000			03415nam a22005055i 4500
001			978-3-540-74011-7
003			DE-He213
005			20161121231214.0
007			cr nn 008mamaa
008			100301s2008 xxu| s |||| 0|eng d
020			_a9783540740117 _9978-3-540-74011-7
024	7		_a10.1007/978-3-540-74011-7 _2doi
050		4	_aQA273.A1-274.9
050		4	_aQA274-274.9
072		7	_aPBT _2bicssc
072		7	_aPBWL _2bicssc
072		7	_aMAT029000 _2bisacsh
082	0	4	_a519.2 _223
100	1		_aShiryaev, Albert N. _eauthor.
245	1	0	_aOptimal Stopping Rules _h[electronic resource] / _cby Albert N. Shiryaev ; edited by B. Rozovskii, G. Grimmett.
264		1	_aNew York, NY : _bSpringer New York, _c2008.
300			_aXII, 220 p. 7 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aStochastic Modelling and Applied Probability, _x0172-4568 ; _v8
505	0		_aRandom Processes: Markov Times -- Optimal Stopping of Markov Sequences -- Optimal Stopping of Markov Processes -- Some Applications to Problems of Mathematical Statistics.
520			_aAlthough three decades have passed since first publication of this book reprinted now as a result of popular demand, the content remains up-to-date and interesting for many researchers as is shown by the many references to it in current publications. The "ground floor" of Optimal Stopping Theory was constructed by A.Wald in his sequential analysis in connection with the testing of statistical hypotheses by non-traditional (sequential) methods. It was later discovered that these methods have, in idea, a close connection to the general theory of stochastic optimization for random processes. The area of application of the Optimal Stopping Theory is very broad. It is sufficient at this point to emphasise that its methods are well tailored to the study of American (-type) options (in mathematics of finance and financial engineering), where a buyer has the freedom to exercise an option at any stopping time. In this book, the general theory of the construction of optimal stopping policies is developed for the case of Markov processes in discrete and continuous time. One chapter is devoted specially to the applications that address problems of the testing of statistical hypotheses, and quickest detection of the time of change of the probability characteristics of the observable processes. The author, A.N.Shiryaev, is one of the leading experts of the field and gives an authoritative treatment of a subject that, 30 years after original publication of this book, is proving increasingly important.
650		0	_aMathematics.
650		0	_aProbabilities.
650		0	_aStatistics.
650	1	4	_aMathematics.
650	2	4	_aProbability Theory and Stochastic Processes.
650	2	4	_aStatistics for Business/Economics/Mathematical Finance/Insurance.
700	1		_aRozovskii, B. _eeditor.
700	1		_aGrimmett, G. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783540740100
830		0	_aStochastic Modelling and Applied Probability, _x0172-4568 ; _v8
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-540-74011-7
912			_aZDB-2-SMA
950			_aMathematics and Statistics (Springer-11649)
999			_c510102 _d510102