Derivatives and Internal Models

The successful first edition provided an introduction to the valuation and risk management of modern financial instruments, formulated in a precise mathematical expression and comprehensively covering all relevant topics using consistent and exact notation. In this edition, Deutsch continues with this philosophy covering new and more advanced topics including risk adjusted performance and portfolio optimization. This edition also includes a CD-ROM in the form of Excel workbooks giving detailed models of the concepts discussed in the book.

Review of previous edition:

'Whether you are looking for a standard reference or a stand-alone learning guide, Derivatives and Internal Models deserves a place on your bookshelf.' - Risk

Autorentext
HANS-PETER DEUTSCH is Managing Director of d-fine, a major consultancy firm.

Inhalt
PART I: FUNDAMENTALS Introduction Legal Framework Fundamental Risk Factors of Financial Markets Financial Instruments - A System of Derivatives and Underlyings PART II: METHODS Overview of the Assumptions for Different Valuation Methods Present Value Methods, Yields and Traditional Risk Measures Arbitrage The Black-Scholes Differential Equation Integral Forms and Analytic Solutions in the Black-Scholes World Numerical Solutions of Differential Equations using Finite Differences Binomial and Trinomial Trees Monte-Carlo Simulations Hedging Martingale and Numeraire Interest Rates and Term Structure Models PART III: INSTRUMENTS Spot Transactions on Interest Instruments Forward Transactions on Interest Rates Plain Vanilla Options Exotic Options Structured Products and Stripping PART IV: RISK Fundamentals The Variance-Covariance Method Simulation Methods Interest Rate Risk and Cash Flows Example VaR-Computation Backtesting: Checking the Applied Methods Risk Adjusted Return and Portfolio Theory PART V: MARKET DATA Interest Rate Term Structures Volatility Market Parameter from Historical Time Series Time Series Modelling Forecasting with Time Series Models Principle Component Analysis Pre-Treatment of Time Series and Assesment of Models Probabiltiy and Statistics