Specification procedures for multivariate stable-Paretian laws for independent andforconditionally heteroskedastic data
| dc.contributor.author | Meintanis, Simos G. | |
| dc.contributor.author | Nolan, John P. | |
| dc.contributor.author | Pretorius, Charl | |
| dc.date.accessioned | 2025-12-03T13:59:03Z | |
| dc.date.issued | 2024 | |
| dc.description | Journal Article, Pure and Applied Analytics, North-West University, Potchefstroom Campus | |
| dc.description.abstract | We consider goodness-of-fit methods for multivariate symmetric and asymmetric stable Paretian random vectors in arbitrary dimension. The methods are based on the empirical characteristic function and are implemented both in the i.i.d. context as well as for innovations in GARCH models. Asymptotic properties of the proposed procedures are discussed, while the finite-sample properties are illustrated by means of an extensive Monte Carlo study. The procedures are also applied to real data from the financial markets. | |
| dc.identifier.citation | Meintanis, S.G et al. 2024. Specification procedures for multivariate stable-Paretian laws for independent and for conditionally heteroskedastic data. TEST, 33(2), pp.517-539.. https://doi.org/10.1007/s11749-023-00909-3 | |
| dc.identifier.uri | http://hdl.handle.net/10394/44605 | |
| dc.language.iso | en | |
| dc.publisher | Springer New York | |
| dc.subject | Empirical characteristic function | |
| dc.subject | Goodness-of-fit | |
| dc.subject | Heavy-tailed distribution | |
| dc.title | Specification procedures for multivariate stable-Paretian laws for independent andforconditionally heteroskedastic data | |
| dc.type | Article |