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Financial Derivative and Energy Market Valuation: Theory and Implementation in Matlab

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Synopses & Reviews

Publisher Comments:

A road map for implementing quantitative financial models

Financial Derivative and Energy Market Valuation brings the application of financial models to a higher level by helping readers capture the true behavior of energy markets and related financial derivatives. The book provides readers with a range of statistical and quantitative techniques and demonstrates how to implement the presented concepts and methods in Matlab®.

Featuring an unparalleled level of detail, this unique work provides the underlying theory and various advanced topics without requiring a prior high-level understanding of mathematics or finance. In addition to a self-contained treatment of applied topics such as modern Fourier-based analysis and affine transforms, Financial Derivative and Energy Market Valuation also:

• Provides the derivation, numerical implementation, and documentation of the corresponding Matlab for each topic

• Extends seminal works developed over the last four decades to derive and utilize present-day financial models

• Shows how to use applied methods such as fast Fourier transforms to generate statistical distributions for option pricing

• Includes all Matlab code for readers wishing to replicate the figures found throughout the book

Thorough, practical, and easy to use, Financial Derivative and Energy Market Valuation is a first-rate guide for readers who want to learn how to use advanced numerical methods to implement and apply state-of-the-art financial models. The book is also ideal for graduate-level courses in quantitative finance, mathematical finance, and financial engineering.

Synopsis:

A road map for implementing quantitative financial models

Financial Derivative and Energy Market Valuation brings the application of financial models to a higher level by helping readers capture the true behavior of energy markets and related financial derivatives. The book provides readers with a range of statistical and quantitative techniques and demonstrates how to implement the presented concepts and methods in Matlab®.

Featuring an unparalleled level of detail, this unique work provides the underlying theory and various advanced topics without requiring a prior high-level understanding of mathematics or finance. In addition to a self-contained treatment of applied topics such as modern Fourier-based analysis and affine transforms, Financial Derivative and Energy Market Valuation also:

  • Provides the derivation, numerical implementation, and documentation of the corresponding Matlab for each topic
  • Extends seminal works developed over the last four decades to derive and utilize present-day financial models
  • Shows how to use applied methods such as fast Fourier transforms to generate statistical distributions for option pricing
  • Includes all Matlab® code for readers wishing to replicate the figures found throughout the book

Thorough, practical, and easy to use, Financial Derivative and Energy Market Valuation is a first-rate guide for readers who want to learn how to use advanced numerical methods to implement and apply state-of-the-art financial models. The book is also ideal for graduate-level courses in quantitative finance, mathematical finance, and financial engineering.

Synopsis:

With an introduction to the needed mathematical financial theory, this book presents statistical and quantitative methods to implement and apply state-of-the-art financial models. It details the necessary steps for implementation of the models in MATLAB and provides the code; discusses the affine transform formalism; focuses on developing and utilizing the Kalman filter; and exploits the extended, Gauss-Hermite, unscented, Monte Carlo, and particle Kalman filters for nonlinear and non-Gaussian models.

About the Author

MICHAEL MASTRO, PhD, is a civilian Staff Scientist at the U.S. Naval Research Lab. Dr. Mastro has authored more than 150 papers and patents and has organized several conference symposia.

Table of Contents

Preface vii

1 Financial Models 1

2 Jump Models 35

3 Options 65

4 Binomial Trees 105

5 Trinomial Trees 131

6 Finite Difference Methods 167

7 Kalman Filter 231

8 Futures and Forwards 245

9 Nonlinear and Non-Gaussian Kalman Filter 295

10 Short-Term Deviation/Long-Term Equilibrium Model 349

11 Futures and Forwards Options 359

12 Fourier Transform 397

13 Fundamentals of Characteristic Functions 459

14 Application of Characteristic Functions 467

15 Levy Processes 505

16 Fourier-Based Option Analysis 547

17 Fundamentals of Stochastic Finance 585

18 Affine Jump-Diffusion Processes 605

Index 645

Product Details

ISBN:
9781118487716
Author:
Mastro, Michael A.
Publisher:
John Wiley & Sons
Author:
Mastro, M.
Author:
Michael Mastro, PhD
Author:
Mastro, Michael
Subject:
Statistics
Subject:
Statistics for Finance, Business & Economics
Subject:
qualitative finance, derivative valuation, financial derivative valuation, statistics, financial engineering, applied mathematics
Subject:
Mathematics | Probability and Statistics
Subject:
BUSINESS & ECONOMICS/Business Mathematics
Subject:
Business & Economics-Econometrics
Subject:
qualitative finance, derivative valuation, financial derivative valuation,
Subject:
statistics, financial engineering, applied mathematics
Copyright:
Edition Description:
WOL online Book (not BRO)
Publication Date:
20130326
Binding:
HARDCOVER
Language:
English
Pages:
664
Dimensions:
235 x 163 x 37.8 mm 35.84 oz

Related Subjects

Business » Investing
Business » Personal Finance
Science and Mathematics » Mathematics » Applied
Science and Mathematics » Mathematics » Probability and Statistics » General
Science and Mathematics » Mathematics » Probability and Statistics » Statistics
Textbooks » General

Financial Derivative and Energy Market Valuation: Theory and Implementation in Matlab New Hardcover
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$145.50 In Stock
Product details 664 pages John Wiley & Sons - English 9781118487716 Reviews:
"Synopsis" by , A road map for implementing quantitative financial models

Financial Derivative and Energy Market Valuation brings the application of financial models to a higher level by helping readers capture the true behavior of energy markets and related financial derivatives. The book provides readers with a range of statistical and quantitative techniques and demonstrates how to implement the presented concepts and methods in Matlab®.

Featuring an unparalleled level of detail, this unique work provides the underlying theory and various advanced topics without requiring a prior high-level understanding of mathematics or finance. In addition to a self-contained treatment of applied topics such as modern Fourier-based analysis and affine transforms, Financial Derivative and Energy Market Valuation also:

  • Provides the derivation, numerical implementation, and documentation of the corresponding Matlab for each topic
  • Extends seminal works developed over the last four decades to derive and utilize present-day financial models
  • Shows how to use applied methods such as fast Fourier transforms to generate statistical distributions for option pricing
  • Includes all Matlab® code for readers wishing to replicate the figures found throughout the book

Thorough, practical, and easy to use, Financial Derivative and Energy Market Valuation is a first-rate guide for readers who want to learn how to use advanced numerical methods to implement and apply state-of-the-art financial models. The book is also ideal for graduate-level courses in quantitative finance, mathematical finance, and financial engineering.

"Synopsis" by , With an introduction to the needed mathematical financial theory, this book presents statistical and quantitative methods to implement and apply state-of-the-art financial models. It details the necessary steps for implementation of the models in MATLAB and provides the code; discusses the affine transform formalism; focuses on developing and utilizing the Kalman filter; and exploits the extended, Gauss-Hermite, unscented, Monte Carlo, and particle Kalman filters for nonlinear and non-Gaussian models.
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