Details

Autor(en) / Beteiligte

• Liao, Xin
• Peng, Liang
• Peng, ZuoXiang
• Zheng, YanTing

Titel

Dynamic bivariate normal copula

Ist Teil von

• Science China. Mathematics, 2016-05, Vol.59 (5), p.955-976

Ort / Verlag

Beijing: Science China Press

Erscheinungsjahr

2016

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Normal copula with a correlation coefficient between-1 and 1 is tail independent and so it severely underestimates extreme probabilities. By letting the correlation coefficient in a normal copula depend on the sample size, H¨usler and Reiss（1989） showed that the tail can become asymptotically dependent. We extend this result by deriving the limit of the normalized maximum of n independent observations, where the i-th observation follows from a normal copula with its correlation coefficient being either a parametric or a nonparametric function of i/n. Furthermore, both parametric and nonparametric inference for this unknown function are studied, which can be employed to test the condition by H¨usler and Reiss（1989）. A simulation study and real data analysis are presented too.