Home Page Icon
Home Page
Table of Contents for
Cover
Close
Cover
by Francois Longin
Extreme Events in Finance
Cover
Financial Engineering and Econometrics
Title Page
Copyright
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
Properties of
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 VR 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 Reading
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
Financial Engineering and Econometrics
End User License Agreement
Search in book...
Toggle Font Controls
Playlists
Add To
Create new playlist
Name your new playlist
Playlist description (optional)
Cancel
Create playlist
Sign In
Email address
Password
Forgot Password?
Create account
Login
or
Continue with Facebook
Continue with Google
Sign Up
Full Name
Email address
Confirm Email Address
Password
Login
Create account
or
Continue with Facebook
Continue with Google
Next
Next Chapter
Contents
Add Highlight
No Comment
..................Content has been hidden....................
You can't read the all page of ebook, please click
here
login for view all page.
Day Mode
Cloud Mode
Night Mode
Reset