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Extreme value index estimation with ...

Oregon State University.

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Extreme value index estimation with applications to modeling extreme insurance losses and sea surface temperatures.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Extreme value index estimation with applications to modeling extreme insurance losses and sea surface temperatures./
Author:	Henry, John B., III.
Description:	99 p.
Notes:	Source: Dissertation Abstracts International, Volume: 69-06, Section: B, page: 3610.
Contained By:	Dissertation Abstracts International69-06B.
Subject:	Economics, Finance. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3321089
ISBN:	9780549710790

Extreme value index estimation with applications to modeling extreme insurance losses and sea surface temperatures.
Henry, John B., III.

Extreme value index estimation with applications to modeling extreme insurance losses and sea surface temperatures. - 99 p.

Source: Dissertation Abstracts International, Volume: 69-06, Section: B, page: 3610.

Thesis (Ph.D.)--Oregon State University, 2008.

The extreme value index (EVI) links the generalized extreme value (GEV) distribution and the generalized Pareto (GP) distribution. These two distributions are fundamental in extreme value theory (EVT), with the GEV distribution being the only possible non-degenerate limiting distribution of properly normalized maxima of iid random variables, and the GP distribution appearing as the limit distribution of scaled excesses over high thresholds. The reciprocal of the EVI is know as the Pareto tail index (provided the EVI is positive). A new tail index estimator is proposed here that is obtained by matching general theoretical harmonic moments with corresponding empirical moments. Theoretical properties of the estimator are provided along with applications and a comparison to other tail index estimators. A tail index estimator suitable for partitioned data is also given. Having only partitioned data to work with is a circumstance sometimes faced by actuaries. Strengths and weaknesses of this estimator are explored through simulation. An application of the estimator to real world partitioned insurance data is given. The sign of the EVI is of interest when one is interested in testing whether or not a distribution has a bounded tail. In this work, the controversial thermostat hypothesis for sea surface temperature (SST) is investigated in this framework. A GP model using SST data from the western Pacific warm pool provides some evidence of a temperature upper bound between 31.2°C and 32.0°C. This estimate is compared those obtained elsewhere using the ocean heat budget and other physical models.

ISBN: 9780549710790Subjects--Topical Terms:

626650
Economics, Finance.

Extreme value index estimation with applications to modeling extreme insurance losses and sea surface temperatures.
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100 1 $a Henry, John B., III. $3 1064932
245 1 0 $a Extreme value index estimation with applications to modeling extreme insurance losses and sea surface temperatures.
300 $a 99 p.
500 $a Source: Dissertation Abstracts International, Volume: 69-06, Section: B, page: 3610.
502 $a Thesis (Ph.D.)--Oregon State University, 2008.
520 $a The extreme value index (EVI) links the generalized extreme value (GEV) distribution and the generalized Pareto (GP) distribution. These two distributions are fundamental in extreme value theory (EVT), with the GEV distribution being the only possible non-degenerate limiting distribution of properly normalized maxima of iid random variables, and the GP distribution appearing as the limit distribution of scaled excesses over high thresholds. The reciprocal of the EVI is know as the Pareto tail index (provided the EVI is positive). A new tail index estimator is proposed here that is obtained by matching general theoretical harmonic moments with corresponding empirical moments. Theoretical properties of the estimator are provided along with applications and a comparison to other tail index estimators. A tail index estimator suitable for partitioned data is also given. Having only partitioned data to work with is a circumstance sometimes faced by actuaries. Strengths and weaknesses of this estimator are explored through simulation. An application of the estimator to real world partitioned insurance data is given. The sign of the EVI is of interest when one is interested in testing whether or not a distribution has a bounded tail. In this work, the controversial thermostat hypothesis for sea surface temperature (SST) is investigated in this framework. A GP model using SST data from the western Pacific warm pool provides some evidence of a temperature upper bound between 31.2°C and 32.0°C. This estimate is compared those obtained elsewhere using the ocean heat budget and other physical models.
590 $a School code: 0172.
650 4 $a Economics, Finance. $3 626650
650 4 $a Mathematics. $3 515831
650 4 $a Statistics. $3 517247
690 $a 0405
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710 2 $a Oregon State University. $3 625720
773 0 $t Dissertation Abstracts International $g 69-06B.
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791 $a Ph.D.
792 $a 2008
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3321089