Semi- and Nonparametric ARCH Processes

Joint Authors

Linton, Oliver B.
Yan, Yang

Source

Journal of Probability and Statistics

Issue

Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-17, 17 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2010-08-05

Country of Publication

Egypt

No. of Pages

17

Main Subjects

Mathematics

Abstract EN

ARCH/GARCH modelling has been successfully applied in empirical finance for many years.

This paper surveys the semiparametric and nonparametric methods in univariate and multivariate ARCH/GARCH models.

First, we introduce some specific semiparametric models and investigate the semiparametric and nonparametrics estimation techniques applied to: the error density, the functional form of the volatility function, the relationship between mean and variance, long memory processes, locally stationary processes, continuous time processes and multivariate models.

The second part of the paper is about the general properties of such processes, including stationary conditions, ergodic conditions and mixing conditions.

The last part is on the estimation methods in ARCH/GARCH processes.

American Psychological Association (APA)

Linton, Oliver B.& Yan, Yang. 2010. Semi- and Nonparametric ARCH Processes. Journal of Probability and Statistics،Vol. 2011, no. 2011, pp.1-17.
https://search.emarefa.net/detail/BIM-506992

Modern Language Association (MLA)

Linton, Oliver B.& Yan, Yang. Semi- and Nonparametric ARCH Processes. Journal of Probability and Statistics No. 2011 (2011), pp.1-17.
https://search.emarefa.net/detail/BIM-506992

American Medical Association (AMA)

Linton, Oliver B.& Yan, Yang. Semi- and Nonparametric ARCH Processes. Journal of Probability and Statistics. 2010. Vol. 2011, no. 2011, pp.1-17.
https://search.emarefa.net/detail/BIM-506992

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-506992