Stationarity and Invertibility

John D. Levendis
Additional contact information
John D. Levendis: Loyola University New Orleans

Chapter 4 in Time Series Econometrics, 2018, pp 81-99 from Springer

Abstract: Abstract Most time-series methods are only valid if the underlying time-series is stationary. The more stationary something is, the more predictable it is. More specifically, a time-series is stationary if its mean, variance, and autocovariance do not rely on the particular time period.

Date: 2018
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:spr:sptchp:978-3-319-98282-3_4

Ordering information: This item can be ordered from
http://www.springer.com/9783319982823

DOI: 10.1007/978-3-319-98282-3_4

Access Statistics for this chapter

More chapters in Springer Texts in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().