John Wiley & Sons Quantitative Finance Cover Presents a multitude of topics relevant to the quantitative finance community by combining the best .. Product #: 978-1-118-62995-6 Regular price: $116.82 $116.82 In Stock

Quantitative Finance

Mariani, Maria C. / Florescu, Ionut

Statistics in Practice

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1. Edition January 2020
496 Pages, Hardcover
Wiley & Sons Ltd

ISBN: 978-1-118-62995-6
John Wiley & Sons

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Presents a multitude of topics relevant to the quantitative finance community by combining the best of the theory with the usefulness of applications

Written by accomplished teachers and researchers in the field, this book presents quantitative finance theory through applications to specific practical problems and comes with accompanying coding techniques in R and MATLAB, and some generic pseudo-algorithms to modern finance. It also offers over 300 examples and exercises that are appropriate for the beginning student as well as the practitioner in the field.

The Quantitative Finance book is divided into four parts. Part One begins by providing readers with the theoretical backdrop needed from probability and stochastic processes. We also present some useful finance concepts used throughout the book. In part two of the book we present the classical Black-Scholes-Merton model in a uniquely accessible and understandable way. Implied volatility as well as local volatility surfaces are also discussed. Next, solutions to Partial Differential Equations (PDE), wavelets and Fourier transforms are presented. Several methodologies for pricing options namely, tree methods, finite difference method and Monte Carlo simulation methods are also discussed. We conclude this part with a discussion on stochastic differential equations (SDE's). In the third part of this book, several new and advanced models from current literature such as general Lvy processes, nonlinear PDE's for stochastic volatility models in a transaction fee market, PDE's in a jump-diffusion with stochastic volatility models and factor and copulas models are discussed. In part four of the book, we conclude with a solid presentation of the typical topics in fixed income securities and derivatives. We discuss models for pricing bonds market, marketable securities, credit default swaps (CDS) and securitizations.
* Classroom-tested over a three-year period with the input of students and experienced practitioners
* Emphasizes the volatility of financial analyses and interpretations
* Weaves theory with application throughout the book
* Utilizes R and MATLAB software programs
* Presents pseudo-algorithms for readers who do not have access to any particular programming system
* Supplemented with extensive author-maintained web site that includes helpful teaching hints, data sets, software programs, and additional content

Quantitative Finance is an ideal textbook for upper-undergraduate and beginning graduate students in statistics, financial engineering, quantitative finance, and mathematical finance programs. It will also appeal to practitioners in the same fields.

List of Figures xv

List of Tables xvii

Part I Stochastic Processes and Finance 1

1 Stochastic Processes 3

2 Basics of Finance 33

Part II Quantitative Finance in Practice 47

3 Some Models Used in Quantitative Finance 49

4 Solving Partial Differential Equations 83

5 Wavelets and Fourier Transforms 101

6 Tree Methods 121

7 Approximating PDEs 177

8 Approximating Stochastic Processes 203

9 Stochastic Differential Equations 245

Part III Advanced Models for Underlying Assets 287

10 Stochastic Volatility Models 289

12 General Lévy Processes 325

13 Generalized Lévy Processes, Long Range Correlations, and Memory Effects 337

14 Approximating General Derivative Prices 365

15 Solutions to Complex Models Arising in the Pricing of Financial Options 389

16 Factor and Copulas Models 403

Part IV Fixed Income Securities and Derivatives 413

17 Models for the Bond Market 415

18 Exchange Traded Funds (ETFs), Credit Default Swap (CDS), and Securitization 431

Bibliography 445

Index 000
MARIA C. MARIANI, PHD, is Shigeko K. Chan Distinguished Professor and Chair in the Department of Mathematical Sciences at The University of Texas at El Paso. She currently focuses her research on mathematical finance, stochastic and non-linear differential equations, geophysics, and numerical methods. Dr. Mariani is co-organizer of the Conference on Modeling High-Frequency Data in Finance.

IONUT FLORESCU, PHD, is Research Professor in Financial Engineering at Stevens Institute of Technology. He serves as Director of the Hanlon Laboratories as well as Director of the Financial Analytics program. His main research is in probability and stochastic processes and applications to domains such as finance, computer vision, robotics, earthquake studies, weather studies, and many more. Dr. Florescu is lead organizer of the Conference on Modeling High-Frequency Data in Finance.

M. C. Mariani, University of Texas at El Paso; I. Florescu, Stevens Institute of Technology