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001			62-091109
003			CH-001817-3
005			20170613140738.0
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008			091109e20070906sz fot ||| 0|eng d
020			_a9783037195352
024	7	0	_a10.4171/035 _2doi
040			_ach0018173
072		7	_aPBT _2bicssc
084			_a60-xx _a91-xx _2msc
100	1		_aBalkema, Guus, _eauthor.
245	1	0	_aHigh Risk Scenarios and Extremes _h[electronic resource] : _bA geometric approach / _cGuus Balkema, Paul Embrechts
260	3		_aZuerich, Switzerland : _bEuropean Mathematical Society Publishing House, _c2007
264		1	_aZuerich, Switzerland : _bEuropean Mathematical Society Publishing House, _c2007
300			_a1 online resource (388 pages)
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	0		_aZurich Lectures in Advanced Mathematics (ZLAM)
506	1		_aRestricted to subscribers: _uhttp://www.ems-ph.org/ebooks.php
520			_aQuantitative 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 first part is an elegant exposition of coordinatewise extreme value theory; the second half develops the more basic geometric theory. Besides a precise mathematical deduction of the main results, the text yields numerous discussions of a more applied nature. A twenty page preview introduces the key concepts; the extensive introduction provides links to financial mathematics and insurance theory. 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.
650	0	7	_aProbability & statistics _2bicssc
650	0	7	_aProbability theory and stochastic processes _2msc
650	0	7	_aGame theory, economics, social and behavioral sciences _2msc
700	1		_aBalkema, Guus, _eauthor.
700	1		_aEmbrechts, Paul, _eauthor.
856	4	0	_uhttps://doi.org/10.4171/035
856	4	2	_3cover image _uhttp://www.ems-ph.org/img/books/balkema_mini.jpg
942			_2EBK13751 _cEBK
999			_c50375 _d50375