Financial Modelling: Theory, Implementation and Practice with MATLAB Source
Joerg Kienitz
ISBN 10: 0470744898 ISBN 13: 9780470744895
Published by John Wiley & Sons Inc, 2012
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* The book enables the reader to model, design and implement a range of financial models for derivatives pricing and asset allocation. Series: Wiley Finance Series. Num Pages: 734 pages, Illustrations. BIC Classification: KFF. Category: (P) Professional & Vocational. Dimension: 249 x 176 x 45. Weight in Grams: 1386. . 2013. 1st Edition. Hardcover. . . . . Seller Inventory # V9780470744895
Synopsis:
Financial modelling
Theory, Implementation and Practice with MATLAB Source
Jörg Kienitz and Daniel Wetterau
Financial Modelling - Theory, Implementation and Practice with MATLAB Source is a unique combination of quantitative techniques, the application to financial problems and programming using Matlab. The book enables the reader to model, design and implement a wide range of financial models for derivatives pricing and asset allocation, providing practitioners with complete financial modelling workflow, from model choice, deriving prices and Greeks using (semi-) analytic and simulation techniques, and calibration even for exotic options.
The book is split into three parts. The first part considers financial markets in general and looks at the complex models needed to handle observed structures, reviewing models based on diffusions including stochastic-local volatility models and (pure) jump processes. It shows the possible risk-neutral densities, implied volatility surfaces, option pricing and typical paths for a variety of models including SABR, Heston, Bates, Bates-Hull-White, Displaced-Heston, or stochastic volatility versions of Variance Gamma, respectively Normal Inverse Gaussian models and finally, multi-dimensional models. The stochastic-local-volatility Libor market model with time-dependent parameters is considered and as an application how to price and risk-manage CMS spread products is demonstrated.
The second part of the book deals with numerical methods which enables the reader to use the models of the first part for pricing and risk management, covering methods based on direct integration and Fourier transforms, and detailing the implementation of the COS, CONV, Carr-Madan method or Fourier-Space-Time Stepping. This is applied to pricing of European, Bermudan and exotic options as well as the calculation of the Greeks. The Monte Carlo simulation technique is outlined and bridge sampling is discussed in a Gaussian setting and for Lévy processes. Computation of Greeks is covered using likelihood ratio methods and adjoint techniques. A chapter on state-of-the-art optimization algorithms rounds up the toolkit for applying advanced mathematical models to financial problems and the last chapter in this section of the book also serves as an introduction to model risk.
The third part is devoted to the usage of Matlab, introducing the software package by describing the basic functions applied for financial engineering. The programming is approached from an object-oriented perspective with examples to propose a framework for calibration, hedging and the adjoint method for calculating Greeks in a Libor market model.
Source code used for producing the results and analysing the models is provided on the author's dedicated website, http://www.mathworks.de/matlabcentral/fileexchange/authors/246981.
About the Author:
About the authors
JÖRG KIENITZ is the head of Quantitative Analytics at Deutsche Postbank AG. He is primarily involved in developing and implementing models for pricing complex derivatives structures and for asset allocation. He also lectures at university level on advanced financial modelling and implementation including the University of Oxford's part-time Masters of Finance course. Jörg works as an independent consultant for model development and validation as well as giving seminars for finance professionals. He is a speaker at the major financial conferences including Global Derivatives, WBS Fixed Income and RISK. Jörg is a member of the editorial board of International Review of Applied Financial Issues and Economics and holds a Ph.D. in stochastic analysis from the University of Bielefeld.
DANIEL WETTERAU is a specialist in the Quantitative Analytics team of Deutsche Postbank AG. He is responsible for the implementation of term structure models, advanced numerical methods, optimization algorithms and methods for advanced quantitative asset allocation. Further to his work he teaches finance courses for market professionals. Daniel received a Masters in financial mathematics from the University of Wuppertal and was awarded the Barmenia mathematics award for his thesis.
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Bibliographic Details
Title: Financial Modelling: Theory, Implementation ...
Publisher: John Wiley & Sons Inc
Publication Date: 2012
Binding: Hardcover
Condition: New
Edition: 1st Edition
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Financial Modelling: Theory, Implementation and Practice with Matlab Source (The Wiley Finance Series)
Seller: killarneybooks, Inagh, CLARE, Ireland
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Hardcover. Condition: Good. 1st Edition. Hardcover, xiii + 719 pages, NOT ex-library. Weight: 1.4kg. Yellow highlighting on 3 pages; pencil marks on one page; faint grubby yellow marks in margins of a few leaves (not affecting the readability of text). Else interior is clean and bright, free of inscriptions and stamps, firmly bound. Grubby yellow marks on edges of a portion of leaves externally. Edgeworn dust jacket with a tear to lower front panel. -- Contents: Introduction; I Financial Markets and Popular Models 1 Financial Markets: Data, Basics and Derivatives [Introduction and Objectives; Financial Time-Series, Statistical Properties of Market Data and Invariants; Implied Volatility Surfaces and Volatility Dynamics; Applications; General Remarks on Notation; Summary and Conclusions; Appendix: Quotes] 2 Diffusion Models [Introduction and Objectives; Local Volatility Models; Stochastic Volatility Models; Stochastic Volatility and Stochastic Rates Models; Summary and Conclusions] 3 Models with Jumps [Introduction and Objectives; Poisson Processes and Jump Diffusions; Exponential Lévy Models; Other Models; Martingale Correction; Summary and Conclusions] 4 Multi-Dimensional Models [Introduction and Objectives; Multi-Dimensional Diffusions; Multi-Dimensional Heston and SABR Models; Parameter Averaging; Markovian Projection; Copulae; Multi-Dimensional Variance Gamma Processes; Summary and Conclusions]; II Numerical Methods and Recipes 5 Option Pricing by Transform Techniques and Direct Integration [Introduction and Objectives; Fourier Transform; Carr-Madan Method; Lewis Method; Attari Method; Convolution Method; Cosine Method; Comparison, Stability and Performance; Extending the Methods to Forward Start Options; Density Recovery; Summary and Conclusions] 6 Advanced Topics Using Transform Techniques [Introduction and Objectives; Pricing Non-Standard Vanilla Options; Bermudan and American Options; Cosine Method and Barrier Options; Greeks; Summary and Conclusions] 7 Monte Carlo Simulation and Applications [Introduction and Objectives; Sampling Diffusion Processes; Special Purpose Schemes; Adding Jumps; Bridge Sampling; Libor Market Model; Multi-Dimensional Lévy Models; Copulae; Summary and Conclusions] 8 Monte Carlo Simulation: Advanced Issues [Introduction and Objectives; Monte Carlo and Early Exercise; Greeks with Monte Carlo; Euler Schemes and General Greeks; Application to Trigger Swap; Summary and Conclusions; Appendix: Trees] 9 Calibration and Optimization [Introduction and Objectives; Nelder-Mead Method; Levenberg-Marquardt Method; L-BFGS Method; SQP Method; Differential Evolution; Simulated Annealing; Summary and Conclusions] 10 Model Risk: Calibration, Pricing and Hedging [Introduction and Objectives; Calibration; Pricing Exotic Options; Hedging; Summary and Conclusions]; III Implementation, Software Design and Mathematics 11 Matlab: Basics [Introduction and Objectives; General Remarks; Matrices, Vectors and Cell Arrays; Functions and Function Handles; Toolboxes; Useful Functions and Methods; Plotting; Summary and Conclusions] 12 Matlab: Object Oriented Development [Introduction and Objectives; Matlab OO Model; A Model Class Hierarchy; A Pricer Class Hierarchy; An Optimizer Class Hierarchy; Design Patterns; Example: Calibration Engine; Example: The Libor Market Model and Greeks; Summary and Conclusions] 13 Math Fundamentals [Introduction and Objectives; Probability Theory and Stochastic Processes; Numerical Methods for Stochastic Processes; Basics on Complex Analysis; Characteristic Function and Fourier Transform; Summary and Conclusions]; List of Figures; List of Tables; Bibliography; Index. Seller Inventory # 006486
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Financial Modelling (Hardcover)
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ISBN 10: 0470744898
ISBN 13: 9780470744895
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Hardcover. Condition: new. Hardcover. Financial modelling Theory, Implementation and Practice with MATLAB Source Joerg Kienitz and Daniel Wetterau Financial Modelling - Theory, Implementation and Practice with MATLAB Source is a unique combination of quantitative techniques, the application to financial problems and programming using Matlab. The book enables the reader to model, design and implement a wide range of financial models for derivatives pricing and asset allocation, providing practitioners with complete financial modelling workflow, from model choice, deriving prices and Greeks using (semi-) analytic and simulation techniques, and calibration even for exotic options. The book is split into three parts. The first part considers financial markets in general and looks at the complex models needed to handle observed structures, reviewing models based on diffusions including stochastic-local volatility models and (pure) jump processes. It shows the possible risk-neutral densities, implied volatility surfaces, option pricing and typical paths for a variety of models including SABR, Heston, Bates, Bates-Hull-White, Displaced-Heston, or stochastic volatility versions of Variance Gamma, respectively Normal Inverse Gaussian models and finally, multi-dimensional models. The stochastic-local-volatility Libor market model with time-dependent parameters is considered and as an application how to price and risk-manage CMS spread products is demonstrated. The second part of the book deals with numerical methods which enables the reader to use the models of the first part for pricing and risk management, covering methods based on direct integration and Fourier transforms, and detailing the implementation of the COS, CONV, Carr-Madan method or Fourier-Space-Time Stepping. This is applied to pricing of European, Bermudan and exotic options as well as the calculation of the Greeks. The Monte Carlo simulation technique is outlined and bridge sampling is discussed in a Gaussian setting and for Levy processes. Computation of Greeks is covered using likelihood ratio methods and adjoint techniques. A chapter on state-of-the-art optimization algorithms rounds up the toolkit for applying advanced mathematical models to financial problems and the last chapter in this section of the book also serves as an introduction to model risk. The third part is devoted to the usage of Matlab, introducing the software package by describing the basic functions applied for financial engineering. The programming is approached from an object-oriented perspective with examples to propose a framework for calibration, hedging and the adjoint method for calculating Greeks in a Libor market model. Source code used for producing the results and analysing the models is provided on the author's dedicated website, * The book enables the reader to model, design and implement a range of financial models for derivatives pricing and asset allocation. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9780470744895
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Financial Modelling (Hardcover)
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John Wiley & Sons Inc, New York, 2012
ISBN 10: 0470744898
ISBN 13: 9780470744895
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Hardcover. Condition: new. Hardcover. Financial modelling Theory, Implementation and Practice with MATLAB Source Joerg Kienitz and Daniel Wetterau Financial Modelling - Theory, Implementation and Practice with MATLAB Source is a unique combination of quantitative techniques, the application to financial problems and programming using Matlab. The book enables the reader to model, design and implement a wide range of financial models for derivatives pricing and asset allocation, providing practitioners with complete financial modelling workflow, from model choice, deriving prices and Greeks using (semi-) analytic and simulation techniques, and calibration even for exotic options. The book is split into three parts. The first part considers financial markets in general and looks at the complex models needed to handle observed structures, reviewing models based on diffusions including stochastic-local volatility models and (pure) jump processes. It shows the possible risk-neutral densities, implied volatility surfaces, option pricing and typical paths for a variety of models including SABR, Heston, Bates, Bates-Hull-White, Displaced-Heston, or stochastic volatility versions of Variance Gamma, respectively Normal Inverse Gaussian models and finally, multi-dimensional models. The stochastic-local-volatility Libor market model with time-dependent parameters is considered and as an application how to price and risk-manage CMS spread products is demonstrated. The second part of the book deals with numerical methods which enables the reader to use the models of the first part for pricing and risk management, covering methods based on direct integration and Fourier transforms, and detailing the implementation of the COS, CONV, Carr-Madan method or Fourier-Space-Time Stepping. This is applied to pricing of European, Bermudan and exotic options as well as the calculation of the Greeks. The Monte Carlo simulation technique is outlined and bridge sampling is discussed in a Gaussian setting and for Levy processes. Computation of Greeks is covered using likelihood ratio methods and adjoint techniques. A chapter on state-of-the-art optimization algorithms rounds up the toolkit for applying advanced mathematical models to financial problems and the last chapter in this section of the book also serves as an introduction to model risk. The third part is devoted to the usage of Matlab, introducing the software package by describing the basic functions applied for financial engineering. The programming is approached from an object-oriented perspective with examples to propose a framework for calibration, hedging and the adjoint method for calculating Greeks in a Libor market model. Source code used for producing the results and analysing the models is provided on the author's dedicated website, * The book enables the reader to model, design and implement a range of financial models for derivatives pricing and asset allocation. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9780470744895
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Financial Modelling (Hardcover)
Published by
John Wiley & Sons Inc, New York, 2012
ISBN 10: 0470744898
ISBN 13: 9780470744895
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Hardcover
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Hardcover. Condition: new. Hardcover. Financial modelling Theory, Implementation and Practice with MATLAB Source Joerg Kienitz and Daniel Wetterau Financial Modelling - Theory, Implementation and Practice with MATLAB Source is a unique combination of quantitative techniques, the application to financial problems and programming using Matlab. The book enables the reader to model, design and implement a wide range of financial models for derivatives pricing and asset allocation, providing practitioners with complete financial modelling workflow, from model choice, deriving prices and Greeks using (semi-) analytic and simulation techniques, and calibration even for exotic options. The book is split into three parts. The first part considers financial markets in general and looks at the complex models needed to handle observed structures, reviewing models based on diffusions including stochastic-local volatility models and (pure) jump processes. It shows the possible risk-neutral densities, implied volatility surfaces, option pricing and typical paths for a variety of models including SABR, Heston, Bates, Bates-Hull-White, Displaced-Heston, or stochastic volatility versions of Variance Gamma, respectively Normal Inverse Gaussian models and finally, multi-dimensional models. The stochastic-local-volatility Libor market model with time-dependent parameters is considered and as an application how to price and risk-manage CMS spread products is demonstrated. The second part of the book deals with numerical methods which enables the reader to use the models of the first part for pricing and risk management, covering methods based on direct integration and Fourier transforms, and detailing the implementation of the COS, CONV, Carr-Madan method or Fourier-Space-Time Stepping. This is applied to pricing of European, Bermudan and exotic options as well as the calculation of the Greeks. The Monte Carlo simulation technique is outlined and bridge sampling is discussed in a Gaussian setting and for Levy processes. Computation of Greeks is covered using likelihood ratio methods and adjoint techniques. A chapter on state-of-the-art optimization algorithms rounds up the toolkit for applying advanced mathematical models to financial problems and the last chapter in this section of the book also serves as an introduction to model risk. The third part is devoted to the usage of Matlab, introducing the software package by describing the basic functions applied for financial engineering. The programming is approached from an object-oriented perspective with examples to propose a framework for calibration, hedging and the adjoint method for calculating Greeks in a Libor market model. Source code used for producing the results and analysing the models is provided on the author's dedicated website, * The book enables the reader to model, design and implement a range of financial models for derivatives pricing and asset allocation. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780470744895