• Medientyp: E-Book
  • Titel: A Statistical Methodology for Assessing the Maximal Strength of Tail Dependence
  • Beteiligte: Sun, Ning [Verfasser:in]; Yang, Chen [Sonstige Person, Familie und Körperschaft]; Zitikis, Ricardas [Sonstige Person, Familie und Körperschaft]
  • Erschienen: [S.l.]: SSRN, [2020]
  • Umfang: 1 Online-Ressource (29 p)
  • Sprache: Englisch
  • DOI: 10.2139/ssrn.3545598
  • Identifikator:
  • Schlagwörter: copula ; maximal tail dependence ; statistical estimation ; Kendall's distribution
  • Entstehung:
  • Anmerkungen: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments February 27, 2020 erstellt
  • Beschreibung: Several diagonal-based tail dependence indices have been suggested in the literature to quantify tail dependence. They have well-developed statistical inference theories but tend to underestimate tail dependence. For those problems when assessing the maximal strength of dependence is important (e.g., co-movements of financial instruments), the maximal tail dependence index was introduced, but it has so far lacked empirical estimators and statistical inference results, thus hindering its practical use. In the present paper we suggest an empirical estimator for the index, explore its statistical properties, and illustrate its performance on simulated data
  • Zugangsstatus: Freier Zugang