Temporal Aggregation of Stationary and Non‐stationary Continuous‐Time Processes

Henghsiu Tsai () and K. S. Chan

Scandinavian Journal of Statistics, 2005, vol. 32, issue 4, 583-597

Abstract: Abstract. We study the autocorrelation structure of aggregates from a continuous‐time process. The underlying continuous‐time process or some of its higher derivative is assumed to be a stationary continuous‐time auto‐regressive fractionally integrated moving‐average (CARFIMA) process with Hurst parameter H. We derive closed‐form expressions for the limiting autocorrelation function and the normalized spectral density of the aggregates, as the extent of aggregation increases to infinity. The limiting model of the aggregates, after appropriate number of differencing, is shown to be some functional of the standard fractional Brownian motion with the same Hurst parameter of the continuous‐time process from which the aggregates are measured. These results are then used to assess the loss of forecasting efficiency due to aggregation.

Date: 2005
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

Downloads: (external link)
https://doi.org/10.1111/j.1467-9469.2005.00455.x

Related works:
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:scjsta:v:32:y:2005:i:4:p:583-597

Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0303-6898

Access Statistics for this article

Scandinavian Journal of Statistics is currently edited by ÿrnulf Borgan and Bo Lindqvist

More articles in Scandinavian Journal of Statistics from Danish Society for Theoretical Statistics, Finnish Statistical Society, Norwegian Statistical Association, Swedish Statistical Association
Bibliographic data for series maintained by Wiley Content Delivery ().