuous Threshold Autoregressive Models pp. 163-172

Yaxing Yang and Dong Li

Large Covariance and Autocovariance Matrices, By Arup Bose and Monika Bhattacharjee. Published by Taylor & Francis Group, LLC, Boca Raton, London, New York, 2019. ISBN: 9781138303867 (HARDBACK) pp. 173-174

Jianfeng Yao