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 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. INDICE: About the Editor xiii .About the Contributors xv .1 Introduction 1François Longin .1.1 Extremes 1 .1.2 History 2 .1.3 Extreme value theory 2 .1.4 Statistical estimation of extremes 2 .1.5 Applications in finance 4 .1.6 Practitioners points of view 6 .1.7 A broader view on modeling extremes 6 .1.8 Final words 7 .1.9 Thank you note 7 .References 8 .2 Extremes Under Dependence Historical Development and Parallels with Central Limit Theory 11M.R. Leadbetter .2.1 Introduction 11 .2.2 Classical (I.I.D.) central limit and extreme value theories 12 .2.3 Exceedances of levels, kth largest values 14 .2.4 CLT and EVT for stationary sequences, bernstein s blocks, and strong mixing 15 .2.5 Weak distributional mixing for EVT, D(un), extremal index 18 .2.6 Point process of level exceedances 19 .2.7 Continuous parameter extremes 20 .References 22 .3 The Extreme Value Problem in Finance: Comparing the Pragmatic Program with the Mandelbrot Program 25Christian Walter .3.1 The extreme value puzzle in financial modeling 25 .3.2 The sato classification and the two programs 28 .3.3 Mandelbrot s program: A fractal approach 34 .3.4 The Pragmatic Program: A data–driven approach 39 .3.5 Conclusion 47 .Acknowledgments 48 .References 48 .4 Extreme Value Theory: An Introductory Overview 53Isabel Fraga Alves and Cláudia Neves .4.1 Introduction 53 .4.2 Univariate case 56 .4.3 Multivariate case: Some highlights 84 .Further reading 90 .Acknowledgments 90 .References 90 .5 Estimation of the Extreme Value Index 97Beirlant J., Herrmann K., and Teugels J.L. .5.1 Introduction 97 .5.2 The main limit theorem behind extreme value theory 98 .5.3 Characterizations of the max–domains of attraction and extreme value index estimators 99 .5.4 Consistency and asymptotic normality of the estimators 103 .5.5 Second–order reduced–bias estimation 104 .5.6 Case study 106 .5.7 Other topics and comments 108 .References 111 .6 Bootstrap Methods in Statistics of Extremes 117M. Ivette Gomes, Frederico Caeiro, Lígia Henriques–Rodrigues, and B.G. Manjunath .6.1 Introduction 117 .6.2 A few details on EVT 119 .6.3 The bootstrap methodology in statistics of univariate extremes 127 .6.4 Applications to simulated data 133 .6.5 Concluding remarks 133 .Acknowledgments 135 .References 135 .7 Extreme Values Statistics for Markov Chains with Applications to Finance and Insurance 139Patrice Bertail, Stéphan Clémençon, and Charles Tillier .7.1 Introduction 139 .7.2 On the (pseudo) regenerative approach for markovian data 141 .7.3 Preliminary results 151 .7.4 Regeneration–based statistical methods for extremal events 154 .7.5 The extremal index 156 .7.6 The regeneration–based hill estimator 159 .7.7 Applications to ruin theory and financial time series 161 .7.8 An application to the CAC40 165 .7.9 Conclusion 167 .References 167 .8 Lévy Processes and Extreme Value Theory 171Olivier Le Courtois and Christian Walter .8.1 Introduction 171 .8.2 Extreme value theory 173 .8.3 Infinite divisibility and Lévy processes 178 .8.4 Heavy–tailed Lévy processes 182 .8.5 Semi–heavy–tailed Lévy processes 184 .8.6 Lévy processes and extreme values 187 .8.7 Conclusion 192 .References 192 .9 Statistics of Extremes: Challenges and Opportunities 195M. de Carvalho .9.1 Introduction 195 .9.2 Statistics of bivariate extremes 196 .9.3 Models based on families of tilted measures 204 .9.4 Miscellanea 209 .References 211 .10 Measures of Financial Risk 215S.Y. Novak .10.1 Introduction 215 .10.2 Traditional measures of risk 215 .10.3 Risk estimation 218 .10.4 Technical analysis of financial data 222 .10.5 Dynamic risk measurement 226 .10.6 Open problems and further research 234 .10.7 Conclusion 235 .Acknowledgment 235 .References 235 .11 On the Estimation of the Distribution of Aggregated Heavy–Tailed Risks: Application to Risk Measures 239Marie Kratz .11.1 Introduction 239 .11.2 A brief review of existing methods 245 .11.3 New approaches: Mixed limit theorems 247 .11.4 Application to risk measures and comparison 269 .11.5 Conclusion 277 .References 279 .12 Estimation Methods for Value at Risk 283Saralees Nadarajah and Stephen Chan .12.1 Introduction 283 .12.2 General properties 289 .12.3 Parametric methods 300 .12.4 Nonparametric methods 326 .12.5 Semiparametric methods 332 .12.6 Computer software 344 .12.7 Conclusions 347 .Acknowledgment 347 .References 347 .13 Comparing Tail Risk and Systemic Risk Profiles for Different Types of U.S. Financial Institutions 357Stefan Straetmans and Thanh Thi Huyen Dinh .13.1 Introduction 357 .13.2 Tail risk and systemic risk indicators 361 .13.3 Tail risk and systemic risk estimation 364 .13.4 Empirical results 368 .13.5 Conclusions 381 .References 382 .14 Extreme Value Theory and Credit Spreads 391Wesley Phoa .14.1 Preliminaries 391 .14.2 Tail behavior of credit markets 394 .14.3 Some multivariate analysis 398 .14.4 Approximating value at risk for credit portfolios 401 .14.5 Other directions 403 .References 404 .15 Extreme Value Theory and Risk Management in Electricity Markets 405Kam Fong Chan and Philip Gray .15.1 Introduction 405 .15.2 Prior literature 407 .15.3 Specification of VaR estimation approaches 409 .15.4 Empirical analysis 413 .15.5 Conclusion 422 .Acknowledgment 423 .References 423 .16 Margin Setting and Extreme Value Theory 427John Cotter and Kevin Dowd .16.1 Introduction 427 .16.2 Margin setting 428 .16.3 Theory and methods 430 .16.4 Empirical results 434 .16.5 Conclusions 439 .Acknowledgment 440 .References 440 .17 The Sortino Ratio and Extreme Value Theory: An Application to Asset Allocation 443G. Geoffrey Booth and John Paul Broussard .17.1 Introduction 443 .17.2 Data definitions and description 446 .17.3 Performance ratios and their estimations 451 .17.4 Performance measurement results and implications 456 .17.5 Concluding remarks 460 .Acknowledgments 461 .References 461 .18 Portfolio Insurance: The Extreme Value Approach Applied to the CPPI Method 465Philippe Bertrand and Jean–Luc Prigent .18.1 Introduction 465 .18.2 The CPPI method 467 .18.3 CPPI and quantile hedging 472 .18.4 Conclusion 481 .References 481 .19 The Choice of the Distribution of Asset Returns: How Extreme Value Can Help? 483François Longin .19.1 Introduction 483 .19.2 Extreme value theory 485 .19.3 Estimation of the tail index 488 .19.4 Application of extreme value theory to discriminate among distributions of returns 490 .19.5 Empirical results 493 .19.6 Conclusion 501 .References 501 .20 Protecting Assets Under Non–Parametric Market Conditions 507Jean–Marie Choffray and Charles Pahud de Mortanges .20.1 Investors known knowns 509 .20.2 Investors known unknowns 512 .20.3 Investors unknown knowns 515 .20.4 Investors unknown unknowns 518 .20.5 Synthesis 522 .References 523 .21 EVT Seen by a Vet: A Practitioner s Experience on Extreme Value Theory 525Jean–François Boulier .21.1 What has the vet done? 525 .21.2 Why use EVT? 526 .21.3 What EVT could additionally bring to the party? 528 .21.4 A final thought 528 .References 528 .22 The Robotization of Financial Activities: A Cybernetic Perspective 529Hubert Rodarie .22.1 An increasingly complex system 530 .22.2 Human error 532 .22.3 Concretely, what do we need to do to transform a company into a machine? 534 .References 543 .23 Two Tales of Liquidity Stress 545Jacques Ninet .23.1 The french money market fund industry. How history has shaped a potentially vulnerable framework 546 .23.2 The 1992 1995 forex crisis 547 .23.3 Four mutations paving the way for another meltdown 549 .23.4 The subprime crisis spillover. How some MMFs were forced to lock and some others not 551 .23.5 Conclusion. What lessons can be drawn from these two tales? 552 .Further Readings 553 .24 Managing Operational Risk in the Banking Business An Internal Auditor Point of View 555Maxime Laot .Further Reading 559 .References 560 .Annexes 560 .25 Credo Ut Intelligam 563Henri Bourguinat and Eric Briys .25.1 Introduction 563 .25.2 Anselmist finance 563 .25.3 Casino or dance hall? 565 .25.4 Simple–minded diversification 566 .25.5 Homo sapiens versus homo economicus 568 .Acknowledgement 569 .References 569 .26 Bounded Rationalities, Routines, and Practical as well as Theoretical Blindness: On the Discrepancy Between Markets and Corporations 571Laurent Bibard .26.1 Introduction: Expecting the unexpected 571 .26.2 Markets and corporations: A structural and self–disruptive divergence of interests 572 .26.3 Making a step back from a dream: On people expectations 574 .26.4 How to disentangle people from a unilateral short–term orientation? 578 .References 580 .Name Index 583 .Subject Index 593

• ISBN: 978-1-118-65019-6
• Editorial: Wiley–Blackwell
• Encuadernacion: Cartoné
• Páginas: 640
• Fecha Publicación: 09/11/2016
• Nº Volúmenes: 1
• Idioma: Inglés