Journal of Time Series Analysis最新文献

Non‐causal and non‐invertible ARMA models: Identification, estimation and application in equity portfolios 非因果和非可逆 ARMA 模型：股票投资组合中的识别、估计和应用

IF 0.9 4区数学

Journal of Time Series Analysis Pub Date : 2024-09-18 DOI: 10.1111/jtsa.12776

Alain Hecq, Daniel Velasquez‐Gaviria

引用次数: 0

Mixing properties of non‐stationary multi‐variate count processes 非稳态多变量计数过程的混合特性

IF 0.9 4区数学

Journal of Time Series Analysis Pub Date : 2024-09-17 DOI: 10.1111/jtsa.12775

Zinsou Max Debaly, Michael H. Neumann, Lionel Truquet

引用次数: 0

Mean‐preserving rounding integer‐valued ARMA models 保均舍入整数值 ARMA 模型

IF 0.9 4区数学

Journal of Time Series Analysis Pub Date : 2024-09-11 DOI: 10.1111/jtsa.12774

Christian H. Weiß, Fukang Zhu

{"title":"Mean‐preserving rounding integer‐valued ARMA models","authors":"Christian H. Weiß, Fukang Zhu","doi":"10.1111/jtsa.12774","DOIUrl":"https://doi.org/10.1111/jtsa.12774","url":null,"abstract":"In the past four decades, research on count time series has made significant progress, but research on ‐valued time series is relatively rare. Existing ‐valued models are mainly of autoregressive structure, where the use of the rounding operator is very natural. Because of the discontinuity of the rounding operator, the formulation of the corresponding model identifiability conditions and the computation of parameter estimators need special attention. It is also difficult to derive closed‐form formulae for crucial stochastic properties. We rediscover a stochastic rounding operator, referred to as mean‐preserving rounding, which overcomes the above drawbacks. Then, a novel class of ‐valued ARMA models based on the new operator is proposed, and the existence of stationary solutions of the models is established. Stochastic properties including closed‐form formulae for (conditional) moments, autocorrelation function, and conditional distributions are obtained. The advantages of our novel model class compared to existing ones are demonstrated. In particular, our model construction avoids identifiability issues such that maximum likelihood estimation is possible. A simulation study is provided, and the appealing performance of the new models is shown by several real‐world data sets.","PeriodicalId":49973,"journal":{"name":"Journal of Time Series Analysis","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142206452","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Forecasting the yield curve: the role of additional and time‐varying decay parameters, conditional heteroscedasticity, and macro‐economic factors 预测收益率曲线：附加和时变衰减参数、条件异方差和宏观经济因素的作用

IF 0.9 4区数学

Journal of Time Series Analysis Pub Date : 2024-09-09 DOI: 10.1111/jtsa.12769

João F. Caldeira, Werley C. Cordeiro, Esther Ruiz, André A.P. Santos

{"title":"Forecasting the yield curve: the role of additional and time‐varying decay parameters, conditional heteroscedasticity, and macro‐economic factors","authors":"João F. Caldeira, Werley C. Cordeiro, Esther Ruiz, André A.P. Santos","doi":"10.1111/jtsa.12769","DOIUrl":"https://doi.org/10.1111/jtsa.12769","url":null,"abstract":"In this article, we analyse the forecasting performance of several parametric extensions of the popular Dynamic Nelson–Siegel (DNS) model for the yield curve. Our focus is on the role of additional and time‐varying decay parameters, conditional heteroscedasticity, and macroeconomic variables. We also consider the role of several popular restrictions on the dynamics of the factors. Using a novel dataset of end‐of‐month continuously compounded Treasury yields on US zero‐coupon bonds and frequentist estimation based on the extended Kalman filter, we show that a second decay parameter does not contribute to better forecasts. In concordance with the preferred habitat theory, we also show that the best forecasting model depends on the maturity. For short maturities, the best performance is obtained in a heteroscedastic model with a time‐varying decay parameter. However, for long maturities, neither the time‐varying decay nor the heteroscedasticity plays any role, and the best forecasts are obtained in the basic DNS model with the shape of the yield curve depending on macroeconomic activity. Finally, we find that assuming non‐stationary factors is helpful in forecasting at long horizons.","PeriodicalId":49973,"journal":{"name":"Journal of Time Series Analysis","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142206451","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Weighted discrete ARMA models for categorical time series 分类时间序列的加权离散 ARMA 模型

IF 0.9 4区数学

Journal of Time Series Analysis Pub Date : 2024-09-06 DOI: 10.1111/jtsa.12773

Christian H. Weiß, Osama Swidan

引用次数: 0

Estimating lagged (cross‐)covariance operators of Lp‐m‐approximable processes in cartesian product hilbert spaces 估计卡特积希尔伯特空间中 Lp-m 近似过程的滞后（交叉）协方差算子

IF 0.9 4区数学

Journal of Time Series Analysis Pub Date : 2024-08-30 DOI: 10.1111/jtsa.12772

Sebastian Kühnert

引用次数: 0

Improved estimation of dynamic models of conditional means and variances 条件均值和方差动态模型的改进估计

IF 0.9 4区数学

Journal of Time Series Analysis Pub Date : 2024-08-30 DOI: 10.1111/jtsa.12770

Weining Wang, Jeffrey M. Wooldridge, Mengshan Xu

引用次数: 0

Self‐normalization inference for linear trends in cointegrating regressions 协整回归中线性趋势的自归一化推断

IF 0.9 4区数学

Journal of Time Series Analysis Pub Date : 2024-08-29 DOI: 10.1111/jtsa.12771

Cheol‐Keun Cho

引用次数: 0

The Granger–Johansen representation theorem for integrated time series on Banach space 巴拿赫空间上整合时间序列的格兰杰-约翰森表示定理

IF 0.9 4区数学

Journal of Time Series Analysis Pub Date : 2024-08-18 DOI: 10.1111/jtsa.12766

Phil Howlett, Brendan K. Beare, Massimo Franchi, John Boland, Konstantin Avrachenkov

{"title":"The Granger–Johansen representation theorem for integrated time series on Banach space","authors":"Phil Howlett, Brendan K. Beare, Massimo Franchi, John Boland, Konstantin Avrachenkov","doi":"10.1111/jtsa.12766","DOIUrl":"https://doi.org/10.1111/jtsa.12766","url":null,"abstract":"We prove an extended Granger–Johansen representation theorem (GJRT) for finite‐ or infinite‐order integrated autoregressive time series on Banach space. We assume only that the resolvent of the autoregressive polynomial for the series is analytic on and inside the unit circle except for an isolated singularity at unity. If the singularity is a pole of finite order the time series is integrated of the same order. If the singularity is an essential singularity the time series is integrated of order infinity. When there is no deterministic forcing the value of the series at each time is the sum of an almost surely convergent stochastic trend, a deterministic term depending on the initial conditions and a finite sum of embedded white noise terms in the prior observations. This is the extended GJRT. In each case the original series is the sum of two separate autoregressive time series on complementary subspaces – a singular component which is integrated of the same order as the original series and a regular component which is not integrated. The extended GJRT applies to all integrated autoregressive processes irrespective of the spatial dimension, the number of stochastic trends and cointegrating relations in the system and the order of integration.","PeriodicalId":49973,"journal":{"name":"Journal of Time Series Analysis","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142206457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Testing covariance separability for continuous functional data 测试连续函数数据的协方差可分性

IF 0.9 4区数学

Journal of Time Series Analysis Pub Date : 2024-08-12 DOI: 10.1111/jtsa.12764

Holger Dette, Gauthier Dierickx, Tim Kutta

{"title":"Testing covariance separability for continuous functional data","authors":"Holger Dette, Gauthier Dierickx, Tim Kutta","doi":"10.1111/jtsa.12764","DOIUrl":"https://doi.org/10.1111/jtsa.12764","url":null,"abstract":"Analyzing the covariance structure of data is a fundamental task of statistics. While this task is simple for low‐dimensional observations, it becomes challenging for more intricate objects, such as multi‐variate functions. Here, the covariance can be so complex that just saving a non‐parametric estimate is impractical and structural assumptions are necessary to tame the model. One popular assumption for space‐time data is separability of the covariance into purely spatial and temporal factors. In this article, we present a new test for separability in the context of dependent functional time series. While most of the related work studies functional data in a Hilbert space of square integrable functions, we model the observations as objects in the space of continuous functions equipped with the supremum norm. We argue that this (mathematically challenging) setup enhances interpretability for users and is more in line with practical preprocessing. Our test statistic measures the maximal deviation between the estimated covariance kernel and a separable approximation. Critical values are obtained by a non‐standard multiplier bootstrap for dependent data. We prove the statistical validity of our approach and demonstrate its practicability in a simulation study and a data example.","PeriodicalId":49973,"journal":{"name":"Journal of Time Series Analysis","volume":null,"pages":null},"PeriodicalIF":0.9,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141941411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0