Journal of Time Series Analysis
1980 - 2025
Current editor(s): M.B. Priestley From Wiley Blackwell Bibliographic data for series maintained by Wiley Content Delivery (). Access Statistics for this journal.
Is something missing from the series or not right? See the RePEc data check for the archive and series.
Volume 44, issue 5-6, 2023
- Editorial Announcement pp. 439-439

- Robert Taylor
- Special Issue of the Journal of Time Series Analysis in Honor of Professor Masanobu Taniguchi pp. 440-441

- Marc Hallin, Yoshihide Kakizawa and Hira Koul
- Weighted l1‐Penalized Corrected Quantile Regression for High‐Dimensional Temporally Dependent Measurement Errors pp. 442-473

- Monika Bhattacharjee, Nilanjan Chakraborty and Hira L. Koul
- Testing of Constant Parameters for Semi‐Parametric Functional Coefficient Models with Integrated Covariates pp. 474-486

- Shan Dai and Ngai Hang Chan
- Clustering multivariate time series using energy distance pp. 487-504

- Richard A. Davis, Leon Fernandes and Konstantinos Fokianos
- Detecting relevant changes in the spatiotemporal mean function pp. 505-532

- Holger Dette and Pascal Quanz
- Optimal estimating function for weak location‐scale dynamic models pp. 533-555

- Christian Francq and Jean‐Michel Zakoïan
- Estimation on unevenly spaced time series pp. 556-577

- Liudas Giraitis and Fulvia Marotta
- Factor models for high‐dimensional functional time series I: Representation results pp. 578-600

- Marc Hallin, Gilles Nisol and Shahin Tavakoli
- Factor models for high‐dimensional functional time series II: Estimation and forecasting pp. 601-621

- Shahin Tavakoli, Gilles Nisol and Marc Hallin
- Testing for symmetric correlation matrices with applications to factor models pp. 622-643

- Nan‐Jung Hsu, Lai Heng Sim and Ruey S. Tsay
- Bivariate random coefficient integer‐valued autoregressive models: Parameter estimation and change point test pp. 644-666

- Sangyeol Lee and Minyoung Jo
- A testing approach to clustering scalar time series pp. 667-685

- Daniel Peña and Ruey S. Tsay
- Some recent trends in embeddings of time series and dynamic networks pp. 686-709

- Dag Tjøstheim, Martin Jullum and Anders Løland
Volume 44, issue 4, 2023
- Editorial announcement pp. 335-335

- Robert Taylor
- Announcement: Call for Papers for Special Issue in Honour of Stephen J. Taylor pp. 336-336

- Torben Andersen, Kim Christensen and Ingmar Nolte
- On highly skewed fractional log‐stable noise sequences and their application pp. 337-358

- Harry Pavlopoulos and George Chronis
- On the asymptotic behavior of bubble date estimators pp. 359-373

- Eiji Kurozumi and Anton Skrobotov
- Regime switching models for circular and linear time series pp. 374-392

- Andrew Harvey and Dario Palumbo
- Autoregressive conditional proportion: A multiplicative‐error model for (0,1)‐valued time series pp. 393-417

- Abdelhakim Aknouche and Stefanos Dimitrakopoulos
- Geometric ergodicity and conditional self‐weighted M‐estimator of a GRCAR(p) model with heavy‐tailed errors pp. 418-436

- Xiaoyan Li, Jiazhu Pan and Anchao Song
Volume 44, issue 3, 2023
- Volatility models for stylized facts of high‐frequency financial data pp. 262-279

- Donggyu Kim and Minseok Shin
- Tempered functional time series pp. 280-293

- Farzad Sabzikar and Piotr Kokoszka
- A nonparametric predictive regression model using partitioning estimators based on Taylor expansions pp. 294-318

- Jose Olmo
- System identification using autoregressive Bayesian neural networks with nonparametric noise models pp. 319-330

- Christos Merkatas and Simo Särkkä
- Corrigendum to the article “Regular multidimensional stationary time series” pp. 331-332

- Tamás Szabados
Volume 44, issue 2, 2023
- Dynamic deconvolution and identification of independent autoregressive sources pp. 151-180

- Christian Gourieroux and Joann Jasiak
- Estimation of the variance function in structural break autoregressive models with non‐stationary and explosive segments pp. 181-205

- David I. Harvey, Stephen J. Leybourne and Yang Zu
- Flexible bivariate INGARCH process with a broad range of contemporaneous correlation pp. 206-222

- Luiza S. C. Piancastelli, Wagner Barreto‐Souza and Hernando Ombao
- Directed graphs and variable selection in large vector autoregressive models pp. 223-246

- Dominik Bertsche, Ralf Brüggemann and Christian Kascha
- Higher‐order asymptotics of minimax estimators for time series pp. 247-257

- Xiaofei Xu, Yan Liu and Masanobu Taniguchi
Volume 44, issue 1, 2023
- Editorial Announcement: Journal of Time Series Analysis Distinguished Authors 2022 pp. 3-3

- Robert Taylor
- High‐dimensional sparse multivariate stochastic volatility models pp. 4-22

- Benjamin Poignard and Manabu Asai
- A prediction perspective on the Wiener–Hopf equations for time series pp. 23-42

- Suhasini Subba Rao and Junho Yang
- Peaks, gaps, and time‐reversibility of economic time series pp. 43-68

- Tommaso Proietti
- Non‐parametric short‐ and long‐run Granger causality testing in the frequency domain pp. 69-92

- Cleiton Taufemback
- Seasonal count time series pp. 93-124

- Jiajie Kong and Robert Lund
- Student‐t stochastic volatility model with composite likelihood EM‐algorithm pp. 125-147

- Raanju R. Sundararajan and Wagner Barreto‐Souza
Volume 43, issue 6, 2022
- A non‐parametric test for multi‐variate trend functions pp. 856-871

- Erhua Zhang, Xiaojun Song and Jilin Wu
- Inference in functional factor models with applications to yield curves pp. 872-894

- Lajos Horvath, Piotr Kokoszka, Jeremy VanderDoes and Shixuan Wang
- Trend locally stationary wavelet processes pp. 895-917

- Euan T. McGonigle, Rebecca Killick and Matthew A. Nunes
- Autoregressive mixture models for clustering time series pp. 918-937

- Benny Ren and Ian Barnett
- Estimation of the empirical risk‐return relation: A generalized‐risk‐in‐mean model pp. 938-963

- Xuanling Yang and Dong Li
- Portmanteau test for a class of multivariate asymmetric power GARCH model pp. 964-1002

- Yacouba Boubacar Maïnassara, Othman Kadmiri and Bruno Saussereau
Volume 43, issue 5, 2022
- Testing the volatility jumps based on the high frequency data pp. 669-694

- Guangying Liu, Meiyao Liu and Jinguan Lin
- Rank test of unit‐root hypothesis with AR‐GARCH errors pp. 695-719

- Guili Liao, Qimeng Liu, Rongmao Zhang and Shifang Zhang
- Estimation and inference in adaptive learning models with slowly decreasing gains pp. 720-749

- Alexander Mayer
- Asymptotic independence ex machina: Extreme value theory for the diagonal SRE model pp. 750-780

- Sebastian Mentemeier and Olivier Wintenberger
- Permutation testing for dependence in time series pp. 781-807

- Joseph P. Romano and Marius A. Tirlea
- A new non‐parametric cross‐spectrum estimator pp. 808-827

- Evangelos E. Ioannidis
- Johansen‐type cointegration tests with a Fourier function pp. 828-852

- Razvan Pascalau, Junsoo Lee, Saban Nazlioglu and Yan (Olivia) Lu
Volume 43, issue 4, 2022
- Simultaneous variable selection and structural identification for time‐varying coefficient models pp. 511-531

- Ngai Hang Chan, Linhao Gao and Wilfredo Palma
- Regularized estimation of high‐dimensional vector autoregressions with weakly dependent innovations pp. 532-557

- Ricardo P. Masini, Marcelo Medeiros and Eduardo F. Mendes
- Misspecified semiparametric model selection with weakly dependent observations pp. 558-586

- Francesco Bravo
- Long‐term prediction intervals with many covariates pp. 587-609

- Sayar Karmakar, Marek Chudý and Wei Biao Wu
- Moment estimators for parameters of Lévy‐driven Ornstein–Uhlenbeck processes pp. 610-639

- Yanfeng Wu, Jianqiang Hu and Xiangyu Yang
- Conditional quantile analysis for realized GARCH models pp. 640-665

- Donggyu Kim, Minseog Oh and Yazhen Wang
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 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
| |