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Preface
Introduction
Part I - A rapidly evolving financial world
The evolution of financial markets
Definitions
History
The foreign exchange market
The Eurodollar market
Innovations on the international capital markets
The volatility of financial markets
Definition
Case study
The link between volatility and Value at Risk (VaR)
Banks, insurance companies and other corporate companies in the dawn of the new millennium
The need for risk management
Definitions
A new risk-return world
The risk management discipline and its value-added
The views of the regulators
The Capital Adequacy Directive
The Basel Committee
The Group of Thirty
The role of the new European Central Bank
Part II - Asset estimation
Equity portfolio management
Theoretical foundation
Return and risk
Market efficiency
Asset valuation
Diversification and portfolio management
Principles of diversification
Diversification and portfolio size
The Markowitz model and the critical line algorithm
The Sharpe model
Model with a risk free asset
Utility theory and optimal portfolio selection
Elton, Gruber and Padberg methodology
The market model
Capital asset pricing model
Bond portfolio management
Special features and valuation methods
Bonds and their financial risk
Duration
Convexity and sensitivity
Structure of the yield curve
Strategies for fixed-income portfolio management
Passive strategies and immunisation
Active strategies
Option strategies
Definitions
The value of an option
Intrinsic and time value
Volatility
Sensitivity parameters (the "Greeks")
Assessment models
Binomial model
Black and Scholes model
Derived models
Call-put parity
Option strategies
Simple strategies
Complex strategies
Part III VaR: theory and practice
The theoretical notion of VaR
The notion of risk
Drawbacks of traditional measurement of financial risks
Generalising the notion of risk
VaR of a single asset
Value at Risk
The case of a normal distribution
Asset valuation models
Linear models
Non linear models
VaR of a portfolio
VaR estimation techniques
Recurring probelms with VaR estimation
Variance-covariance method
Decomposition of financial assets
Cash flow mapping
Computing VaR
Monte Carlo simulation
Monte Carlo and probability theory
Computing VaR
Historical simulation
Some new developments
Contribution of extreme value theory
Simulation and stress testing
Comparision of advantages and drawbacks
Theoretical point of view
Practical point of view
Synthesis
Setting up a VaR methodology
Assumptions and definition of input parameters
Database set-up and maintenance
VaR computation
Reporting and interpretation of results
Part IV From risk management to asset management
Global portfolio
Asset allocation
Risk and expected performance of the portfolio
Risk scoring questionnaire and management mandate
Option risks
Short calls
Short puts
Leverage effect
Optimisation of a global portfolio through VaR
VaR on a global portfolio
Choice of a methodology
Defining assumptions and parameters
Defining time horizons and confidence level
Portfolio mix
Combinatorial analysis
Defining steps and constraints
Expected return computation
VaR computation
Standard deviation computation
Elton, Gruber and Padberg optimistion
Comparision and conclusions
Portfolio mix
Combinatorial analysis
Defining steps and constraints
Expected return computation
VaR computation
Standard deviation computation
Elton, Gruber and Padberg optimisation
Institutional management: VaR applied to mutual or investment funds
Basics
The autocorrelation
Net asset value vs underlying asset return
Part V From risk management to asset and liability management (ALM)
Techniques for measuring structural balance sheet risks
Repricing schedules
Static and dynamic simulations
VaR in an asset and liability framework
VaR applicabilty to different types of ALM
VaR applied to the ALM of a bank
VaR applied to the ALM of an insurance company
Conclusions
Appendices
Appendix 1: Useful mathematical concepts
A.1.1 Functions of one variable
A.1.2 Functions of several variables
A.1.3 Matrix algebra
Appendix 2: Useful concepts from probability theory
A.2.1 Random variables
A.2.2 Some classical distributions
A.2.3 Stochastic processes
Appendix 3: Useful statistical concepts
A.3.1 Statistical inference
A.3.2 Regression analysis
Appendix 4: Extreme value theory
A.4.1 Finite result
A.4.2 Asymptotical results
Appendix 5: The forward-forward concept
A.5.1 Introduction
A.5.2 The forward-forward rate
A.5.3 The forward rate agreement
Index
References
Table of contents
CD-ROM includes:
variance-covariance matrix, Monte Carlo and historical analysis examples;
asset management optimisation examples (Elton, Gruber and Padberg methodology); asset and liability gaps and VaR estimations.