000			03412nam a22005055i 4500
001			978-3-642-18324-9
003			DE-He213
005			20140220083753.0
007			cr nn 008mamaa
008			110606s2011 gw | s |||| 0|eng d
020			_a9783642183249 _9978-3-642-18324-9
024	7		_a10.1007/978-3-642-18324-9 _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		_aBäuerle, Nicole. _eauthor.
245	1	0	_aMarkov Decision Processes with Applications to Finance _h[electronic resource] / _cby Nicole Bäuerle, Ulrich Rieder.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2011.
300			_aXVI, 388p. 24 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aUniversitext, _x0172-5939
505	0		_aPreface -- 1.Introduction and First Examples -- Part I Finite Horizon Optimization Problems and Financial Markets -- 2.Theory of Finite Horizon Markov Decision Processes -- 3.The Financial Markets -- 4.Financial Optimization Problems -- Part II Partially Observable Markov Decision Problems -- 5.Partially Observable Markov Decision Processes -- 6.Partially Observable Markov Decision Problems in Finance -- Part III Infinite Horizon Optimization Problems -- 7.Theory of Infinite Horizon Markov Decision Processes -- 8.Piecewise Deterministic Markov Decision Processes -- 9.Optimization Problems in Finance and Insurance -- Part IV Stopping Problems -- 10.Theory of Optimal Stopping Problems -- 11.Stopping Problems in Finance -- Part V Appendix -- A.Tools from Analysis -- B.Tools from Probability -- C.Tools from Mathematical Finance -- References -- Index.
520			_aThe theory of Markov decision processes focuses on controlled Markov chains in discrete time. The authors establish the theory for general state and action spaces and at the same time show its application by means of numerous examples, mostly taken from the fields of finance and operations research. By using a structural approach many technicalities (concerning measure theory) are avoided. They cover problems with finite and infinite horizons, as well as partially observable Markov decision processes, piecewise deterministic Markov decision processes and stopping problems. The book presents Markov decision processes in action and includes various state-of-the-art applications with a particular view towards finance. It is useful for upper-level undergraduates, Master's students and researchers  in both applied probability and finance, and provides exercises (without solutions).
650		0	_aMathematics.
650		0	_aFinance.
650		0	_aDistribution (Probability theory).
650	1	4	_aMathematics.
650	2	4	_aProbability Theory and Stochastic Processes.
650	2	4	_aQuantitative Finance.
650	2	4	_aApplications of Mathematics.
700	1		_aRieder, Ulrich. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783642183232
830		0	_aUniversitext, _x0172-5939
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-642-18324-9
912			_aZDB-2-SMA
999			_c107410 _d107410