The Continuum-GMM Estimation: Theory and Application

Rachidi Kotchoni and Marine Carrasco

Post-Print from HAL

Abstract: By avoiding discretization, the Generalized Method of Moment based on a Continuum of moment conditions (CGMM) permits to effciently use the information content of a continuum moment restrictions. When the moment restrictions are deduced from a characteristic function, the CGMM has the potential to achieve the maximum likelihood efficiency. This chapter reviews the theory underlying the CGMM procedure, discusses the properties of the CGMM estimator and presents numerical algorithms for its implementation. An empirical application is proposed where a Variance Gamma model is fitted to the monthly increments of the USD/GBP exchange rates. We find that the variance forecasts inferred from the Variance Gamma model are of poor quality. A model that specifies the variance as a dependent process should deliver better forecasts. JEL Classification: C00, C13, C15

Keywords: [No; keyword; available] (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations:

Published in International Financial Markets [Book], Volume 1, Taylor & Francis, 2019

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
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:hal:journl:hal-02435760

Access Statistics for this paper

More papers in Post-Print from HAL
Bibliographic data for series maintained by CCSD ().