Linton, Oliver B. and Yan, Yang (2011) Semi- and nonparametric ARCH processes. Journal of Probability and Statistics, 2011. pp. 1-17. ISSN 1687-952X
Full text not available from this repository.Abstract
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.
| Item Type: | Article |
|---|---|
| Official URL: | http://www.hindawi.com/journals/jps/ |
| Additional Information: | © 2011 Hindawi Publishing Corporation |
| Divisions: | Economics STICERD Financial Markets Group |
| Subjects: | H Social Sciences > HG Finance |
| Date Deposited: | 03 May 2011 09:16 |
| Last Modified: | 13 Nov 2024 05:45 |
| URI: | http://eprints.lse.ac.uk/id/eprint/35749 |
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