{"product_id":"financial-derivative-and-energy-market-valuation-isbn-9781118487716","title":"Financial Derivative and Energy Market Valuation","description":"\u003cp\u003e\u003cb\u003eA road map for implementing\u003c\/b\u003e \u003cb\u003equantitative financial models\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eFinancial Derivative and Energy Market Valuation\u003c\/i\u003e 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®.\u003c\/p\u003e \u003cp\u003eFeaturing 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, \u003ci\u003eFinancial Derivative and Energy Market Valuation\u003c\/i\u003e also:\u003cbr\u003e \u003cbr\u003e • Provides the derivation, numerical implementation, and documentation of the corresponding Matlab for each topic\u003cbr\u003e \u003cbr\u003e • Extends seminal works developed over the last four decades to derive and utilize present-day financial models\u003cbr\u003e \u003cbr\u003e • Shows how to use applied methods such as fast Fourier transforms to generate statistical distributions for option pricing\u003cbr\u003e \u003cbr\u003e • Includes all Matlab code for readers wishing to replicate the figures found throughout the book\u003c\/p\u003e \u003cp\u003eThorough, practical, and easy to use, \u003ci\u003eFinancial Derivative and Energy Market Valuation\u003c\/i\u003e 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.\u003c\/p\u003e \u003cp\u003ePreface vii\u003c\/p\u003e \u003cp\u003e1 Financial Models 1\u003c\/p\u003e \u003cp\u003e2 Jump Models 35\u003c\/p\u003e \u003cp\u003e3 Options 65\u003c\/p\u003e \u003cp\u003e4 Binomial Trees 105\u003c\/p\u003e \u003cp\u003e5 Trinomial Trees 131\u003c\/p\u003e \u003cp\u003e6 Finite Difference Methods 167\u003c\/p\u003e \u003cp\u003e7 Kalman Filter 231\u003c\/p\u003e \u003cp\u003e8 Futures and Forwards 245\u003c\/p\u003e \u003cp\u003e9 Nonlinear and Non-Gaussian Kalman Filter 295\u003c\/p\u003e \u003cp\u003e10 Short-Term Deviation\/Long-Term Equilibrium Model 349\u003c\/p\u003e \u003cp\u003e11 Futures and Forwards Options 359\u003c\/p\u003e \u003cp\u003e12 Fourier Transform 397\u003c\/p\u003e \u003cp\u003e13 Fundamentals of Characteristic Functions 459\u003c\/p\u003e \u003cp\u003e14 Application of Characteristic Functions 467\u003c\/p\u003e \u003cp\u003e15 Levy Processes 505\u003c\/p\u003e \u003cp\u003e16 Fourier-Based Option Analysis 547\u003c\/p\u003e \u003cp\u003e17 Fundamentals of Stochastic Finance 585\u003c\/p\u003e \u003cp\u003e18 Affine Jump-Diffusion Processes 605\u003c\/p\u003e \u003cp\u003eIndex 645\u003c\/p\u003e  \u003cp\u003e“The book is also ideal for graduate-level courses in quantitative finance, mathematical finance, and financial engineering.”  (\u003ci\u003eZentralblatt  MATH\u003c\/i\u003e, 1 August 2013)\u003c\/p\u003e \u003cp\u003e\u003cb\u003eMICHAEL MASTRO, PhD, \u003c\/b\u003eis 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.\u003c\/p\u003e    \u003cp\u003e\u003cb\u003eA road map for implementing quantitative financial models\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003ci\u003eFinancial Derivative and Energy Market Valuation\u003c\/i\u003e 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®.\u003c\/p\u003e \u003cp\u003eFeaturing 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, \u003ci\u003eFinancial Derivative and Energy Market Valuation\u003c\/i\u003e also:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eProvides the derivation, numerical implementation, and documentation of the corresponding Matlab for each topic\u003c\/li\u003e \u003cli\u003eExtends seminal works developed over the last four decades to derive and utilize present-day financial models\u003c\/li\u003e \u003cli\u003eShows how to use applied methods such as fast Fourier transforms to generate statistical distributions for option pricing\u003c\/li\u003e \u003cli\u003eIncludes all Matlab® code for readers wishing to replicate the figures found throughout the book\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eThorough, practical, and easy to use, \u003ci\u003eFinancial Derivative and Energy Market Valuation\u003c\/i\u003e 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.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47989209465061,"sku":"NP9781118487716","price":161.95,"currency_code":"USD","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/1842\/7735\/files\/9781118487716.jpg?v=1761783218","url":"https:\/\/k12savings.com\/products\/financial-derivative-and-energy-market-valuation-isbn-9781118487716","provider":"K12savings","version":"1.0","type":"link"}