Stochastic Analysis for Finance with Simulations

ISBN-13: 9783319255873 / Angielski / Miękka / 2016 / 657 str.

Geon Ho Choe

Opis

Introducing stochastic analysis and quantitative finance, this book covers theoretical and computational methods. The main topics are stochastic calculus, option pricing, optimal portfolio investment and interest rate models, with many others, aiming to bridge the gap between mathematics and finance by using diagrams, graphs and simulations.

Recenzje

"This book gives an introduction to financial mathematics. It presents also some background of mathematical facts necessary for understanding modern finance. ... For the reader convenience, the book contains a detailed contents, a list of figures, a list of tables, a list of simulations, a list of acronyms and a list of used symbols." (Jacek Jakubowski, zbMATH 1409.91002, 2019)

"This excellent textbook is addressed to undergraduate and graduate students in mathematics and finance who want to study the main tools of stochastic calculus and its application to quantitative finance. Also, it can be used as a reference book for practitioners and professionals from the financial industry who want a better understanding of the theoretical aspects of stochastic calculus, and how it can be used in the pricing of financial derivatives." (Carlos Vázquez Cendón, Mathematical Reviews, August, 2017)

O autorze

The author's main interests are simulations of random phenomena in the areas of quantitative finance, random number generators, dynamical systems theory, and information theory. He has published a book titled "Computational Ergodic Theory".  

Blurb

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.