KMS Of Academy of mathematics and systems sciences, CAS
Threshold autoregressive models for interval-valued time series data | |
Sun, Yuying1,2; Han, Ai1,2; Hong, Yongmiao3,4; Wang, Shouyang1,2 | |
2018-10-01 | |
发表期刊 | JOURNAL OF ECONOMETRICS |
ISSN | 0304-4076 |
卷号 | 206期号:2页码:414-446 |
摘要 | Modeling and forecasting symbolic data, especially interval-valued time series (ITS) data, has received considerable attention in statistics and related fields. The core of available methods on ITS analysis is based on various applications of conventional linear modeling. However, few works have considered possible nonlinearities in ITS data. In this paper, we propose a new class of threshold autoregressive interval (TARI) models for ITS data. By matching the interval model with interval observations, we develop a minimum distance estimation method for TARI models, and establish the asymptotic theory for the proposed estimators. We show that the threshold parameter estimator is T-consistent and follows an asymptotic compound Poisson process as the sample size T -> infinity. And the estimators for other TARI model parameters are root-T consistent and asymptotically normal. Simulation studies show that the proposed TARI model provides more accurate out-of-sample forecasts than the existing center-radius self-exciting threshold (CR-SETAR) model for ITS data in the literature. Empirical applications to the S&P 500 Price Index document significant asymmetric reactions of the stock markets in Japan, U.K. and France to shocks from the U.S. stock market and that incorporating this asymmetric effect yield better out-of-sample forecasts than a variety of popular models available in the literature. (C) 2018 Published by Elsevier B.V. |
关键词 | Asymmetric reaction Interval-valued data Minimum distance estimation Nonlinearity Symbolic data Threshold autoregressive interval models |
DOI | 10.1016/j.jeconom.2018.06.009 |
语种 | 英语 |
资助项目 | National Natural Science Foundation of China[7041100] ; National Natural Science Foundation of China[71671183] |
WOS研究方向 | Business & Economics ; Mathematics ; Mathematical Methods In Social Sciences |
WOS类目 | Economics ; Mathematics, Interdisciplinary Applications ; Social Sciences, Mathematical Methods |
WOS记录号 | WOS:000447571200008 |
出版者 | ELSEVIER SCIENCE SA |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.amss.ac.cn/handle/2S8OKBNM/31342 |
专题 | 系统科学研究所 |
通讯作者 | Hong, Yongmiao |
作者单位 | 1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China 2.Chinese Acad Sci, Ctr Forecasting Sci, Beijing, Peoples R China 3.Cornell Univ, Dept Econ, Ithaca, NY 14853 USA 4.Cornell Univ, Dept Stat Sci, Ithaca, NY 14850 USA |
推荐引用方式 GB/T 7714 | Sun, Yuying,Han, Ai,Hong, Yongmiao,et al. Threshold autoregressive models for interval-valued time series data[J]. JOURNAL OF ECONOMETRICS,2018,206(2):414-446. |
APA | Sun, Yuying,Han, Ai,Hong, Yongmiao,&Wang, Shouyang.(2018).Threshold autoregressive models for interval-valued time series data.JOURNAL OF ECONOMETRICS,206(2),414-446. |
MLA | Sun, Yuying,et al."Threshold autoregressive models for interval-valued time series data".JOURNAL OF ECONOMETRICS 206.2(2018):414-446. |
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