The replacement of indicator functions by integrated beta kernels in the definition of the empirical tail dependence function is shown to produce a smoothed version of the latter estimator with the same asymptotic distribution but superior finite-sample performance. The link of the new estimator with the empirical beta copula enables a simple but effective resampling scheme.

Additional Metadata
Keywords Bernstein polynomial, Bootstrap, Brown–Resnick process, Copula, Empirical process, Max-linear model, Tail copula, Tail dependence, Weak convergence
Persistent URL dx.doi.org/10.1007/s10687-018-0315-y, hdl.handle.net/1765/105450
Journal Extremes: statistical theory and applications in science, engineering and economics
Citation
Kiriliouk, A.A, Segers, J. (Johan), & Tafakori, L. (Laleh). (2018). An estimator of the stable tail dependence function based on the empirical beta copula. Extremes: statistical theory and applications in science, engineering and economics, 1–20. doi:10.1007/s10687-018-0315-y