Dependence Structure Studies via Copula Characteristic Function Approach

• Grant number: 18/05262-7
• Support Opportunities: Scholarships in Brazil - Post-Doctoral
• Start date: September 01, 2018
• End date: January 31, 2019
• Field of knowledge: Physical Sciences and Mathematics - Probability and Statistics - Applied Probability and Statistics
• Principal Investigator: Nikolai Valtchev Kolev
• Grantee: Tarik Bahraoui
• Host Institution: Instituto de Matemática e Estatística (IME). Universidade de São Paulo (USP). São Paulo , SP, Brazil

Abstract

The aim of this project is to launch characteristic function associated to copula as a new tool for dependence modeling. Copula characteristic function approach is applied to test the hypotheses of independence and exchangeability. The corresponding non-parametric rank tests are based on empirical version of copula characteristic function and involve degenerate V-statistics theory, with a limited use in dependence modeling. We introduce a new measure of bivariate asymmetry based on copula characteristic function. The proposed methodology and associated computational procedures will be compared with existing once and will be applied for analysis of big data sets.

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

BAHRAOUI, TARIK; KOLEV, NIKOLAI. New Measure of the Bivariate Asymmetry. SANKHYA-SERIES A-MATHEMATICAL STATISTICS AND PROBABILITY, MAR 2020. (13/07375-0, 18/05262-7)

BAHRAOUI, TARIK; KOLEV, NIKOLAI. New Measure of the Bivariate Asymmetry. SANKHYA-SERIES A-MATHEMATICAL STATISTICS AND PROBABILITY, v. 83, n. 1, p. 28-pg., 2020-03-20. (13/07375-0, 18/05262-7)