Erschienen: 21.09.2012 Abbildung von Kienitz / Wetterau | Financial Modelling | 2012 | Theory, Implementation and Pra...

Kienitz / Wetterau

Financial Modelling

Theory, Implementation and Practice with MATLAB Source

2012. Buch. 734 S. Hardcover

wiley. ISBN 978-0-470-74489-5

Format (B x L): 17,6 x 24,9 cm

Gewicht: 1376 g

In englischer Sprache

Das Werk ist Teil der Reihe: Wiley Finance Series


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.


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