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Numerical methods in finance and economics : a MATLAB-based introduction 2nd ed

Numerical methods in finance and economics : a MATLAB-based introduction 2nd ed (41회 대출)

자료유형
단행본
개인저자
Brandimarte, Paolo. Brandimarte, Paolo
서명 / 저자사항
Numerical methods in finance and economics : a MATLAB-based introduction / Paolo Brandimarte.
판사항
2nd ed.
발행사항
Hoboken, N.J. :   Wiley-Interscience ,   c2006.  
형태사항
xxiv, 669 p. : ill. ; 25 cm.
총서사항
Statistics in practice
ISBN
0471745030 (hbk.) 9780471745037 (hbk.)
일반주기
Rev. ed. of: Numerical methods in finance. 2002.  
서지주기
Includes bibliographical references and index.
일반주제명
Finance -- Statistical methods. Economics -- Statistical methods.
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245 1 0 ▼a Numerical methods in finance and economics : ▼b a MATLAB-based introduction / ▼c Paolo Brandimarte.
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300 ▼a xxiv, 669 p. : ▼b ill. ; ▼c 25 cm.
490 1 ▼a Statistics in practice
500 ▼a Rev. ed. of: Numerical methods in finance. 2002.
504 ▼a Includes bibliographical references and index.
650 0 ▼a Finance ▼x Statistical methods.
650 0 ▼a Economics ▼x Statistical methods.
700 1 ▼a Brandimarte, Paolo ▼t Numerical methods in finance.

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컨텐츠정보

책소개

A state-of-the-art introduction to the powerful mathematical and statistical tools used in the field of finance

The use of mathematical models and numerical techniques is a practice employed by a growing number of applied mathematicians working on applications in finance. Reflecting this development, Numerical Methods in Finance and Economics: A MATLAB®-Based Introduction, Second Edition bridges the gap between financial theory and computational practice while showing readers how to utilize MATLAB®—the powerful numerical computing environment—for financial applications.

The author provides an essential foundation in finance and numerical analysis in addition to background material for students from both engineering and economics perspectives. A wide range of topics is covered, including standard numerical analysis methods, Monte Carlo methods to simulate systems affected by significant uncertainty, and optimization methods to find an optimal set of decisions.

Among this book's most outstanding features is the integration of MATLAB®, which helps students and practitioners solve relevant problems in finance, such as portfolio management and derivatives pricing. This tutorial is useful in connecting theory with practice in the application of classical numerical methods and advanced methods, while illustrating underlying algorithmic concepts in concrete terms.

Newly featured in the Second Edition:

  • In-depth treatment of Monte Carlo methods with due attention paid to variance reduction strategies
  • New appendix on AMPLⓒ in order to better illustrate the optimization models in Chapters 11 and 12
  • New chapter on binomial and trinomial lattices
  • Additional treatment of partial differential equations with two space dimensions
  • Expanded treatment within the chapter on financial theory to provide a more thorough background for engineers not familiar with finance
  • New coverage of advanced optimization methods and applications later in the text

Numerical Methods in Finance and Economics: A MATLAB®-Based Introduction, Second Edition presents basic treatments and more specialized literature, and it also uses algebraic languages, such as AMPLⓒ, to connect the pencil-and-paper statement of an optimization model with its solution by a software library. Offering computational practice in both financial engineering and economics fields, this book equips practitioners with the necessary techniques to measure and manage risk.


정보제공 : Aladin

목차

Preface to the Second Edition.

From the Preface to the First Edition.

PART I. BACKGROUND.

1. Motivation.

2. Financial Theory.

PART II. NUMERICAL METHODS.

3. Basics of Numerical Analysis.

4. Numerical Integration: Deterministic and Monte Carlo Methods.

5. Finite Difference Methods for Partial Differential Equations.

6. Convex Optimization.

PART III. PRICING EQUITY OPTIONS.

7. Option Pricing by Binomial and Trinomial Lattices.

8. Option Pricing by Monte Carlo Methods.

9. Option Pricing by Finite Difference Methods.

PART IV. ADVANCED OPTMIZATION MODELS AND METHODS.

10. Dynamic Programming.

11. Linear Stochastic Programming Models with Recourse.

12. Non-Convex Optimization.

PART V. APPENDICES.

Appendix A. Introduction to MATLAB Programming.

Appendix B. Refresher on Probability theory and Statistics.

Appendix C. Introduction to AMPL.

Index.


정보제공 : Aladin

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