کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
7357816 1478564 2018 65 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Simultaneous multiple change-point and factor analysis for high-dimensional time series
ترجمه فارسی عنوان
همزمان چندین نقطه تغییر و تجزیه و تحلیل فاکتور برای سری زمانی با طول عمر
موضوعات مرتبط
مهندسی و علوم پایه ریاضیات آمار و احتمال
چکیده انگلیسی
We propose the first comprehensive treatment of high-dimensional time series factor models with multiple change-points in their second-order structure. We operate under the most flexible definition of piecewise stationarity, and estimate the number and locations of change-points consistently as well as identifying whether they originate in the common or idiosyncratic components. Through the use of wavelets, we transform the problem of change-point detection in the second-order structure of a high-dimensional time series, into the (relatively easier) problem of change-point detection in the means of high-dimensional panel data. Also, our methodology circumvents the difficult issue of the accurate estimation of the true number of factors in the presence of multiple change-points by adopting a screening procedure. We further show that consistent factor analysis is achieved over each segment defined by the change-points estimated by the proposed methodology. In extensive simulation studies, we observe that factor analysis prior to change-point detection improves the detectability of change-points, and identify and describe an interesting 'spillover' effect in which substantial breaks in the idiosyncratic components get, naturally enough, identified as change-points in the common components, which prompts us to regard the corresponding change-points as also acting as a form of 'factors'. Our methodology is implemented in the R package factorcpt, available from CRAN.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Econometrics - Volume 206, Issue 1, September 2018, Pages 187-225
نویسندگان
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