4.5 Article

Seasonal FIEGARCH processes

Journal

COMPUTATIONAL STATISTICS & DATA ANALYSIS
Volume 68, Issue -, Pages 262-295

Publisher

ELSEVIER
DOI: 10.1016/j.csda.2013.07.001

Keywords

Long-range dependence; Volatility; Periodicity; FIEGARCH process

Funding

  1. CNPq-Brazil
  2. CAPES-Brazil
  3. INCT em Matematica
  4. Pronex Probabilidade e Processos Estocasticos [E-26/170.008/2008 - APQ1]

Ask authors/readers for more resources

Here we develop the theory of seasonal FIEGARCH processes, denoted by SFIEGARCH, establishing conditions for the existence, the invertibility, the stationarity and the ergodicity of these processes. We analyze their asymptotic dependence structure by means of the autocovariance and autocorrelation functions. We also present some properties regarding their spectral representation. All properties are illustrated through graphical examples and an application of SFIEGARCH models to describe the volatility of the S&P500 US stock index log-return time series in the period from December 13, 2004 to October 10, 2009 is provided. (C) 2013 Elsevier B.V. All rights reserved.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available