Structural Laplace Transform and Compound Autoregressive Models
Serge Darolles,
Christian Gourieroux and
Joann Jasiak
Journal of Time Series Analysis, 2006, vol. 27, issue 4, 477-503
Abstract:
Abstract. This paper presents a new general class of compound autoregressive (Car) models for non‐Gaussian time series. The distinctive feature of the class is that Car models are specified by means of the conditional Laplace transforms. This approach allows for simple derivation of the ergodicity conditions and ensures the existence of forecasting distributions in closed form, at any horizon. The last property is of particular interest for applications to finance and economics that investigate the term structure of variables and/or of their nonlinear transforms. The Car class includes a number of time‐series models that already exist in the literature, as well as new models introduced in this paper. Their applications are illustrated by examples of portfolio management, term structure and extreme risk analysis.
Date: 2006
References: View complete reference list from CitEc
Citations: View citations in EconPapers (43)
Downloads: (external link)
https://doi.org/10.1111/j.1467-9892.2006.00479.x
Related works:
Working Paper: Structural Laplace Transform and Compound Autoregressive Models (2006)
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:27:y:2006:i:4:p:477-503
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 ().