Nonparametric ARCH with additive mean and multiplicative volatility: a new estimation procedure

Name: Nonparametric ARCH with additive mean and multiplicative volatility: a new estimation procedure
Brand: Vita e Pensiero
Availability: OnlineOnly

digital

Article

Magazine

STATISTICA & APPLICAZIONI

Section

Open Access

Title

Nonparametric ARCH with additive mean and multiplicative volatility: a new estimation procedure

Author

Luca Bagnato

Publisher

Vita e Pensiero

Format

Article |

Pdf

Pages

Online from

01-2009

Issn

1824-6672 (print) | 2283-6659 (digital)

Write a comment for this product

Download

Ebook format Pdf readable on these devices:

Computer
with Software:
- Adobe PDF Reader
Android
iPhone/Ipad
with App:
- Adobe PDF Reader
E-Book Reader
Ibs Tolino
Kobo

Description Readers' comments

Motivated by the misspecification problem in time series analysis, the nonparametric approach has quickly developed in the latest years. First models in literature were focused on the estimation of the conditional mean. It is well known that alongside the conditional mean it is important to study the series volatility (conditional variance). The following paper deals with nonparametric autoregression with multiplicative volatility and additive mean as studied by Yang et al. (1999). A new estimation procedure is here provided. The procedure uses the residual-based estimator, backfitting algorithm and the local polynomial estimation. Some applications with simulated and real data will be presented.

Enter a comment for Nonparametric ARCH with additive mean and multiplicative volatility: a new estimation procedure