A Generalised Fractional Differencing Bootstrap for Long Memory Processes

George Kapetanios, Fotis Papailias and Robert Taylor

Journal of Time Series Analysis, 2019, vol. 40, issue 4, 467-492

Abstract: A bootstrap methodology suitable for use with stationary and non‐stationary fractionally integrated time series is further developed in this article. The resampling algorithm involves estimating the degree of fractional integration, applying the fractional differencing operator, resampling the resulting approximation to the underlying short memory series and, finally, cumulating to obtain a resample of the original fractionally integrated process. This approach extends existing methods in the literature by allowing for general bootstrap schemes including blockwise bootstraps. Furthermore, we show that it can also be validly used for non‐stationary fractionally integrated processes. We establish asymptotic validity results for the general method and provide simulation evidence which highlights a number of favourable aspects of its finite sample performance, relative to other commonly used bootstrap methods.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://doi.org/10.1111/jtsa.12460

Related works:
Working Paper: A Generalised Fractional Differencing Bootstrap for Long Memory Processes (2019)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:jtsera:v:40:y:2019:i:4:p:467-492

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0143-9782

Access Statistics for this article

Journal of Time Series Analysis is currently edited by M.B. Priestley

More articles in Journal of Time Series Analysis from Wiley Blackwell
Bibliographic data for series maintained by Wiley Content Delivery ().