Financial Modelling

Beschreibung

"This book offers a comprehensive overview of the main derivative pricing models used in practice across various asset classes. Many numerical examples are provided, and precious implementation details are revealed to the financial community. If the devil is in the details, this is one hell of a book!"--Fabio Mercurio, Bloomberg "This book is a dream come true, a must have, a must read and a must use. High-tech financial engineering and numerics are now becoming accessible to the broad quant community."--Wim Schoutens, Research Professor, University of Leuven "This is a book I wish I'd owned ten years ago to prepare for the exotic derivatives models hype in equity and rates of the first decade. It saves identifying, finding, screening and reading dozens of papers and treats the full life cycle of the models from theory to implementation. The reader can get quickly familiar with the pre-LSV modelling age. With any luck, the Matlab code will also run on octave."--Uwe Wystup, Professor of Quantitative Finance/ Founder & CEO, MathFinance "This book is a nice exposition for those Quants in Financial Engineering who are interested in an overview of modern pricing and calibration techniques in the field of Financial Derivatives. For those who have a strong mathematical background and are interested in implementation issues, this book is a severe choice."--Dr. Ingo Schneider, Financial Engineering, DekaBank "This handbook is a compendium of useful formulae for computational finance. This - and the fact that the authors provide full Matlab code in all cases - makes this work unique. You can test the code as well as looking at the formulae! This book brings many results in one place. It saves much time. The book will certainly be useful as a reference for practitioners, developers and MFE students. In particular, I also see it as a handbook of algorithms that quants can use as input to their favourite production languages C++, C# and Java."--Daniel J. Duffy, Founder, Datasim "In the application of mathematical finance the popularity of a model or theoretical result strongly depends on the ability to provide it with an efficient and robust implementation. Thus, a theory and modelling should naturally be combined with a discussion of its implementation. Being practitioners with a strong academic background, Kienitz and Wetterau provide this complete package in this excellent book; adding a lot of valuable insights."--Christian P. Fries, Head of Model Development, Group Risk Control, DZ BANK AG Frankfurt/Professor for Quantitative Finance, Department of Mathematics, LMU Munich
This book will enable the reader to model, design and implement a range of financial models for derivatives pricing and asset allocation. The book will provide practitioners with the complete financial modeling workflow, from model choice, deriving (semi-) analytic approximate prices and Greeks even for exotic options. Such methods can be used for calibration to market data. Furthermore, Monte Carlo simulation techniques are covered which can be applied to multi-dimensional and path dependent options or some asset allocation problems. Equity/Equity-Interest Rate Hybrid models, Interest Rate models and Asset Allocation are used as examples showing specific models with analysis of their features. The authors then go on to show how to price simple options and how to calibrate the models to real life market data and finally they discuss the pricing of exotic options. At the end of these sections the reader will be able to use the techniques discussed for equity derivatives and interest rate models in other areas of finance such as foreign exchange and inflation. The models discussed for derivatives pricing are: * Heston / Bates Model * Local/Stochastic Volatility Models (DD, CEV, DDHeston) * Lévy Models (Variance-Gamma, Normal Inverse Gaussian) * Heston -- Hull -- White Model * Libor Market Model * SABR Model * Lévy Models with Stochastic Volatility The methods which are discusses * Direct Integration methods+ * Methods based on Fourier Transform * Monte Carlo Simulation * Local and Global Optimization The models discussed for asset allocation are: * Markowitz Model * Black-Litterman Model * Copula Models * CVaR numerical optimization Source code for all the examples is provided with implementation in Matlab.

Autor*in

Joerg Kienitz

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Finance & Investments Financial Engineering Finanz- u. Anlagewesen Finanztechnik

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