The Resource High risk scenarios and extremes : a geometric approach, Guus Balkema, Paul Embrechts
High risk scenarios and extremes : a geometric approach, Guus Balkema, Paul Embrechts
Resource Information
The item High risk scenarios and extremes : a geometric approach, Guus Balkema, Paul Embrechts represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri Libraries.This item is available to borrow from 1 library branch.
Resource Information
The item High risk scenarios and extremes : a geometric approach, Guus Balkema, Paul Embrechts represents a specific, individual, material embodiment of a distinct intellectual or artistic creation found in University of Missouri Libraries.
This item is available to borrow from 1 library branch.
- Summary
- "Quantitative Risk Management (QRM) has become a field of research of considerable importance to numerous areas of application, including insurance, banking, energy, medicine, reliability. Mainly motivated by examples from insurance and finance, the authors develop a theory for handling multivariate extremes. The approach borrows ideas from portfolio theory and aims at an intuitive approach in the spirit of the Peaks over Thresholds method. The point of view is geometric. It leads to a probabilistic description of what in QRM language may be referred to as a high risk scenario: the conditional behaviour of risk factors given that a large move on a linear combination [portfolio, say] has been observed. The theoretical models which describe such conditional extremal behaviour are characterized and their relation to the limit theory for coordinatewise maxima is explained." "The book is based on a graduate course on point processes and extremes. It could form the basis for an advanced course on multivariate extreme value theory or a course on mathematical issues underlying risk. Students in statistics and finance with a mathematical, quantitative background are the prime audience. Actuaries and risk managers involved in data based risk analysis will find the models discussed in the book stimulating. The text contains many indications for further research."--BOOK JACKET
- Language
- eng
- Extent
- xiii, 375 pages
- Contents
-
- univariate theory: maxima and exceedances
- Componentwise maxima
- High risk scenarios
- The
- Gauss-exponential domain, rotund sets
- The
- Gauss-exponential domain, unimodal distributions
- Flat functions and flat measures
- Heavy tails and bounded vectors
- The
- Foreword -- Introduction
- multivariate GPDs
- Exceedances over horizontal thresholds
- Horizontal thresholds -- examples
- Heavy tails and eliptic thresholds
- Heavy tails -- examples
- Regular variation and excess measures
- Point processes
- Poisson point processes
- The
- distribution
- Convergence
- Converging sample clouds
- The
- Isbn
- 9783037190357
- Label
- High risk scenarios and extremes : a geometric approach
- Title
- High risk scenarios and extremes
- Title remainder
- a geometric approach
- Statement of responsibility
- Guus Balkema, Paul Embrechts
- Language
- eng
- Summary
- "Quantitative Risk Management (QRM) has become a field of research of considerable importance to numerous areas of application, including insurance, banking, energy, medicine, reliability. Mainly motivated by examples from insurance and finance, the authors develop a theory for handling multivariate extremes. The approach borrows ideas from portfolio theory and aims at an intuitive approach in the spirit of the Peaks over Thresholds method. The point of view is geometric. It leads to a probabilistic description of what in QRM language may be referred to as a high risk scenario: the conditional behaviour of risk factors given that a large move on a linear combination [portfolio, say] has been observed. The theoretical models which describe such conditional extremal behaviour are characterized and their relation to the limit theory for coordinatewise maxima is explained." "The book is based on a graduate course on point processes and extremes. It could form the basis for an advanced course on multivariate extreme value theory or a course on mathematical issues underlying risk. Students in statistics and finance with a mathematical, quantitative background are the prime audience. Actuaries and risk managers involved in data based risk analysis will find the models discussed in the book stimulating. The text contains many indications for further research."--BOOK JACKET
- Cataloging source
- COO
- http://library.link/vocab/creatorName
- Balkema, A. A
- Index
- index present
- LC call number
- QA278
- LC item number
- .B35 2007
- Literary form
- non fiction
- Nature of contents
- bibliography
- http://library.link/vocab/relatedWorkOrContributorDate
- 1953-
- http://library.link/vocab/relatedWorkOrContributorName
- Embrechts, Paul
- Series statement
- Zurich lectures in advanced mathematics
- http://library.link/vocab/subjectName
-
- Multivariate analysis
- Extreme value theory
- Point processes
- Risk assessment
- Label
- High risk scenarios and extremes : a geometric approach, Guus Balkema, Paul Embrechts
- Bibliography note
- Includes bibliographical references (p. ([361]-368) and index
- Carrier category
- volume
- Carrier category code
-
- nc
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
-
- univariate theory: maxima and exceedances
- Componentwise maxima
- High risk scenarios
- The
- Gauss-exponential domain, rotund sets
- The
- Gauss-exponential domain, unimodal distributions
- Flat functions and flat measures
- Heavy tails and bounded vectors
- The
- Foreword -- Introduction
- multivariate GPDs
- Exceedances over horizontal thresholds
- Horizontal thresholds -- examples
- Heavy tails and eliptic thresholds
- Heavy tails -- examples
- Regular variation and excess measures
- Point processes
- Poisson point processes
- The
- distribution
- Convergence
- Converging sample clouds
- The
- Control code
- 191922927
- Dimensions
- 24 cm
- Extent
- xiii, 375 pages
- Isbn
- 9783037190357
- Media category
- unmediated
- Media MARC source
- rdamedia
- Media type code
-
- n
- System control number
- (OCoLC)191922927
- Label
- High risk scenarios and extremes : a geometric approach, Guus Balkema, Paul Embrechts
- Bibliography note
- Includes bibliographical references (p. ([361]-368) and index
- Carrier category
- volume
- Carrier category code
-
- nc
- Carrier MARC source
- rdacarrier
- Content category
- text
- Content type code
-
- txt
- Content type MARC source
- rdacontent
- Contents
-
- univariate theory: maxima and exceedances
- Componentwise maxima
- High risk scenarios
- The
- Gauss-exponential domain, rotund sets
- The
- Gauss-exponential domain, unimodal distributions
- Flat functions and flat measures
- Heavy tails and bounded vectors
- The
- Foreword -- Introduction
- multivariate GPDs
- Exceedances over horizontal thresholds
- Horizontal thresholds -- examples
- Heavy tails and eliptic thresholds
- Heavy tails -- examples
- Regular variation and excess measures
- Point processes
- Poisson point processes
- The
- distribution
- Convergence
- Converging sample clouds
- The
- Control code
- 191922927
- Dimensions
- 24 cm
- Extent
- xiii, 375 pages
- Isbn
- 9783037190357
- Media category
- unmediated
- Media MARC source
- rdamedia
- Media type code
-
- n
- System control number
- (OCoLC)191922927
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<div class="citation" vocab="http://schema.org/"><i class="fa fa-external-link-square fa-fw"></i> Data from <span resource="http://link.library.missouri.edu/portal/High-risk-scenarios-and-extremes--a-geometric/RH9Iq_oAtds/" typeof="Book http://bibfra.me/vocab/lite/Item"><span property="name http://bibfra.me/vocab/lite/label"><a href="http://link.library.missouri.edu/portal/High-risk-scenarios-and-extremes--a-geometric/RH9Iq_oAtds/">High risk scenarios and extremes : a geometric approach, Guus Balkema, Paul Embrechts</a></span> - <span property="potentialAction" typeOf="OrganizeAction"><span property="agent" typeof="LibrarySystem http://library.link/vocab/LibrarySystem" resource="http://link.library.missouri.edu/"><span property="name http://bibfra.me/vocab/lite/label"><a property="url" href="http://link.library.missouri.edu/">University of Missouri Libraries</a></span></span></span></span></div>
