Robust and Efficient Estimation of the Tail Index of a Single-Parameter Pareto Distribution

By Vytaras Brazauskas, Robert Serfling. 2000

83 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/74779edc35075acbdaa2a141b77ab2640e32b074

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Economics and Econometrics

1. Ricardas Zitikis
2. B. Jones
3. Vytaras Brazauskas
4. Madan Lal Puri
5. Barry C. Arnold
6. Robert Serfling
7. Maria L. Rizzo
8. Andreas Kleefeld

In Finance

1. Ricardas Zitikis
2. B. Jones
3. Vytaras Brazauskas
4. Robert Serfling
5. Madan Lal Puri
6. Barry C. Arnold
7. Milan Stehlík
8. Dieter Schell

In Management Science and Operations Research

1. Ricardas Zitikis
2. B. Jones
3. Madan Lal Puri
4. Vytaras Brazauskas
5. Robert Serfling
6. Barry C. Arnold
7. Edward Furman
8. Ying Wei

Citations in the corpus

• Estimating conditional tail expectation with actuarial applications in view (2008, methodology): “A more detailed discussion of these applications along with various techniques for estimation of parameters of these families can be found in Brazauskas and Serfling (2000), Serfling (2002) and Brazauskas and Kaiser (2004).”
• Efficient and Robust Fitting of Lognormal Distributions (2002, background): “While the most favorable choice in Table 5 is (k, m )=( 9, 9), with ARE = 0.98, we must also take into account the corresponding BP value, 0.07, from Tables 1 and 3. If somewhat higher BP values are needed, at the cost of a small reduction in ARE, the choice (k, m )= (5, 5 ) offers ARE = 0.95 with ”
• Pareto and Generalized Pareto Distributions (2008, background): “Detailed discussion of generalized median estimates, together with comparisons with competing estimates in terms of asymptotic relative efficiency and breakdown points may be found in Brazauskas and Serfling (2000) .”
• Robust fitting of claim severity distributions and the method of trimmed moments (2009, methodology): “This has been accomplished by Brazauskas and Serfling (2000b) in the Pareto and exponential cases.”
• The harmonic moment tail index estimator: asymptotic distribution and robustness (2014, background): “For instance, Brazauskas and Serfling (2000) studied the lack of robustness of classical tail index estimators in a simple one-parameter Pareto model F(x) = 1 − (σ/x)1/γ , (x ≥ σ ) with σ > 0 known.”