LEADER 03759nam 2200577 450 001 9910271007303321 005 20200520144314.0 010 $a1-119-38808-2 010 $a1-119-38805-8 010 $a1-119-38804-X 035 $a(CKB)4340000000203232 035 \\$a(Safari)9781119387619 035 $a(OCoLC)1031279391 035 $a(Au-PeEL)EBL5046858 035 $a(CaPaEBR)ebr11441146 035 $a(CaONFJC)MIL1036922 035 $a(OCoLC)1004196867 035 $a(CaSebORM)9781119387619 035 $a(MiAaPQ)EBC5046858 035 $a(EXLCZ)994340000000203232 100 $a20171014h20172017 uy 0 101 0 $aeng 135 $aurunu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aApplied probabilistic calculus for financial engineering $ean introduction using R /$fby Bertram K.C. Chan 205 $a1st edition 210 1$aHoboken, New Jersey :$cWiley,$d2017. 210 4$dİ2017 215 $a1 online resource (1 volume) $cillustrations 311 $a1-119-38761-2 320 $aIncludes bibliographical references and index. 330 $aIllustrates how R may be used successfully to solve problems in quantitative finance Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R provides R recipes for asset allocation and portfolio optimization problems. It begins by introducing all the necessary probabilistic and statistical foundations, before moving on to topics related to asset allocation and portfolio optimization with R codes illustrated for various examples. This clear and concise book covers financial engineering, using R in data analysis, and univariate, bivariate, and multivariate data analysis. It examines probabilistic calculus for modeling financial engineering?walking the reader through building an effective financial model from the Geometric Brownian Motion (GBM) Model via probabilistic calculus, while also covering Ito Calculus. Classical mathematical models in financial engineering and modern portfolio theory are discussed?along with the Two Mutual Fund Theorem and The Sharpe Ratio. The book also looks at R as a calculator and using R in data analysis in financial engineering. Additionally, it covers asset allocation using R, financial risk modeling and portfolio optimization using R, global and local optimal values, locating functional maxima and minima, and portfolio optimization by performance analytics in CRAN. Covers optimization methodologies in probabilistic calculus for financial engineering Answers the question: What does a "Random Walk" Financial Theory look like? Covers the GBM Model and the Random Walk Model Examines modern theories of portfolio optimization, including The Markowitz Model of Modern Portfolio Theory (MPT), The Black-Litterman Model, and The Black-Scholes Option Pricing Model Applied Probabilistic Calculus for Financial Engineering: An Introduction Using R s an ideal reference for professionals and students in economics, econometrics, and finance, as well as for financial investment quants and financial engineers. 606 $aFinancial engineering$xMathematical models 606 $aProbabilities 606 $aCalculus 606 $aR (Computer program language) 615 0$aFinancial engineering$xMathematical models. 615 0$aProbabilities. 615 0$aCalculus. 615 0$aR (Computer program language) 676 $a332.015192 700 $aChan$b B. K. C$g(Bertram Kim-Cheong),$0937065 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910271007303321 996 $aApplied probabilistic calculus for financial engineering$92110590 997 $aUNINA