Extreme Events in Finance

A Handbook of Extreme Value Theory and its Applications
 
 
John Wiley & Sons Inc (Verlag)
  • erschienen am 21. September 2016
  • |
  • 640 Seiten
 
E-Book | PDF mit Adobe DRM | Systemvoraussetzungen
978-1-118-65033-2 (ISBN)
 
A guide to the growing importance of extreme value risk theory, methods, and applications in the financial sector
Presenting a uniquely accessible guide, Extreme Events in Finance: A Handbook of Extreme Value Theory and Its Applications features a combination of the theory, methods, and applications of extreme value theory (EVT) in finance and a practical understanding of market behavior including both ordinary and extraordinary conditions.
Beginning with a fascinating history of EVTs and financial modeling, the handbook introduces the historical implications that resulted in the applications and then clearly examines the fundamental results of EVT in finance. After dealing with these theoretical results, the handbook focuses on the EVT methods critical for data analysis. Finally, the handbook features the practical applications and techniques and how these can be implemented in financial markets. Extreme Events in Finance: A Handbook of Extreme Value Theory and Its Applications includes:
* Over 40 contributions from international experts in the areas of finance, statistics, economics, business, insurance, and risk management
* Topical discussions on univariate and multivariate case extremes as well as regulation in financial markets
* Extensive references in order to provide readers with resources for further study
* Discussions on using R packages to compute the value of risk and related quantities
The book is a valuable reference for practitioners in financial markets such as financial institutions, investment funds, and corporate treasuries, financial engineers, quantitative analysts, regulators, risk managers, large-scale consultancy groups, and insurers. Extreme Events in Finance: A Handbook of Extreme Value Theory and Its Applications is also a useful textbook for postgraduate courses on the methodology of EVTs in finance.
François Longin, PhD, is Professor in the Department of Finance at ESSEC Business School, France. He has been working on the applications of extreme value theory to financial markets for many years, and his research has been applied by financial institutions in the risk management area including market, credit, and operational risks. His research works can be found in scientific journals such as The Journal of Finance. Dr. Longin is currently a financial consultant with expertise covering risk management for financial institutions and portfolio management for asset management firms.
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  • Cover
  • Title Page
  • Copyright
  • Contents
  • About the Editor
  • About the Contributors
  • Chapter 1 Introduction
  • 1.1 Extremes
  • 1.2 History
  • 1.3 Extreme value theory
  • 1.4 Statistical estimation of extremes
  • 1.5 Applications in finance
  • 1.6 Practitioners' points of view
  • 1.7 A broader view on modeling extremes
  • 1.8 Final words
  • 1.9 Thank you note
  • References
  • Chapter 2 Extremes Under Dependence-Historical Development and Parallels with Central Limit Theory
  • 2.1 Introduction
  • 2.2 Classical (I.I.D.) central limit and extreme value theories
  • 2.3 Exceedances of levels, kth largest values
  • 2.4 CLT and EVT for stationary sequences, bernstein's blocks and strong mixing
  • 2.5 Weak distributional mixing for EVT, D(un), extremal index
  • 2.6 Point process of level exceedances
  • 2.7 Continuous parameter extremes
  • References
  • Chapter 3 The Extreme Value Problem in Finance: Comparing the Pragmatic Program with the Mandelbrot Program
  • 3.1 The extreme value puzzle in financial modeling
  • 3.2 The sato classification and the two programs
  • 3.3 Mandelbrot's program: A fractal approach
  • 3.4 The Pragmatic Program: A data-driven approach
  • 3.5 Conclusion
  • Acknowledgments
  • References
  • Chapter 4 Extreme Value Theory: An Introductory Overview
  • 4.1 Introduction
  • 4.2 Univariate case
  • 4.3 Multivariate case: Some highlights
  • Further reading
  • Acknowledgments
  • References
  • Chapter 5 Estimation of the Extreme Value Index
  • 5.1 Introduction
  • 5.2 The main limit theorem behind extreme value theory
  • 5.3 Characterizations of the max-domains of attraction and extreme value index estimators
  • 5.4 Consistency and asymptotic normality of the estimators
  • 5.5 Second-order reduced-bias estimation
  • 5.6 Case study
  • 5.7 Other topics and comments
  • References
  • Chapter 6 Bootstrap Methods in Statistics of Extremes
  • 6.1 Introduction
  • 6.2 A few details on EVT
  • 6.3 The bootstrap methodology in statistics of univariate extremes
  • 6.4 Applications to simulated data
  • 6.5 Concluding remarks
  • Acknowledgments
  • References
  • Chapter 7 Extreme Values Statistics for Markov Chains with Applications to Finance and Insurance
  • 7.1 Introduction
  • 7.2 On the (pseudo) regenerative approach for markovian data
  • 7.3 Preliminary results
  • 7.4 Regeneration-based statistical methods for extremal events
  • 7.5 The extremal index
  • 7.6 The regeneration-based hill estimator
  • 7.7 Applications to ruin theory and financial time series
  • 7.8 An application to the CAC40
  • 7.9 Conclusion
  • References
  • Chapter 8 Lévy Processes and Extreme Value Theory
  • 8.1 Introduction
  • 8.2 Extreme value theory
  • 8.3 Infinite divisibility and Lévy processes
  • 8.4 Heavy-tailed Lévy processes
  • 8.5 Semi-heavy-tailed Lévy processes
  • 8.6 Lévy processes and extreme values
  • 8.7 Conclusion
  • References
  • Chapter 9 Statistics of Extremes: Challenges and Opportunities
  • 9.1 Introduction
  • 9.2 Statistics of bivariate extremes
  • 9.3 Models based on families of tilted measures
  • 9.4 Miscellanea
  • References
  • Chapter 10 Measures of Financial Risk
  • 10.1 Introduction
  • 10.2 Traditional measures of risk
  • 10.3 Risk estimation
  • 10.4 "Technical analysis" of financial data
  • 10.5 Dynamic risk measurement
  • 10.6 Open problems and further research
  • 10.7 Conclusion
  • Acknowledgment
  • References
  • Chapter 11 On the Estimation of the Distribution of Aggregated Heavy-Tailed Risks: Application to Risk Measures
  • 11.1 Introduction
  • 11.2 A brief review of existing methods
  • 11.3 New approaches: Mixed limit theorems
  • 11.4 Application to risk measures and comparison
  • 11.5 Conclusion
  • References
  • Chapter 12 Estimation Methods for Value at Risk
  • 12.1 Introduction
  • 12.2 General properties
  • 12.3 Parametric methods
  • 12.4 Nonparametric methods
  • 12.5 Semiparametric methods
  • 12.6 Computer software
  • 12.7 Conclusions
  • Acknowledgment
  • References
  • Chapter 13 Comparing Tail Risk and Systemic Risk Profiles for Different Types of U.S. Financial Institutions
  • 13.1 Introduction
  • 13.2 Tail risk and systemic risk indicators
  • 13.3 Tail risk and systemic risk estimation
  • 13.4 Empirical results
  • 13.5 Conclusions
  • References
  • Chapter 14 Extreme Value Theory and Credit Spreads
  • 14.1 Preliminaries
  • 14.2 Tail behavior of credit markets
  • 14.3 Some multivariate analysis
  • 14.4 Approximating value at risk for credit portfolios
  • 14.5 Other directions
  • References
  • Chapter 15 Extreme Value Theory and Risk Management in Electricity Markets
  • 15.1 Introduction
  • 15.2 Prior literature
  • 15.3 Specification of VaR estimation approaches
  • 15.4 Empirical analysis
  • 15.5 Conclusion
  • Acknowledgment
  • References
  • Chapter 16 Margin Setting and Extreme Value Theory
  • 16.1 Introduction
  • 16.2 Margin setting
  • 16.3 Theory and methods
  • 16.4 Empirical results
  • 16.5 Conclusions
  • Acknowledgment
  • References
  • Chapter 17 The Sortino Ratio and Extreme Value Theory: An Application to Asset Allocation
  • 17.1 Introduction
  • 17.2 Data definitions and description
  • 17.3 Performance ratios and their estimations
  • 17.4 Performance measurement results and implications
  • 17.5 Concluding remarks
  • Acknowledgments
  • References
  • Chapter 18 Portfolio Insurance: The Extreme Value Approach Applied to the CPPI Method
  • 18.1 Introduction
  • 18.2 The CPPI method
  • 18.3 CPPI and quantile hedging
  • 18.4 Conclusion
  • References
  • Chapter 19 The Choice of the Distribution of Asset Returns: How Extreme Value Can Help?1
  • 19.1 Introduction
  • 19.2 Extreme value theory
  • 19.3 Estimation of the tail index
  • 19.4 Application of extreme value theory to discriminate among distributions of returns
  • 19.5 Empirical results
  • 19.6 Conclusion
  • References
  • Chapter 20 Protecting Assets Under Non-Parametric Market Conditions
  • 20.1 Investors' "known knowns"
  • 20.2 Investors' "known unknowns"
  • 20.3 Investors' "unknown knowns"
  • 20.4 Investors' "unknown unknowns"
  • 20.5 Synthesis
  • References
  • Chapter 21 EVT Seen by a Vet: A Practitioner's Experience on Extreme Value Theory
  • 21.1 What has the vet done?
  • 21.2 Why use EVT?
  • 21.3 What EVT could additionally bring to the party?
  • 21.4 A final thought
  • References
  • Chapter 22 The Robotization of Financial Activities: A Cybernetic Perspective
  • 22.1 An increasingly complex system
  • 22.2 Human error
  • 22.3 Concretely, what do we need to do to transform a company into a machine?
  • References
  • Chapter 23 Two Tales of Liquidity Stress
  • 23.1 The french money market fund industry. How history has shaped a potentially vulnerable framework
  • 23.2 The 1992-1995 forex crisis
  • 23.3 Four mutations paving the way for another meltdown
  • 23.4 The subprime crisis spillover. How some MMFs were forced to lock and some others not
  • 23.5 Conclusion. What lessons can be drawn from these two tales?
  • Further Readings
  • Chapter 24 Managing Operational Risk in the Banking Business-An Internal Auditor Point of View
  • Further Reading
  • References
  • Annexes
  • Chapter 25 Credo Ut Intelligam*
  • 25.1 Introduction
  • 25.2 "Anselmist" finance
  • 25.3 Casino or dance hall?
  • 25.4 Simple-minded diversification
  • 25.5 Homo sapiens versus homo economicus
  • Acknowledgement
  • References
  • Chapter 26 Bounded Rationalities, Routines, and Practical as well as Theoretical Blindness: On the Discrepancy Between Markets and Corporations
  • 26.1 Introduction: Expecting the unexpected
  • 26.2 Markets and corporations: A structural and self-disruptive divergence of interests
  • 26.3 Making a step back from a dream: On people expectations
  • 26.4 How to disentangle people from a unilateral short-term orientation?
  • References
  • Name Index
  • Subject Index
  • EULA

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