國立虎尾科技大學 |

Stochastic analysis for finance with simulations

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Stochastic analysis for finance with simulations/ by Geon Ho Choe.
Author:	Choe, Geon Ho.
Published:	Cham :Springer International Publishing : : 2016.,
Description:	xxxii, 657 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Stochastic analysis. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-25589-7
ISBN:	9783319255897

Stochastic analysis for finance with simulations
Choe, Geon Ho.

Stochastic analysis for finance with simulations[electronic resource] /by Geon Ho Choe. - Cham :Springer International Publishing :2016. - xxxii, 657 p. :ill., digital ;24 cm. - Universitext,0172-5939. - Universitext..

Preface -- Acknowledgements -- List of Figures -- List of Tables -- List of Simulations -- Fundamental Concepts -- Financial Derivatives -- The Lebesgue Integral -- Basic Probability Theory -- Conditional Expectation -- Stochastic Processes -- Brownian Motion -- Girsanov's Theorem -- The Reflection Principle of Brownian Motion -- The Ito Integral -- The Ito Formula -- Stochastic Differential Equations -- The Feynmann-Kac Theorem -- The Binomial Tree Method for Option Pricing -- The Black-Scholes-Merton Differential Equation -- The Martingale Method -- Pricing of Vanilla Options -- Pricing of Exotic Options -- American Options -- The Capital Asset Pricing Model -- Dynamic Programming -- Bond Pricing -- Interest Rate Models -- Numeraires -- Numerical Estimation of Volatility -- Time Series -- Random Numbers -- The Monte Carlo Method for Option Pricing -- Numerical Solution of the Black-Scholes-Merton Equation -- Numerical Solution of Stochastic Differential Equations. Appendices -- Solutions for Selected Problems -- Glossary -- References -- Index.

This book is an introduction to stochastic analysis and quantitative finance; it includes both theoretical and computational methods. Topics covered are stochastic calculus, option pricing, optimal portfolio investment, and interest rate models. Also included are simulations of stochastic phenomena, numerical solutions of the Black-Scholes-Merton equation, Monte Carlo methods, and time series. Basic measure theory is used as a tool to describe probabilistic phenomena. The level of familiarity with computer programming is kept to a minimum. To make the book accessible to a wider audience, some background mathematical facts are included in the first part of the book and also in the appendices. This work attempts to bridge the gap between mathematics and finance by using diagrams, graphs and simulations in addition to rigorous theoretical exposition. Simulations are not only used as the computational method in quantitative finance, but they can also facilitate an intuitive and deeper understanding of theoretical concepts. Stochastic Analysis for Finance with Simulations is designed for readers who want to have a deeper understanding of the delicate theory of quantitative finance by doing computer simulations in addition to theoretical study. It will particularly appeal to advanced undergraduate and graduate students in mathematics and business, but not excluding practitioners in finance industry.

ISBN: 9783319255897

Standard No.: 10.1007/978-3-319-25589-7doiSubjects--Topical Terms:

560202
Stochastic analysis.

LC Class. No.: QA274.2

Dewey Class. No.: 519.22

Stochastic analysis for finance with simulations
LDR:03447nam a2200325 a 4500 001 865895
003 DE-He213
005 20160714140346.0
006 m d
007 cr nn 008maaau
008 170720s2016 gw s 0 eng d
020 $a 9783319255897 $q (electronic bk.)
020 $a 9783319255873 $q (paper)
024 7 $a 10.1007/978-3-319-25589-7 $2 doi
035 $a 978-3-319-25589-7
040 $a GP $c GP
041 0 $a eng
050 4 $a QA274.2
072 7 $a PB $2 bicssc
072 7 $a MAT000000 $2 bisacsh
082 0 4 $a 519.22 $2 23
090 $a QA274.2 $b .C545 2016
100 1 $a Choe, Geon Ho. $3 672479
245 1 0 $a Stochastic analysis for finance with simulations $h [electronic resource] / $c by Geon Ho Choe.
260 $a Cham : $c 2016. $b Springer International Publishing : $b Imprint: Springer,
300 $a xxxii, 657 p. : $b ill., digital ; $c 24 cm.
490 1 $a Universitext, $x 0172-5939
505 0 $a Preface -- Acknowledgements -- List of Figures -- List of Tables -- List of Simulations -- Fundamental Concepts -- Financial Derivatives -- The Lebesgue Integral -- Basic Probability Theory -- Conditional Expectation -- Stochastic Processes -- Brownian Motion -- Girsanov's Theorem -- The Reflection Principle of Brownian Motion -- The Ito Integral -- The Ito Formula -- Stochastic Differential Equations -- The Feynmann-Kac Theorem -- The Binomial Tree Method for Option Pricing -- The Black-Scholes-Merton Differential Equation -- The Martingale Method -- Pricing of Vanilla Options -- Pricing of Exotic Options -- American Options -- The Capital Asset Pricing Model -- Dynamic Programming -- Bond Pricing -- Interest Rate Models -- Numeraires -- Numerical Estimation of Volatility -- Time Series -- Random Numbers -- The Monte Carlo Method for Option Pricing -- Numerical Solution of the Black-Scholes-Merton Equation -- Numerical Solution of Stochastic Differential Equations. Appendices -- Solutions for Selected Problems -- Glossary -- References -- Index.
520 $a This book is an introduction to stochastic analysis and quantitative finance; it includes both theoretical and computational methods. Topics covered are stochastic calculus, option pricing, optimal portfolio investment, and interest rate models. Also included are simulations of stochastic phenomena, numerical solutions of the Black-Scholes-Merton equation, Monte Carlo methods, and time series. Basic measure theory is used as a tool to describe probabilistic phenomena. The level of familiarity with computer programming is kept to a minimum. To make the book accessible to a wider audience, some background mathematical facts are included in the first part of the book and also in the appendices. This work attempts to bridge the gap between mathematics and finance by using diagrams, graphs and simulations in addition to rigorous theoretical exposition. Simulations are not only used as the computational method in quantitative finance, but they can also facilitate an intuitive and deeper understanding of theoretical concepts. Stochastic Analysis for Finance with Simulations is designed for readers who want to have a deeper understanding of the delicate theory of quantitative finance by doing computer simulations in addition to theoretical study. It will particularly appeal to advanced undergraduate and graduate students in mathematics and business, but not excluding practitioners in finance industry.
650 0 $a Stochastic analysis. $3 560202
650 0 $a Business mathematics. $3 557696
650 1 4 $a Mathematics. $3 527692
650 2 4 $a Mathematics, general. $3 669694
650 2 4 $a Quantitative Finance. $3 669372
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer eBooks
830 0 $a Universitext. $3 881573
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-25589-7
950 $a Mathematics and Statistics (Springer-11649)