Models and Analysis
Buch, Englisch, 384 Seiten, Format (B × H): 159 mm x 236 mm, Gewicht: 626 g
ISBN: 978-1-118-34946-5
Verlag: Wiley
A comprehensive and accessible introduction to modern quantitative risk management.
The business world is rife with risk and uncertainty, and risk management is a vitally important topic for managers. The best way to achieve a clear understanding of risk is to use quantitative tools and probability models. Written for students, this book has a quantitative emphasis but is accessible to those without a strong mathematical background.
Business Risk Management: Models and Analysis
- Discusses novel modern approaches to risk management
- Introduces advanced topics in an accessible manner
- Includes motivating worked examples and exercises (including selected solutions)
- Is written with the student in mind, and does not assume advanced mathematics
- Is suitable for self-study by the manager who wishes to better understand this important field.
Aimed at postgraduate students, this book is also suitable for senior undergraduates, MBA students, and all those who have a general interest in business risk.
Autoren/Hrsg.
Weitere Infos & Material
Preface xiii
1 What is risk management? 1
1.1 Introduction 2
1.2 Identifying and documenting risk 5
1.3 Fallacies and traps in risk management 7
1.4 Why safety is different 9
1.5 The Basel framework 11
1.6 Hold or hedge? 12
1.7 Learning from a disaster 13
1.7.1 What went wrong? 15
Notes 17
References 18
Exercises 19
2 The structure of risk 22
2.1 Introduction to probability and risk 23
2.2 The structure of risk 25
2.2.1 Intersection and union risk 25
2.2.2 Maximum of random variables 28
2.3 Portfolios and diversification 30
2.3.1 Adding random variables 30
2.3.2 Portfolios with minimum variance 33
2.3.3 Optimal portfolio theory 37
2.3.4 When risk follows a normal distribution 38
2.4 The impact of correlation 40
2.4.1 Using covariance in combining random variables 41
2.4.2 Minimum variance portfolio with covariance 43
2.4.3 The maximum of variables that are positively correlated 44
2.4.4 Multivariate normal 46
2.5 Using copulas to model multivariate distributions 49
2.5.1 *Details on copula modeling 52
Notes 58
References 59
Exercises 60
3 Measuring risk 63
3.1 How can we measure risk? 64
3.2 Value at risk 67
3.3 Combining and comparing risks 73
3.4 VaR in practice 76
3.5 Criticisms of VaR 79
3.6 Beyond value at risk 82
3.6.1 *More details on expected shortfall 86
Notes 88
References 88
Exercises 89
4 Understanding the tails 92
4.1 Heavy-tailed distributions 93
4.1.1 Defining the tail index 93
4.1.2 Estimating the tail index 95
4.1.3 *More details on the tail index 98
4.2 Limiting distributions for the maximum 100
4.2.1 *More details on maximum distributions and Fisher–Tippett 106
4.3 Excess distributions 109
4.3.1 *More deta
