MARC Record from Library of Congress

LEADER: 02574cam a2200301 a 4500
001 2012016086
003 DLC
005 20130110084408.0
008 120531s2012 flua b 001 0 eng
010 $a 2012016086
020 $a9781439858240
040 $aDLC$cDLC
042 $apcc
050 00 $aHG106$b.W35 2012
082 00 $a332.01/518282$223
084 $aBUS027000$aMAT000000$aMAT029000$2bisacsh
100 1 $aWang, Hui,$d1976-
245 10 $aMonte Carlo simulation with applications to finance /$cHui Wang.
260 $aBoca Raton :$bCRC Press,$c2012.
300 $a282 p. :$bill. ;$c25 cm.
490 0 $aChapman & Hall/CRC financial mathematics series
504 $aIncludes bibliographical references (p. [277]-279) and index.
520 $a"Preface This book can serve as the text for a one-semester course on Monte Carlo simulation. The intended audience is advanced undergraduate students or students on master's programs who wish to learn the basics of this exciting topic and its applications to finance. The book is largely self-contained. The only prerequisite is some experience with probability and statistics. Prior knowledge on option pricing is helpful but not essential. As in any study of Monte Carlo simulation, coding is an integral part and cannot be ignored. The book contains a large number of MATLAB coding exercises. They are designed in a progressive manner so that no prior experience with MATLAB is required. Much of the mathematics in the book is informal. For example, randomvariables are simply defined to be functions on the sample space, even though they should be measurable with respect to appropriate algebras; exchanging the order of integrations is carried out liberally, even though it should be justified by the Tonelli-Fubini Theorem. The motivation for doing so is to avoid the technical measure theoretic jargon, which is of little concern in practice and does not help much to further the understanding of the topic. The book is an extension of the lecture notes that I have developed for an undergraduate course on Monte Carlo simulation at Brown University. I would like to thank the students who have taken the course, as well as the Division of Applied Mathematics at Brown, for their support. Hui Wang Providence, Rhode Island January, 2012"--$cProvided by publisher.
650 0 $aFinance$xMathematical methods.
650 0 $aMonte Carlo method.
650 7 $aBUSINESS & ECONOMICS / Finance.$2bisacsh
650 7 $aMATHEMATICS / General.$2bisacsh
650 7 $aMATHEMATICS / Probability & Statistics / General.$2bisacsh