Specification procedures for multivariate stable-Paretian laws for independent and for conditionally heteroskedastic data

Simos G. Meintanis (), John P. Nolan and Charl Pretorius
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Simos G. Meintanis: National and Kapodistrian University of Athens
John P. Nolan: American University
Charl Pretorius: North-West University

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2024, vol. 33, issue 2, No 7, 517-539

Abstract: 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.

Keywords: Empirical characteristic function; Goodness-of-fit; Heavy-tailed distribution; 62G20; 62H15; 62M10 (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11749-023-00909-3

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