A New Regression-Based Tail Index Estimator
A New Regression-Based Tail Index Estimator
ABSTRACT
A new regression-based approach for the estimation of the tail index of heavy-tailed distributions with several important properties is introduced. First, it provides a bias reduction when compared to available regression-based methods; second, it is resilient to the choice of the tail length used for the estimation of the tail index; third, when the effect of the slowly varying function at infinity of the Pareto distribution vanishes slowly, it continues to perform satisfactorily; and fourth, it performs well under dependence of unknown form. An approach to compute the asymptotic variance under time dependence and conditional heteroskcedasticity is also provided.
WITH
João Nicolau, ISEG-Universidade de Lisboa
About Instructors
Paulo Rodrigues
Paulo M. M. Rodrigues is a senior research economist at the Economics and Research Department of the Bank of Portugal and Professor of Econometrics at Nova School of Business and Economics. His research interests include time-series econometrics, financial econometrics and empirical macroeconomics and finance.