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LEADER: 03441nam a22004935a 4500
001 014157662-6
005 20141003190132.0
008 121227s1998 xxu| o ||0| 0|eng d
020 $a9780387227054
020 $a9781441928528 (ebk.)
020 $a9780387227054
020 $a9781441928528
024 7 $a10.1007/b98840$2doi
035 $a(Springer)9780387227054
040 $aSpringer
050 4 $aHB135-147
072 7 $aBUS027000$2bisacsh
072 7 $aKF$2bicssc
072 7 $aMAT003000$2bisacsh
082 04 $a519$223
100 1 $aKaratzas, Ioannis,$eauthor.
245 10 $aMethods of Mathematical Finance /$cby Ioannis Karatzas, Steven E. Shreve.
264 1 $aNew York, NY :$bSpringer New York :$bSpringer,$c1998.
300 $aXV, 415 p.$bonline resource.
336 $atext$btxt$2rdacontent
337 $acomputer$bc$2rdamedia
338 $aonline resource$bcr$2rdacarrier
347 $atext file$bPDF$2rda
490 1 $aApplications of Mathematics, Stochastic Modelling and Applied Probability,$x0172-4568 ;$v39
505 0 $aA Brownian Model of Financial Markets -- Contingent Claim Valuation in a Complete Market -- Single-Agent Consumption and Investment -- Equilibrium in a Complete Market -- Contingent Claims in Incomplete Markets -- Constrained Consumption and Investment.
520 $aThis book is intended for readers who are quite familiar with probability and stochastic processes but know little or nothing about ?nance. It is written in the de?nition/theorem/proof style of modern mathematics and attempts to explain as much of the ?nance motivation and terminology as possible. A mathematical monograph on ?nance can be written today only - cause of two revolutions that have taken place on Wall Street in the latter half of the twentieth century. Both these revolutions began at universities, albeit in economics departments and business schools, not in departments of mathematicsor statistics. Theyhaveledinexorably,however,to anes- lation in the level of mathematics (including probability, statistics, partial di?erential equations and their numerical analysis) used in ?nance, to a point where genuine research problems in the former ?elds are now deeply intertwined with the theory and practice of the latter. The ?rst revolution in ?nance began with the 1952 publication of “Po- folio Selection,” an early version of the doctoral dissertation of Harry Markowitz. This publication began a shift away from the concept of t- ing to identify the “best” stock for an investor, and towards the concept of trying to understand and quantify the trade-o?s between risk and - turn inherent in an entire portfolio of stocks. The vehicle for this so-called mean–variance analysis of portfolios is linear regression; once this analysis is complete, one can then address the optimization problem of choosing the portfolio with the largest mean return, subject to keeping the risk (i. e.
650 20 $aEconomics.
650 10 $aMathematics.
650 0 $aDistribution (Probability theory)
650 0 $aEconomics.
650 0 $aFinance.
650 0 $aMathematics.
650 24 $aProbability Theory and Stochastic Processes.
650 24 $aQuantitative Finance.
700 1 $aShreve, Steven E.,$eauthor.
776 08 $iPrinted edition:$z9781441928528
830 0 $aApplications of Mathematics, Stochastic Modelling and Applied Probability ;$v39.
988 $a20140910
906 $0VEN