000			03435cam a2200397 i 4500
001			16556087
003			OSt
005			20150904100619.0
008			101129s2011 enka b 001 0 eng
010			_a 2010050362
020			_a9781107444294 (pbk.)
020			_a1107400864 (pbk.)
035			_a(OCoLC)ocn690090166
040			_aDLC _cDLC _erda _dYDX _dBTCTA _dYDXCP _dDLC
042			_apcc
050	0	0	_aQA312 _b.K5867 2011
082	0	0	_a515.42 K839F _223
084			_aMAT034000 _2bisacsh
100	1		_aKopp, P. E., _d1944- _eauthor. _94204
222			_aGratis Collection
245	1	0	_aFrom Measures to Itô Integrals _cEkkehard Kopp.
260			_aCambridge : _bCambridge University Press, _c2011.
300			_avii, 120 pages : _billustrations ; _c22 cm.
490	1		_aAfrican Institute of Mathematics Library Series
504			_aIncludes bibliographical references (page 118) and index.
505	8		_aMachine generated contents note: Preface; 1. Probability and measure; 2. Measures and distribution functions; 3. Measurable functions/random variables; 4. Integration and expectation; 5. Lp-spaces and conditional expectation; 6. Discrete-time martingales; 7. Brownian motion; 8. Stochastic integrals; Bibliography; Index.
520			_a"From Measures to Itô Integrals gives a clear account of measure theory, leading via L2-theory to Brownian motion, Itô integrals and a brief look at martingale calculus. Modern probability theory and the applications of stochastic processes rely heavily on an understanding of basic measure theory. This text is ideal preparation for graduate-level courses in mathematical finance and perfect for any reader seeking a basic understanding of the mathematics underpinning the various applications of Itô calculus"--
520			_a"Undergraduate mathematics syllabi vary considerably in their coverage of measure-theoretic probability theory, so beginning graduates often find substantial gaps in their background when attending modules in advanced analysis, stochastic processes and applications. This text seeks to fill some of these gaps concisely. The exercises form an integral part of the text. The material arose from my experience of teaching AIMS students between 2004 and 2007, of which I retain many fond memories. The AIMS series format allows few explorations of byways; and the objective of arriving at a reasonably honest but concise account of the Itô integral decided most of the material. With motivation from elementary probability we discuss measures and integrals, leading via L2-theory and conditional expectation to discrete martingales and an outline proof of the Radon-Nikodym Theorem. The last two chapters introduce Brownian Motion and Itô integrals, with a brief look at martingale calculus. Here proofs of several key results are only sketched briefly or omitted. The Black-Scholes option pricing model provides the main application. None of the results presented is new; any remaining errors are mine"--
650		0	_aMeasure theory _vTextbooks. _94205
650		0	_aMathematics _93725
830		0	_aAIMS library series. _94206
856	4	2	_3Cover image _uhttp://assets.cambridge.org/97811074/00863/cover/9781107400863.jpg
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2ddc _cREF
999			_c6443 _d6443