Robust estimation of the Pareto tail index: a Monte Carlo analysis
نویسندگان
چکیده
منابع مشابه
Robust estimation of the Pareto index: A Monte Carlo Analysis
The Pareto distribution is often used in many areas of economics to model the right tail of heavytailed distributions. However, the standard method of estimating the shape parameter (the Pareto index) of this distribution– the maximum likelihood estimator (MLE) – is non-robust, in the sense that it is very sensitive to extreme observations, data contamination or model deviation. In recent years...
متن کاملOn the Tail Index Estimation of an Autoregressive Pareto Process
In this paper we consider an autoregressive Pareto process which can be used as an alternative to heavy tailed MARMA. We focus on the tail behavior and prove that the tail empirical quantile function can be approximated by a Gaussian process. This result allows to derive a class of consistent and asymptotically normal estimators for the shape parameter. We will see through simulation that the u...
متن کاملA robust estimator for the tail index of Pareto-type distributions
In extreme value statistics, the extreme value index is a well-known parameter to measure the tail heaviness of a distribution. Pareto-type distributions, with strictly positive extreme value index (or tail index) are considered. The most prominent extreme value methods are constructed on efficient maximum likelihood estimators based on specific parametric models which are fitted to excesses ov...
متن کاملConvergence analysis of multifidelity Monte Carlo estimation
The multifidelity Monte Carlo method provides a general framework for combining cheap low-fidelity approximations of an expensive highfidelity model to accelerate the Monte Carlo estimation of statistics of the high-fidelity model output. In this work, we investigate the properties of multifidelity Monte Carlo estimation in the setting where a hierarchy of approximations can be constructed with...
متن کاملOn robust tail index estimation for linear long-memory processes
We consider robust estimation of the tail index α for linear longmemory processes Xt = ∑∞ j=0 ajεt−j with i.i.d. innovations εj following a symmetric α-stable law (1 < α < 2) and coefficients aj ∼ c · j−β ( 1 α < β < 1). Estimates based on the left and right tail respectively are obtained together with a combined statistic with improved efficiency, and a test statistic comparing both tails. Asy...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Empirical Economics
سال: 2015
ISSN: 0377-7332,1435-8921
DOI: 10.1007/s00181-015-0989-9