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Extreme events in finance : a handbook of extreme value theory and its applications

"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 as well as a practical understanding of market behavior including both ordinary and extraordinary conditions. Beginning with a fascinating history of EVTs and financials 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 features a combination of the theory, methods, and applications of extreme value theory (EVT) in finance as well as a practical understanding of market behavior including both ordinary and extraordinary conditions"--

Electronic books

Monografía

1. Introduction
François Longin

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 Final words

1.8 Thank you note

References

2. Extremes under Dependence -- historical development and parallels with central limit theory
Ross Leadbetter

2.1 Introduction

2.2 Classical (iid) 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, Strong mixing

2.5 Weak distributional mixing for EVT, D(un), Extremal Index

2.6 Point process of level exceedances

2.7Continuous parameter extremes

2.8 References

3. The Extreme Value Problem in Finance: Comparing the Pragmatic Programme with the Mandelbrot Programme
Christian Walter

3.1 The extreme value puzzle in financial modelling

3.2 The Sato classification and the two programmes

3.3 Mandelbrot's programme: a fractal approach

3.4 The pragmatic programme: a data-driven approach

3.5 Conclusion

References

4. Extreme Value Theory: An Introductory Overview
Isabel Fraga Alves and Cláudia Neves

4.1 Introduction

4.2 Univariate Case

4.3 Multivariate Case -- some highlights

4.4 Further reading

Acknowledgements

References

5. The estimation of the extreme value index
Jan Beirlant, Klaus Herrmann, and Jozef Teugels

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 bias reduced estimation

5.6 The case study

5.7 Other topics and comments

References

6. Bootstrap methods in statistics of extremes
Ivette Gomes, Frederico Caeiro, Lígia Henriques-Rodrigues, and B.G. Manjunath

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

References

7. Extreme values statistics for Markov chains with applications to Finance and Insurance
Patrice Bertail, Stéphan Clémençon, and Charles Tillier

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

8. Lévy Processes and Extreme Value Theory
Olivier Le Courtois and Christian Walter

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

9. Statistics of Extremes: Challenges and Opportunities
Miguel de Carvalho

9.1 Introduction

9.2 Statistics of Bivariate Extremes

9.3 Models Based on Families of Tilted Measures

9.4 Miscellanea

References

10. Measures of financial risk
Serguei Novak

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

References

11. On the estimation of the distribution of aggregated heavy tailed risks. Application to risk measures
Marie Kratz

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

12. Estimation methods for Value at Risk
Saralees Nadarajah and Stephen Chan

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

Acknowledgments

References

13. Comparing Tail Risk and Systemic Risk Profiles for Different Types of US Financial Institutions
Stefan Straetmans and Thanh Thi Huyen Dinh

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

14. Extreme Value Theory and Credit Spreads
Wesley Phoa

13.1 Preliminaries

13.2 Tail behavior of credit markets

13.3 Some multivariate analysis

13.4 Approximating value-at-risk for credit portfolios

13.5 Other directions

References

15. Extreme Value Theory and Risk Management in Electricity Markets
Kam Fong Chan and Philip Gray

15.1 Introduction

15.2 Prior Literature

15.3 Specification of VaR Estimation Approaches

15.4 Empirical Analysis

15.5 Conclusion

References

16. Margin Setting and Extreme Value Theory
John Cotter and Kevin Dowd

16.1 Introduction

16.2 Margin Setting

16.3 Theory and Methods

16.4 Empirical Results

16.5 Conclusions

References

17. The Sortino Ratio and Extreme Value Theory: An Application to Asset Allocation
Geoffrey Booth and John Paul Broussard

17.1 Introduction

17.2 Data Definitions and Description

17.3 The Performance Ratios and Their Estimations

17.4 Performance Measurement Results and Implications

17.5 Concluding Remarks

References

18. Portfolio Insurance: the Extreme Value Approach Applied to the CPPI Method
Philippe Bertrand and Jean-Luc Prigent

18.1 Introduction

18.2 The CPPI method

18.3 CPPI and Quantile Hedging

18.4 Conclusion

References

19. The choice of the distribution of asset returns: How extreme value theory can help?
François Longin

Introduction

19.1 Extreme value theory

19.2 Estimation of the tail index

19.3 Application of extreme value theory to discriminate among distributions of returns

19.4 Empirical results

19.5 Conclusion

References

Appendix

20. Protecting Assets Under Non-Parametric Market Conditions
Jean-Marie Choffray et Charles Pahud de Mortanges

20.1 Investors "Known knowns"

20.2 Investors "Known unknowns"

20.3 Investors "Unknown knowns"

20.4 Investors "Unknown unknowns"

References

21. EVT seen by a vet: A practitioner's experience on extreme value theory
Jean-François Boulier

21.1 What has "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 as well as a practical understanding of market behavior including both ordinary and extraordinary conditions. Beginning with a fascinating history of EVTs and financials 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."-- Provided by publisher "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 as well as a practical understanding of market behavior including both ordinary and extraordinary conditions"-- Provided by publisher Finance- Mathematical models Extreme value theory- Mathematical models BUSINESS & ECONOMICS- Insurance- Risk Assessment & Management BUSINESS & ECONOMICS- Finance Finance- Mathematical models Electronic books Longin, François Michel 1968-) editor Print version Extreme events in finance. Hoboken : Wiley, 2016 9781118650196 (DLC) 2016004187 (OCoLC)936349635

1. Introduction
François Longin

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 Final words

1.8 Thank you note

References

2. Extremes under Dependence -- historical development and parallels with central limit theory
Ross Leadbetter

2.1 Introduction

2.2 Classical (iid) 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, Strong mixing

2.5 Weak distributional mixing for EVT, D(un), Extremal Index

2.6 Point process of level exceedances

2.7Continuous parameter extremes

2.8 References

3. The Extreme Value Problem in Finance: Comparing the Pragmatic Programme with the Mandelbrot Programme
Christian Walter

3.1 The extreme value puzzle in financial modelling

3.2 The Sato classification and the two programmes

3.3 Mandelbrot's programme: a fractal approach

3.4 The pragmatic programme: a data-driven approach

3.5 Conclusion

References

4. Extreme Value Theory: An Introductory Overview
Isabel Fraga Alves and Cláudia Neves

4.1 Introduction

4.2 Univariate Case

4.3 Multivariate Case -- some highlights

4.4 Further reading

Acknowledgements

References

5. The estimation of the extreme value index
Jan Beirlant, Klaus Herrmann, and Jozef Teugels

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 bias reduced estimation

5.6 The case study

5.7 Other topics and comments

References

6. Bootstrap methods in statistics of extremes
Ivette Gomes, Frederico Caeiro, Lígia Henriques-Rodrigues, and B.G. Manjunath

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

References

7. Extreme values statistics for Markov chains with applications to Finance and Insurance
Patrice Bertail, Stéphan Clémençon, and Charles Tillier

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

8. Lévy Processes and Extreme Value Theory
Olivier Le Courtois and Christian Walter

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

9. Statistics of Extremes: Challenges and Opportunities
Miguel de Carvalho

9.1 Introduction

9.2 Statistics of Bivariate Extremes

9.3 Models Based on Families of Tilted Measures

9.4 Miscellanea

References

10. Measures of financial risk
Serguei Novak

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

References

11. On the estimation of the distribution of aggregated heavy tailed risks. Application to risk measures
Marie Kratz

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

12. Estimation methods for Value at Risk
Saralees Nadarajah and Stephen Chan

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

Acknowledgments

References

13. Comparing Tail Risk and Systemic Risk Profiles for Different Types of US Financial Institutions
Stefan Straetmans and Thanh Thi Huyen Dinh

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

14. Extreme Value Theory and Credit Spreads
Wesley Phoa

13.1 Preliminaries

13.2 Tail behavior of credit markets

13.3 Some multivariate analysis

13.4 Approximating value-at-risk for credit portfolios

13.5 Other directions

References

15. Extreme Value Theory and Risk Management in Electricity Markets
Kam Fong Chan and Philip Gray

15.1 Introduction

15.2 Prior Literature

15.3 Specification of VaR Estimation Approaches

15.4 Empirical Analysis

15.5 Conclusion

References

16. Margin Setting and Extreme Value Theory
John Cotter and Kevin Dowd

16.1 Introduction

16.2 Margin Setting

16.3 Theory and Methods

16.4 Empirical Results

16.5 Conclusions

References

17. The Sortino Ratio and Extreme Value Theory: An Application to Asset Allocation
Geoffrey Booth and John Paul Broussard

17.1 Introduction

17.2 Data Definitions and Description

17.3 The Performance Ratios and Their Estimations

17.4 Performance Measurement Results and Implications

17.5 Concluding Remarks

References

18. Portfolio Insurance: the Extreme Value Approach Applied to the CPPI Method
Philippe Bertrand and Jean-Luc Prigent

18.1 Introduction

18.2 The CPPI method

18.3 CPPI and Quantile Hedging

18.4 Conclusion

References

19. The choice of the distribution of asset returns: How extreme value theory can help?
François Longin

Introduction

19.1 Extreme value theory

19.2 Estimation of the tail index

19.3 Application of extreme value theory to discriminate among distributions of returns

19.4 Empirical results

19.5 Conclusion

References

Appendix

20. Protecting Assets Under Non-Parametric Market Conditions
Jean-Marie Choffray et Charles Pahud de Mortanges

20.1 Investors "Known knowns"

20.2 Investors "Known unknowns"

20.3 Investors "Unknown knowns"

20.4 Investors "Unknown unknowns"

References

21. EVT seen by a vet: A practitioner's experience on extreme value theory
Jean-François Boulier

21.1 What has "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 as well as a practical understanding of market behavior including both ordinary and extraordinary conditions. Beginning with a fascinating history of EVTs and financials 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."-- Provided by publisher "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 as well as a practical understanding of market behavior including both ordinary and extraordinary conditions"-- Provided by publisher Finance- Mathematical models Extreme value theory- Mathematical models BUSINESS & ECONOMICS- Insurance- Risk Assessment & Management BUSINESS & ECONOMICS- Finance Finance- Mathematical models Electronic books Longin, François Michel 1968-) editor Print version Extreme events in finance. Hoboken : Wiley, 2016 9781118650196 (DLC) 2016004187 (OCoLC)936349635

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Título:
Extreme events in finance : a handbook of extreme value theory and its applications / edited by François Longin
Editorial:
Hoboken : Wiley, 2016
Descripción física:
1 online resource
Mención de serie:
Wiley handbooks in financial engineering and econometrics
Bibliografía:
Includes bibliographical references and index
Contenido:

1. Introduction
François Longin

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 Final words

1.8 Thank you note

References

2. Extremes under Dependence -- historical development and parallels with central limit theory
Ross Leadbetter

2.1 Introduction

2.2 Classical (iid) 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, Strong mixing

2.5 Weak distributional mixing for EVT, D(un), Extremal Index

2.6 Point process of level exceedances

2.7Continuous parameter extremes

2.8 References

3. The Extreme Value Problem in Finance: Comparing the Pragmatic Programme with the Mandelbrot Programme
Christian Walter

3.1 The extreme value puzzle in financial modelling

3.2 The Sato classification and the two programmes

3.3 Mandelbrot's programme: a fractal approach

3.4 The pragmatic programme: a data-driven approach

3.5 Conclusion

References

4. Extreme Value Theory: An Introductory Overview
Isabel Fraga Alves and Cláudia Neves

4.1 Introduction

4.2 Univariate Case

4.3 Multivariate Case -- some highlights

4.4 Further reading

Acknowledgements

References

5. The estimation of the extreme value index
Jan Beirlant, Klaus Herrmann, and Jozef Teugels

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 bias reduced estimation

5.6 The case study

5.7 Other topics and comments

References

6. Bootstrap methods in statistics of extremes
Ivette Gomes, Frederico Caeiro, Lígia Henriques-Rodrigues, and B.G. Manjunath

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

References

7. Extreme values statistics for Markov chains with applications to Finance and Insurance
Patrice Bertail, Stéphan Clémençon, and Charles Tillier

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

8. Lévy Processes and Extreme Value Theory
Olivier Le Courtois and Christian Walter

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

9. Statistics of Extremes: Challenges and Opportunities
Miguel de Carvalho

9.1 Introduction

9.2 Statistics of Bivariate Extremes

9.3 Models Based on Families of Tilted Measures

9.4 Miscellanea

References

10. Measures of financial risk
Serguei Novak

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

References

11. On the estimation of the distribution of aggregated heavy tailed risks. Application to risk measures
Marie Kratz

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

12. Estimation methods for Value at Risk
Saralees Nadarajah and Stephen Chan

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

Acknowledgments

References

13. Comparing Tail Risk and Systemic Risk Profiles for Different Types of US Financial Institutions
Stefan Straetmans and Thanh Thi Huyen Dinh

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

14. Extreme Value Theory and Credit Spreads
Wesley Phoa

13.1 Preliminaries

13.2 Tail behavior of credit markets

13.3 Some multivariate analysis

13.4 Approximating value-at-risk for credit portfolios

13.5 Other directions

References

15. Extreme Value Theory and Risk Management in Electricity Markets
Kam Fong Chan and Philip Gray

15.1 Introduction

15.2 Prior Literature

15.3 Specification of VaR Estimation Approaches

15.4 Empirical Analysis

15.5 Conclusion

References

16. Margin Setting and Extreme Value Theory
John Cotter and Kevin Dowd

16.1 Introduction

16.2 Margin Setting

16.3 Theory and Methods

16.4 Empirical Results

16.5 Conclusions

References

17. The Sortino Ratio and Extreme Value Theory: An Application to Asset Allocation
Geoffrey Booth and John Paul Broussard

17.1 Introduction

17.2 Data Definitions and Description

17.3 The Performance Ratios and Their Estimations

17.4 Performance Measurement Results and Implications

17.5 Concluding Remarks

References

18. Portfolio Insurance: the Extreme Value Approach Applied to the CPPI Method
Philippe Bertrand and Jean-Luc Prigent

18.1 Introduction

18.2 The CPPI method

18.3 CPPI and Quantile Hedging

18.4 Conclusion

References

19. The choice of the distribution of asset returns: How extreme value theory can help?
François Longin

Introduction

19.1 Extreme value theory

19.2 Estimation of the tail index

19.3 Application of extreme value theory to discriminate among distributions of returns

19.4 Empirical results

19.5 Conclusion

References

Appendix

20. Protecting Assets Under Non-Parametric Market Conditions
Jean-Marie Choffray et Charles Pahud de Mortanges

20.1 Investors "Known knowns"

20.2 Investors "Known unknowns"

20.3 Investors "Unknown knowns"

20.4 Investors "Unknown unknowns"

References

21. EVT seen by a vet: A practitioner's experience on extreme value theory
Jean-François Boulier

21.1 What has

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Print version: Extreme events in finance., Hoboken : Wiley, 2016 9781118650196 (DLC) 2016004187 (OCoLC)936349635

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