handbook on systemic risk

H A N D B O O K O N S Y S T E M I C R I S K

The Handbook on Systemic Risk, written by experts in the field, providesresearchers with an introduction to the multi-faceted aspects of systemic risks fac-ing the global financial markets. The Handbook explores the multi-disciplinaryapproaches to analyzing this risk, the data requirements for further research, andthe recommendations being made to avert financial crisis. The Handbook isdesigned to encourage new researchers to investigate a topic with immense soci-etal implications as well as to provide, for those already actively involved withintheir own academic discipline, an introduction to the research being undertaken inother disciplines. Each chapter in the Handbook will provide researchers with asuperior introduction to the field and with references to more advanced researcharticles. It is the hope of the editors that this Handbook will stimulate greater inter-disciplinary academic research on the critically important topic of systemic risk inthe global financial markets.

JEAN-PIERRE FOUQUE is Professor and Director of the Center for Research inFinancial Mathematics and Statistics at the University of California, Santa Barbara.

JOSEPH A. LANGSAM spent 25 years at Morgan Stanley, where he collaboratedwith academic experts in mathematics and finance to develop and promote thederivative valuation and risk management models that are necessary for modernfinance. Joseph Langsam is a Policy Fellow in the Center for Financial Policy,Robert H. Smith School of Business, University of Maryland, College Park.

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Cambridge University Press978-1-107-02343-7 - Handbook on Systemic RiskEdited by Jean-Pierre Fouque and Joseph A. LangsamFrontmatterMore information

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HANDBOOK ON SYSTEMIC RISK

Edited by

J E A N - P I E R R E F O U QU EUniversity of California, Santa Barbara

J O S E P H A . L A N G S A MUniversity of Maryland, College Park






C A M B R I D G E U N I V E R S I T Y P R E S S

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Contents

Contributors page xvIntroduction xx

PART I: DATA: THE PREREQUISITE FOR MANAGINGSYSTEMIC RISK 1Data for Systemic Risk 3H.V. Jagadish

1 Systemic Risk Information Requirements: Current Environment,Needs, and Approaches for Development 9Edward T. Hida II1.1 Introduction 91.2 Purpose 101.3 Overview of types of systemic risk information required 101.4 Overview of the financial landscape 141.5 Observations on the state of financial data within financial

institutions 241.6 The challenge ahead for systemic risk information collection 281.7 Paths for collection of systemic risk information 301.8 Conclusions 32Bibliography 36

2 Aligning Models and Data for Systemic Risk Analysis 37Roger M. Stein2.1 Introduction 372.2 Data aggregation and statistical inference: at what level of

detail should data be collected? 422.3 Data linkage 45

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2.4 Aligning data and models 512.5 A brief comment on confidentiality, anonymization and the

role of consortia 562.6 Conclusion 60Bibliography 62

3 Applying FpML 66Andrew Jacobs and Marc Gratacos3.1 Introduction 663.2 Inside FpML 723.3 Application to systemic risk 873.4 Conclusions 91Bibliography 92

4 Data Integration for Systemic Risk in the Financial System 93Arnon Rosenthal and Len Seligman4.1 The systemic risk data integration challenge 934.2 Data integration task model 1004.3 Standards for data exchange 1024.4 Tools for reconciling heterogeneity 1104.5 Research questions 1154.6 Conclusions 120Bibliography 121

5 Semantics in Systemic Risk Management 123Mike Atkin and Mike Bennett5.1 Dealing with semantics 1255.2 Creating an ontology 1325.3 Semantic technology applications 1425.4 Operational data 1445.5 Summary 1455.6 The financial industry business ontology 1475.7 FIBO and systemic risk 153Bibliography 158

PART II: STATISTICS AND SYSTEMIC RISK 161Statistics and Systemic Risk 163John Liechty






Contents vii

6 Statistical Assessments of Systemic Risk Measures 165Carole Bernard, Eike Christian Brechmann and Claudia Czado6.1 Introduction and background on systemic risk 1656.2 CoVaR 1676.3 Marginal Expected Shortfall 1706.4 Other tail dependence measures 1736.5 Conclusions & alternative systemic measure 176Bibliography 178

7 Regime Switching Models and Risk Measurement Tools 180John Liechty7.1 Introduction 1817.2 Using regime shifting models with historical data 1827.3 Using forward-looking data 1877.4 Conclusions 188Bibliography 189

PART III: MEASURING AND REGULATING SYSTEMICRISK 191Measuring and Regulating Systemic Risk 193Viral V. Acharya

8 Measuring Systemic Risk 196Viral V. Acharya, Christian Brownlees, Robert Engle,Farhang Farazmand, and Matthew Richardson8.1 The Dodd–Frank Wall Street reform and Consumer Protec-

tion Act 1988.2 Evaluation of the Dodd–Frank Act 2038.3 NYU Stern systemic risk rankings 208Bibliography 224

9 Taxing Systemic Risk 226Viral V. Acharya, Lasse Pedersen, Thomas Philippon, andMatthew Richardson9.1 Systemic risk and the financial crisis of 2007 to 2009 2269.2 Regulating systemic risk 2299.3 The Dodd–Frank Wall Street reforms and Consumer Protec-

tion Act of 2010 2359.4 A tax on systemic risk 2419.5 Summary 244Bibliography 244






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10 Analyzing Systemic Risk of the European Banking Sector 247Viral V. Acharya and Sascha Steffen10.1 Introduction 24710.2 Methodology – measuring systemic risk 24910.3 Data and summary statistics 25110.4 Measuring systemic risk of European banks 25410.5 Responses to the financial crisis of 2007–2009 26610.6 After the crisis is before the crisis – the sovereign debt crisis

of 2010 27010.7 Conclusion 278Bibliography 281

PART IV: NETWORKS 283Networks: Introduction 285Rama Cont

11 Network Models and Systemic Risk Assessment 287Helmut Elsinger, Alfred Lehar and Martin Summer11.1 Introduction 28711.2 A network model of interbank exposures and contagion risk 28811.3 Estimating network exposures 29111.4 Creating loss scenarios 29411.5 Clearing in the interbank market 29711.6 Empirical findings 29911.7 Extensions 302Bibliography 303

12 Strategic Interactions on Financial Networks for the Analysis ofSystemic Risk 306Ethan Cohen-Cole, Andrei Kirilenko and Eleonora Patacchini12.1 Financial networks and systemic risk 30612.2 Diffusion-like processes over networks 30912.3 An empirical application: the CME market 31612.4 Conclusions and policy implications 323Bibliography 324

13 Network Structure and Systemic Risk in Banking Systems 327Rama Cont, Amal Moussa and Edson B. Santos13.1 Introduction 32713.2 The network structure of banking systems 33313.3 Systemic risk and default contagion 345






Contents ix

13.4 Is default contagion a significant source of systemic risk? 35113.5 What makes an institution systemically important? 35513.6 Does one size fit all? The case for targeted capital requirements 361Bibliography 365

PART V: SYSTEMIC RISK AND MATHEMATICAL FINANCE 369Systemic Risk and Mathematical Finance 371Ronnie Sircar

14 Firms, Banks and Households 372L.C.G. Rogers and P. Zaczkowski14.1 Introduction 37214.2 Modelling assumptions 37414.3 Summary 38514.4 Examples 38714.5 Numerical results 390Bibliography 400

15 An Agent-Based Computational Model for Bank Formation andInterbank Networks 401Matheus R. Grasselli and Omneia R. H. Ismail15.1 Introduction 40115.2 The pre-banking society 40415.3 Introducing banks 41015.4 Interbank market 41615.5 Communities of correlated preferences 42315.6 Conclusions and further directions 428Bibliography 430

16 Diversification in Financial Networks may Increase Systemic Risk 432Josselin Garnier, George Papanicolaou and Tzu-Wei Yang16.1 Introduction 43216.2 A bistable mean-field model for systemic risk 43316.3 Review of some models for systemic risk 43916.4 Summary and conclusion 442Bibliography 442

17 Systemic Risk Illustrated 444Jean-Pierre Fouque and Li-Hsien Sun17.1 Introduction 44417.2 Stability illustrated by simulations 44617.3 Mean-field limit 449






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17.4 Large deviations and systemic risk 45017.5 Conclusion 451Bibliography 452

18 Financial Crisis and Contagion: A Dynamical Systems Approach 453Youngna Choi and Raphael Douady18.1 Introduction 45418.2 Assumptions on an economy 45518.3 A nonlinear dynamic programming model 45818.4 Market instability indicator 46718.5 Financial crisis 46818.6 Case studies and applications 47318.7 Conclusion and further reading 477Bibliography 478

PART VI: COUNTERPARTY RISK AND SYSTEMIC RISK 481Introduction 483Kay GieseckeBibliography 484

19 Pricing and Mitigation of Counterparty Credit Exposures 485Agostino Capponi19.1 Introduction 48519.2 Notation and definitions 48819.3 Risk-neutral pricing of counterparty risk 49119.4 Application to interest-rate and credit default swaps 49619.5 Future trends in counterparty risk 50619.6 Conclusions 508Bibliography 509

20 Counterparty Contagion in Context: Contributions to SystemicRisk 512Jeremy Staum20.1 Introduction 51220.2 Contagion 51320.3 Models of counterparty contagion 51620.4 Other phenomena in models of systemic risk 52320.5 Counterparty contagion and systemic risk 52920.6 Systemic risk attribution 53420.7 Avenues for progress 537Bibliography 540






Contents xi

PART VII: ALGORITHMIC TRADING 545Algorithmic Trading 547Alexander Schied

21 Market Microstructure Knowledge Needed for Controlling anIntra-Day Trading Process 549Charles-Albert Lehalle21.1 Market microstructure modeling and payoff understanding

are key elements of quantitative trading 54921.2 From market design to market microstructure: practical

examples 55221.3 Forward and backward components of the price formation

process 56221.4 From statistically optimal trade scheduling to microscopic

optimization of order flows 56421.5 Perspectives and future work 575Bibliography 576

22 Dynamical Models of Market Impact and Algorithms for OrderExecution 579Jim Gatheral and Alexander Schied22.1 Introduction 57922.2 Price impact and price manipulation 58022.3 Temporary and permanent price impact 58422.4 Transient price impact 58822.5 Further extensions 596Bibliography 599

PART VIII: BEHAVIORAL FINANCE:THE PSYCHOLOGICAL DIMENSION OF SYSTEMIC RISK 603Behavioral Finance: Introduction 605Hersh ShefrinBibliography 621

23 Fear, Greed, and Financial Crises: A Cognitive NeurosciencesPerspective 622Andrew Lo23.1 Introduction 62223.2 A brief history of the brain 62523.3 Fear 62723.4 Greed 632






xii Contents

23.5 Risk 63623.6 Rationality 64023.7 Sentience 64523.8 Interactions 64823.9 Policy implications 65223.10 Conclusion 655Bibliography 659

24 Bubbles, Crises, and Heterogeneous Beliefs 663Wei Xiong24.1 Historical bubbles 66424.2 Limits of arbitrage 67424.3 Heterogeneous beliefs 67724.4 Resale option theory of bubbles 68224.5 Credit cycles 69224.6 General equilibrium models with heterogeneous beliefs 69624.7 Welfare analysis with distorted beliefs 70124.8 Summary and future directions 704Bibliography 706

25 Systemic Risk and Sentiment 714Giovanni Barone-Adesi, Loriano Mancini and Hersh Shefrin25.1 Introduction 71425.2 Behavioral asset pricing theory and sentiment 71925.3 Estimating the empirical SDF 72325.4 Sentiment and the financial crisis 72625.5 External measures of sentiment 73425.6 Sentiment, systemic risk and leverage 73625.7 Conclusion 739

PART IX: REGULATION 743Regulation: Introduction 745Gary Stern and Ron J. Feldman

26 The New Financial Stability Framework in Europe 748Carsten Detken and Per Nymand-Andersen26.1 The new European approach to systemic risk 74926.2 The new European systemic risk framework 75326.3 The ECB approach to systemic risk 75526.4 Global markets require a global approach to risk. 76626.5 Conclusion 768Bibliography 771






Contents xiii

27 Sector-Level Financial Networks and MacroprudentialRisk Analysis in the Euro Area 775Olli Castren and Ilja Kristian Kavonius27.1 Introduction 77527.2 Description of the data 77727.3 The network of balance sheet exposures for the aggregate

Euro area financial system 77727.4 Derivation of the risk-based balance sheets 78127.5 Propagation of shocks in the risk-based financial network 78627.6 Concluding remarks 788Bibliography 789

28 Systemic Risk Early Warning System: A Micro-Macro PrudentialSynthesis 791Mikhail V. Oet, Ryan Eiben, Timothy Bianco, Dieter Gramlich,Stephen J. Ong, and Jing Wang28.1 Introduction 79228.2 EWS elements 79628.3 Risk model and results 80128.4 Discussion and implications 81228.5 Conclusions and future work 828Bibliography 843

PART X: COMPUTATIONAL ISSUES AND REQUIREMENTS 847Computational Issues and Requirements: Introduction 849Richard Byrne

29 Enabling Data Analysis for Addressing Systemic Risk 852Eric Hughes, Arnon Rosenthal, Charles Worrell29.1 Challenges in analyzing systemic risk 85229.2 Approaches that support analysis 85329.3 Analysis approaches 86229.4 Discussion and future research 866Bibliography 868

30 Operational Considerations in an Analytic Environment forSystemic Risk 869Charles Worrell, Samar Guharay, Matt McMahon, Len Seligman, andRajani Shenoy30.1 Introduction 86930.2 Controlling the frame of reference 870






xiv Contents

30.3 Managing the data environment 87130.4 Model hosting and execution environment 87430.5 Comparison and measurement across disparate models 87530.6 Aggregation of risk components 87730.7 From analysis to decisions 879Bibliography 880

31 Requirements for Systemic Risk Management in the FinancialSector 882Alan J. King, Donna N. Dillenberger, Aviv Orani, Francis N. Parr, andGong Su31.1 Introduction 88231.2 History 88431.3 Modern mortgage market 88431.4 Network and counterparty risk 89031.5 Requirements for broad scope risk 89231.6 Integrated risk analytics 89531.7 Reference data 90131.8 Risk analytics services 90731.9 Summary 910Bibliography 911

PART XI: ACCOUNTING ISSUES 913Accounting and Systemic Risk: An Introduction 915Trevor S. HarrisBibliography 917

32 Accounting’s Role in the Reporting, Creation, and Avoidance ofSystemic Risk in Financial Institutions 918Trevor S. Harris, Robert Herz and Doron Nissim32.1 Introduction 91832.2 Some basics of accounting and financial reporting 92132.3 Accounting for systemic risk 92432.4 Accounting for different asset and liability classes 92632.5 Accounting, pro-cyclicality and systemic risk: summary

thoughts 95732.6 Single firm versus systemic risk 96132.7 Concluding remarks 962Bibliography 963






Contributors

Viral V. Acharya New York University, Stern School of Business, 44 West 4th St,New York, NY 10012, USA. [email protected]

Mike Atkin EDM Council, 10101 East Bexhill Drive, Kensington, MD 20895,USA. [email protected]

Mike Bennett EDM Council, 43 Queen of Denmark Court, London SE16 7TB,UK. [email protected]

Giovanni Barone-Adesi Swiss Financial Institute, Faculty of Economics,University of Lugano, Via Buffi 13, CH-6900 Lugano, [email protected]

Carole Bernard Department of Statistics and Actuarial Science University ofWaterloo, Waterloo, Ontario, N2L 3G1, Canada. [email protected]

Timothy Bianco Federal Reserve Bank of Cleveland, P.O. Box 6387, Cleveland,OH 44101-1387, USA. [email protected]

Eike Christian Brechmann Technische Universitat Munchen, ZentrumMathematik, Lehrstuhl fur Mathematische Statistik, Parkring 13, 85748Garching-Hochbruck, Germany. [email protected]

Christian Brownlees Department of Economics and Business, Pompeu FabraUniversity, Ramon Trias Fargas 25–27, 08005, Barcelona, [email protected]

Richard Byrne The MITRE Corp, 7515 Colshire Drive, McLean, VA 22102, [email protected]

Agostino Capponi School of Industrial Engineering, Purdue University, WestLafayette, IN 47906, USA. [email protected]

Olli Castren European Central Bank (ECB), Kaiserstrasse 29, 60311, Frankfurtam Main, Germany. [email protected]

Youngna Choi Department of Mathematical Sciences, Montclair State University,Montclair, NJ 07043, USA. [email protected]

xv






xvi Contributors

Ethan Cohen-Cole Robert H. Smith School of Business, 4420 Van Munching Hall,University of Maryland, College Park, MD 20742, [email protected]

Rama Cont Department of Mathematics, Imperial College London, London SW72AZ, UK. [email protected]

Claudia Czado Technische Universitat Munchen, Zentrum Mathematik, Lehrstuhlfur Mathematische Statistik, Parkring 13, 85748 Garching-Hochbruck,Germany. [email protected]

Carsten Detken European Central Bank (ECB), Kaiserstrasse 29, 60311,Frankfurt am Main, [email protected]

Donna N. Dillenberger IBM Research, Thomas J. Watson Research Center,Yorktown Heights, NY 10598, USA. [email protected]

Raphael Douady Centre d’Economie de la Sorbonne, CNRS UMR 8174,Universite Paris 1, Paris, France; and Research Director, [email protected]

Ryan Eiben Indiana University, Department of Economics, Wylie Hall 105, 100 S.Woodlawn Ave., Bloomington, IN 47405, USA. [email protected]

Robert Engle New York University, Stern School of Business, 44 West 4th St, NewYork, NY 10012, USA. [email protected]

Helmut Elsinger Economic Studies Division, Oesterreichische Nationalbank,Otto-Wagner-Platz 3, A-1011, Wien, Austria. [email protected]

Farhang Farazmand Department of Finance, Leonard N. Stern School of Business,New York University, New York, NY 10012, [email protected]

Ron J. Feldman Federal Reserve Bank of Minneapolis, 90 Hennepin Avenue,Minneapolis, MN 55401, USA. [email protected]

Jean-Pierre Fouque Department of Statistics & Applied Probability, University ofCalifornia, Santa Barbara, CA 93106-3110,USA. [email protected]

Josselin Garnier Laboratoire de Probabilites et Modeles Aleatoires & LaboratoireJacques-Louis Lions, Universite Paris VII, Paris, [email protected]

Jim Gatheral Baruch College, CUNY, 55 Lexington Ave, New York, NY 10010,USA. [email protected]

Kay Giesecke Huang Engineering Center, Stanford University, Stanford, CA94305, USA. [email protected]

Dieter Gramlich Baden-Wuerttemberg Cooperative State University, Departmentof Banking, Marienstr. 20, 89518 Heidenheim, Germany; and Cleveland StateUniversity, Graduate School of Business. [email protected]






Contributors xvii

Matheus R. Grasselli Department of Mathematics & Statistics, McMasterUniversity, Hamilton, Ontario L8S 4K1, [email protected]

Marc Gratacos Tradeheader, S.L. Carrer, Sant Pere 8, Baixos Interior, 08911Badalona, Spain. [email protected]

Samar Guharay The MITRE Corporation, 7515 Colshire Drive, McLean, VA22102, [email protected]

Trevor S. Harris Columbia Business School, Columbia University, 3022Broadway, Room 608, New York, NY 10027, [email protected]

Robert Herz Columbia Business School, Columbia University, New York, NY10027, USA. [email protected]

Edward T. Hida II Partner, Global Leader – Risk & Capital Management, Deloitte& Touche LLP, One World Financial Center, New York, NY 10281, [email protected]

Eric Hughes The MITRE Corp, M/S K302, 202 Burlington Rd., Bedford, MA01730, USA. [email protected]

Omneia R. H. Ismail Accounting, Law, Finance and Economics Department,EDHEC Business School, 1 George Street, #07-02 Singapore [email protected]

Andrew Jacobs HandCoded Software, 27 Ryhill Way, Lower Earley, Reading,Berkshire RG6 4AZ, UK. [email protected]

H.V. Jagadish Electrical Engineering and Computer Science Department,University of Michigan, Ann Arbor, MI 48109-2121, [email protected]

Ilja Kristian Kavonius European Central Bank (ECB), Kaiserstrasse 29, 60311,Frankfurt am Main, Germany. Ilja [email protected]

Alan J. King IBM Research, Thomas J. Watson Research Center, YorktownHeights, NY 10598, USA. [email protected]

Andrei Kirilenko Commodity Futures Trading Commission, 1155 21st StreetN.W., Washington, DC 20581, USA. [email protected]

Joe Langsam CFP Policy Fellow, Robert H. Smith School of Business, Universityof Maryland, Van Munching Hall, College Park, MD 20742, [email protected]

Charles-Albert Lehalle Senior Research Manager, Capital Fund Management,23/25, rue de l’Universite, 75007 Paris, [email protected]

Alfred Lehar Haskayne School of Business, University of Calgary, 2500University Drive NW, Calgary, Alberta, T2N 1N4, [email protected]






xviii Contributors

John Liechty College of Business, Pennsylvania State University, University Park,PA 16803, USA. [email protected]

Andrew W. LoMIT Sloan School of Management, 100 Main Street, Cambridge,MA 02142, USA; and Chief Investment Strategist, AlphaSimplex Group, [email protected]

Loriano Mancini Swiss Finance Institute at EPFL, Quartier UNIL-Dorigny,Extranef 217, CH-1015 Lausanne, [email protected]

Matt McMahon The MITRE Corporation, 7515 Colshire Drive, McLean, VA22102, USA. [email protected]

Amal Moussa Department of Statistics, Columbia University, New York, NY10027, USA. [email protected]

Doron Nissim Columbia Business School, Columbia University, New York, NY10027, USA. [email protected]

Per Nymand-Andersen European Central Bank (ECB), Kaiserstrasse 29, 60311,Frankfurt am Main, Germany. [email protected]

Mikhail V. Oet Federal Reserve Bank of Cleveland, P.O. Box 6387, Cleveland,OH 44101-1387, USA. [email protected]

Stephen J. Ong Federal Reserve Bank of Cleveland, P.O. Box 6387, Cleveland,OH 44101-1387, USA. [email protected]

Aviv Orani IBM Research, Thomas J. Watson Research Center, Yorktown Heights,NY 10598, USA. [email protected]

George Papanicolaou Mathematics Department, Stanford University, CA 94305,USA. [email protected]

Francis N. Parr IBM Research, Thomas J. Watson Research Center, YorktownHeights, NY 10598, USA. [email protected]

Eleonora Patacchini Department of Economic and Social Analysis, La SapienzaUniversity of Rome, P. le A. Moro 5, 00185 Roma, [email protected]

Lasse Pedersen New York University, Stern School of Business, 44 West 4th St,New York, NY 10012, USA. [email protected]

Thomas Philippon New York University, Stern School of Business, 44 West 4th St,New York, NY 10012, USA. [email protected]

Matthew Richardson New York University, Stern School of Business, 44 West 4thSt, New York, NY 10012, USA. [email protected]

L.C.G. Rogers Statistical Laboratory, University of Cambridge, WilberforceRoad, Cambridge CB3 0WB, UK. [email protected]

Arnon Rosenthal The MITRE Corporation, M/S K302, 202 Burlington Rd.,Bedford, MA 01730, USA. [email protected]






Contributors xix

Edson B. Santos Banco Central do Brasil, P.O. Box 08670, SBS Quadra 3 Bloco B– Edificio-Sede, Brasilia, DF 70074–900, [email protected]

Alexander Schied Department of Mathematics, University of Mannheim, 68131Mannheim, Germany. [email protected]

Len Seligman The MITRE Corporation, 7515 Colshire Drive, McLean, VA 22102USA. [email protected]

Hersh Shefrin Leavey School of Business, Santa Clara University, Santa Clara,CA 95053, USA. [email protected]

Rajani Shenoy The MITRE Corporation, 7515 Colshire Drive, McLean, VA22102, USA. [email protected]

Ronnie Sircar ORFE Department, Princeton University, Princeton, NJ 08544,USA. [email protected]

Jeremy Staum Department of Industrial Engineering and Management Sciences,Northwestern University, 2145 Sheridan Road, Evanston, IL 60208-3119, [email protected]

Sascha Steffen ESMT European School of Management and Technology,Schlossplatz 1, 10178 Berlin, Germany. [email protected]

Roger M. Stein Moody’s Research Labs, 7 World Trade Center, New York, NY10007, USA. [email protected]

Gary Stern Stern Partners LLC, 1727 Humboldt Ave S, Minneapolis, MN 55403,USA. [email protected]

Gong Su IBM Research, Thomas J. Watson Research Center, Yorktown Heights,NY 10598, USA. [email protected]

Martin Summer Economic Studies Division, Oesterreichische Nationalbank,Otto-Wagner-Platz 3, A-1011, Wien, Austria. [email protected]

Li-Hsien Sun Department of Statistics & Applied Probability, University ofCalifornia, Santa Barbara, CA 93106-3110, USA. [email protected]

Jing Wang Cleveland State University, Monte Ahuja College of Business, FinanceDepartment, 1555 Saddle Brook Ln., Westlake, OH 44145, [email protected]

Charles Worrell The MITRE Corporation, 7515 Colshire Drive, McLean, VA22102, USA. [email protected]

Wei Xiong Department of Economics and Bendheim Center for Finance,Princeton University, Princeton, NJ 08540, [email protected]

Tzu-Wei Yang Institute for Computational and Mathematical Engineering(ICME), Stanford University, CA 94305, USA. [email protected]

P. Zaczkowski Statistical Laboratory, University of Cambridge, Wilberforce Road,Cambridge CB3 0WB, UK. [email protected]






IntroductionJean-Pierre Fouque and Joe Langsam

The intent in producing this Handbook is to familiarize researchers and policymakers with the many aspects of systemic risk. The Handbook contains some 32chapters prepared by experts from a multitude of academic and professional back-grounds. What will become clear to the reader are both the complexity of systemicrisk and the necessity for bringing together multiple academic disciplines to bet-ter understand systemic risk and for designing policies to mitigate the impact ofa systemic crisis upon the global economy. Recent history has shown us not onlythe enormous cost of a systemic crisis but also how woefully unprepared and ill-equipped governments and private markets have been to prevent a systemic crisisor minimize its impact.

The first issue in addressing systemic risk is to define the system. Despite thelarge volume of recent articles on the topic of systemic risk, there has been littleattention paid to what is endogenous to the system and events that are external.The financial system is a system in which humans, their emotions, politics and re-sponses to incentives play a critical role. The topology of the system is extremelycomplex, dynamic, and not well studied. The system does not recognize nationalboundaries. Events in the US have impacted the markets across the globe. Euro-pean debt crisis is impacting the Americas, Africa, and Asia. The common use ofthe terms “Wall Street” and “Main Street” seems to suggest that the two are separ-able. The contribution of the consumer to systemic risk, as evidenced by the inter-play of the subprime borrowers and massive bank losses, strongly demonstratesthat the “Real Economy” and the “Financial Markets” are not separable systems.Wall Street and Main Street and their international equivalents intersect numeroustimes. Legislation, produced to address market disruptions, in turn, changes the be-havior of market participants. In a similar vein, accounting rules are proposed inresponse to events and, in turn, change behavior. This is a system that is continu-ally evolving. It is a system that has proven to be robust. The ongoing crisis haspainfully demonstrated that it is not so robust that one can ignore systemic risks.

xx






Introduction xxi

What are the important components of the financial system? It is beyond thescope of this book, or of research yet undertaken, to fully answer that question.The system continues to expand in scope and new classes emerge. Ten years ago,one would have considered mortgage servicing to be an insignificant and benigncomponent of the system. Clearly, that is not the case today. The academic commu-nity has an ever increasing important role. The theories and applications developedby academics in the fields of finance, mathematics, economics, statistics, computerscience and several other disciplines have been applied, sometimes incorrectly, tocreate products, create trading strategies, and motivate laws and regulations. Therole of technology, once considered a back office cost center activity by the bankingcommunity, has become an important profit area through the emergence of mediumand high frequency trading strategies.

Research into financial markets systemic risk is still in the very early stages.There is no agreed upon definition of systemic risk. There does not exist a formaldefinition of a systemic crisis adequate to officially identify when a crisis beganand ended. A temporary working definition for systemic risk might be:

Systemic Risk is the risk of a disruption of the market’s ability to facilitate the flowsof capital that results in the reduction in the growth of the global GDP.

This definition needs refinement but captures the essential characteristics of sys-temic risk. Systemic risk refers to the risk that the ability of the system to functionas intended is seriously degraded. It does not refer to the risk that a componentor several components fail unless such failure jeopardizes the integrity of the sys-tem. Models introduced in the Mathematical Finance section of this Handbookdemonstrate how the inter-connectedness of the system can pose the potential fora systemic crisis. Systemic risk does not refer to losses in the financial marketsunless such losses impact the financial system to the extent that there is impact oneconomic growth. Actions that reduce the default probability of each individualsystemically important institution can have the result of increasing the probabilityof a system wide failure.

The financial system is not deterministic. It is subjected to random shocks andevolves in response to these shocks. The financial system is exposed to manysources of risk; some are endogenous reflecting the structure of the system whileothers are external. External shocks include potential attacks upon the system bythose opposed to a capitalist system as well as natural disasters. Market participantsnot only respond to regulatory policies, but also anticipate policies and regulatoryactions and develop new activities in response to these anticipations.

Systemic risk research, similar to medical research, has a dual focus: preventiveand curative. Policies and actions as well as data requirements required to preventsystemic crisis differ from those needed to recover from a crisis. Mitigating actions






xxii Introduction

have powerful impact upon the financial markets. Actions taken when not appro-priate or that do not address current problematic factors can have strong adverseimpact. A Fed easing in the midst of a crisis when credit is extremely tight and eco-nomic growth is waning has a far different impact than the same easing in periodswhen systemic risk attributable to excessive leverage is increasing.

This Handbook explores the roles of several of the important components of thefinancial system and explores how these areas relate to systemic risk. It is intendedto be an introduction to the issues surrounding system risk. It is designed for re-searchers and policy makers. It is not intended to be complete, nor can it be. Muchresearch must be undertaken before that could be done. TheHandbook is organizedinto eleven Parts in the order below:

I. Data: The Prerequisite for Managing Systemic RiskII. Statistics and Systemic Risk

III. Measuring and Regulating Systemic RiskIV. NetworksV. Systemic Risk and Mathematical Finance

VI. Counterparty Risk and Systemic RiskVII. Algorithmic Trading

VIII. Behavioral Finance: The Psychological Dimension Of Systemic RiskIX. RegulationX. Computational Issues and Requirements

XI. Accounting Issues

The reader will recognize that there is significant overlap in the topics covered inthese chapters. Data issues are addressed in both the data chapter and the computa-tional chapter. Mathematical modeling is an important feature in multiple chapters.Economics, finance, and behavioral finance are addressed in several chapters. Thisoverlap reflects both the importance of the topics and the multiple approaches takenby different academic disciplines.

We begin the Handbook with a focus on data. Data is a critical component ofall issues related to systemic risk. The global financial system constantly producesmyriad amounts of data. This data, all too often, is inaccurate, chaotically reported,unreadable by electronic systems, and inaccessible to researchers, policy makers,investors, and regulators. Hank Paulson’s book On The Brink, makes it clear thatthe critical regulators and those involved in possible bailouts had vastly insufficientinformation regarding the size and nature of both Lehman Brothers and AIG. Theabsence of accessible well-structured records of ownership and transferences ofmortgages has further complicated the housing crisis.

Data released into the markets will change the behavior of the markets. Systems






Introduction xxiii

will need to be developed and upgraded to report trading data using a standard-ized format. This will be expensive. Not every section of the market benefits fromhaving greater transparency in the markets. New products will be engineered andtrading venues may be changed to avoid reporting the data that new legislationmight require. Some, data including regulatory findings regarding the credit wor-thiness of a bank, while not suggesting imminent credit unworthiness, could causebank runs. The questions of what to release to the public or to researchers and whento release it are important topics for both researchers and policy makers.

H.V. Jagadish, the editor of Part I, on Data, states at the start of his introductionthat systemic risk involves dependencies between multiple entities in the financialsystem. It follows that evaluation of systemic risk requires the integration of data.The first chapter, by Edward Hida II, reviews the financial information requiredfor systemic risk modeling and the multiplicity of places (and databases) in whichvarious components may be found. This review sets the stage for later chapters thatdeal with data integration, pulling together information obtained from distributedsources in support of systemic risk assessment. The second chapter, by Roger Stein,has extensive discussion of the ways in which systemic modeling objectives beardirectly on the priorities and approaches for data collection or, conversely, howdecisions about data strategies act to constrain the types of questions that mod-els can answer. The Financial products Markup Language (FpML) is a languagefor expressing financial contracts. In the third chapter, Andrew Jacobs and MarcGratacos present a brief overview of FpML and then describe how it could providea basis for computer-driven analysis of conditionally dependent chains of poten-tial events. Arnon Rosenthal and Len Seligman, in the fourth chapter, discuss thedaunting task of integrating massive data and then organizing and distributing thedata in functionally useful form. The authors point out the advantages of standardsand the need to continue developing them while warning the reader that it is un-realistic to expect a complete set of same. Rosenthal and Seligman emphasize theneed to develop data techniques, in the absence of complete standards. In the finalchapter, Mike Atkin and Mike Bennett of the EDM Council describe the promiseof semantic web technologies to integrate financial data for the purposes identifiedin preceding chapters. They also discuss the naming standards and ontologies re-quired to get started on this semantic web based integration. The Enterprise DataManagement Council is a non-profit trade association of the financial industry fo-cused on the representation, modeling, and integration of financial data.

Data is not information. Statistics, analysis, theory, and analytics are required toextract information from data. The second Part, Statistics and Systemic Risk, editedby John Liechty, introduces statistical approaches to measuring systemic risk. Thefirst of the two chapters is written by Carole Bernard, Elke Christian Brechmannand Claudia Czado. This chapter introduces the reader to several measures of trad-






xxiv Introduction

ing and systemic risk. Some of these measures have been implemented with theresults available on the web. Being able to measure and monitor systemic risk iscritically important for macro-prudential risk management and prudent regulation.There is additional discussion about many of these measures in Part III,Measuringand Regulating Systemic Risk. The second chapter, written by John Liechty, intro-duces the reader to regime shifting models, a modeling approach that addresses thestructural difference of market behavior in normal markets from those in crisis.

Part III, edited by Viral Acharya, discusses measures of systemic risk attributableto banks. The chapter by Viral Acharya, Christian Brownlees, Robert Engle, Far-hang Farazmand and Matthew Richardson presents a method for using market dataand regulatory stress test to compute such a measure. The chapter shows how thisapproach fits into the requirements of the Dodd–Frank Act to identify systemi-cally important institutions (SIFIs). The second chapter written by Viral Acharya,Lasse Pedersen, Thomas Philippon, and Matthew Richardson proposes a methodfor identifying a shortfall in capital by a SIFI. The third, and final, chapter of thisPart, written by Viral Acharya and Sascha Steffen, examines the international as-pects of measuring systemic risk extending the analysis to Europe, Australia, andAsia. This chapter presents evidence on the consistency of performance of certainmeasures across these geographies.Networks, Part IV, edited by Rama Cont, introduces network models as a method-

ology for understanding and modeling the relationships within the financial system.The first chapter, by Helmut Elsinger, Alfred Lehar and Martin Summer, providesa detailed study of simulation methods for insolvency contagion. The chapter byEthan Cohen-Cole, Andrei Kirilenko and Eleonora Patacchini discusses the useof behavioral-based models in the financial markets context. They define a newmeasure of systemic risk and they suggest policy implications and areas for fu-ture research. The final chapter, by Rama Cont, Amal Moussa and Edson Santos,presents a quantitative methodology for analyzing the potential for contagion andsystemic risk in networks of interlinked financial institutions. The authors illustratetheir model with data from the Brazilian banking system. They present a strong ar-gument that capital requirements should depend on exposures rather than balancesheet size.

Part V,Mathematical Finance, edited by Ronnie Sircar, provides the reader witha critically important introduction to the mathematical models of the economic andfinancial dynamics of the financial system. The chapters in this part provide a sur-vey of selected mathematical models with a focus on those used in finance whilealso including a view of several models used in other fields. The chapter by ChrisRogers and Pawel Zaczkowski utilizes an equilibrium framework to model howthe financial markets affect the real economy. Matheus Grasselli and Omneia Is-mail, in their chapter, introduce agent-based models to better understand bank runs






Introduction xxv

and the motivation for the creation of interbank markets. The chapter by JosselinGarnier, George Papanicolaou, and Tzu-Wei Yang, and that by Jean-Pierre Fouqueand Li-Hsien Sun present models relying on a mean-field model of diffusions todemonstrate that agent cooperation, while reducing the probabilities of default forthe individual agents, can lead to increased probability of systemic failure. Thisapproach enables one to mathematically analyze highly complex interactions andmodel systemic risk as large deviations from a stable state. Youngna Choi andRaphael Douady use classical perturbation theory of dynamical systems to providea measure of instability of the global financial market. They utilize this model toinvestigate the effects of certain regulatory policies.Counterparty Risk and Systemic Risk, Part VI, is edited by Kay Giesecke and

investigates systemic risk issues arising from counterparty risk. The chapter byAgostino Capponi describes the mechanics of counterparty risk from both the pric-ing and risk management perspectives. It contains a discussion of counterparty riskproblems of active research interests including the modeling of liquidity curves tocapture the funding cost incurred when computing Credit Valuation Adjustment(CVA) and the systemic risk that could be attributed to CVA. Next, Jeremy Staumillustrates the importance of understanding networks. He surveys models of coun-terparty contagion through the payments system, through cross-holdings of debtand equity, and through derivatives exposures.

There are two chapters in Part VII, Algorithmic Trading, edited by AlexanderSchied. The first, by Charles-Albert Lehalle investigates relationships betweenmarket design and market microstructure using examples from Europe and theUSA. Key events including the May 6, 2011 “flash crash” are modeled and com-mented. In the second chapter, Jim Gatheral and Alexander Schied provide anoverview of several order execution algorithms with extensions to incorporate darkpools. They present models that describe the empirically observed transience ofprice impact and optimal trading strategies associated with these models.

Part VIII, Behavioral Finance: The Psychological Dimension of Systemic Risk,edited by Hersh Shefrin, introduces a topic that is critically important for under-standing systemic risk in the financial markets. The Part is comprised of three chap-ters. In the first, Andrew Lo reviews both the basic neuroscience of financial de-cisions and the legal and regulatory infrastructure of the financial industry in lightof this research. He then discusses the implications for financial crisis, regulatoryreform, and systemic risk management. The chapter by Wei Xiong reviews a set ofempirical and theoretical work that provides a coherent framework of bubbles anddebt crisis based on agents heterogeneous beliefs. Giovanni Barone-Adesi, LorianoMancini, and Hersh Shefrin examine, in their chapter, crisis events between 2002and 2009 from three interrelated perspectives: marginal expected shortfall (MES)which utilizes publically available data to construct a measure of an individual fi-






xxvi Introduction

nancial firm’s contribution to systemic risk; behavioral theory incorporating theconcept of sentiment; and asset pricing theory.

The regulatory community is charged with supervising the financial markets.Macro prudential supervision is intended to protect the public from systemic cri-sis. The regulatory environment is fractured not only by geopolitical structures butalso within political units. The United States has several regulatory agencies oftenwith overlapping responsibilities. While regulators may examine almost every ac-tivity of a bank, they have limited authority to look into the activities of the shadowbanking system. Regulations intended to protect the public may have unintendedconsequences that could increase systemic risk. “Regulatory arbitrage” is a well-established practice. It should be well recognized that market participants respondto regulatory actions that are considered to be constraints on their ability to makea profit. Understanding how the markets will evolve in response to regulatory re-quirements is a critically important research topic.

Part IX, Regulation, edited by Gary Stern, contains three chapters. The first, byCarsten Detken and Per Nymand-Andersen, presents a conceptual framework formaintaining system stability. The chapter also describes the new European super-visory architecture and compares it to the US structure. The second chapter, byOlli Castren and Ilja Kristian Kavonius, uses Euro flow of funds data to construct anetwork of bilateral balance sheet exposures and then shows how local shocks canpropagate through the network and result in systemic shocks. They conclude thathigh financial leverage and high asset volatility increase a sector’s vulnerability toshocks and contagions. The third chapter, by Mikhail V. Oet, Ryan Eiben, TimothyBianco, Dieter Gramlich, Stephen J. Ong, and Jing Wang, introduces SAFE (Sys-temic Assessment of the Financial Environment), an early warning system of sys-temic crisis developed by the Federal Reserve Bank of Cleveland. SAFE presentsto institutional supervisors a toolkit of possible supervisory actions that can be usedto diffuse the build-up of systemic risk in the markets.

Discussions of systemic risk often overlook the importance of technology. Thefinancial system is heavily reliant upon computers and the internet. Computers andthe systems through which the computers communicate with each other are used inevery aspect of trading and risk management. The demands upon technology andthe required computational power are increasing at a rapid rate. Macro-prudentialregulatory supervision with potential requirements to acquire and analyze daily, ifnot real-time, transaction data, will require significant computational resources.

Part X, Computational Issues and Requirements, edited by Richard Byrne, ad-dress these problems. In the first chapter, Eric Hughes, Arnon Rosenthal, andCharles Worrell survey the computational approaches that may be needed to pro-vide information about systemic risk and the mitigations of this risk. They also sug-gest future avenues of research. The chapter by Charles Worrell, Samara Guharay,






Introduction xxvii

Matt McMahon, Len Seligman, and Rajani Shenoy discusses several of the manyoperational considerations relevant to managing a modeling environment for ana-lyzing systemic risk. Challenges in data management, model hosting, and data se-curity are described. Three operating models for a risk modeling forum that wouldassist decision makers in building consensus around data driven analysis are de-scribed. The third and final chapter written by Alan King, Donna Dillenberger,Aviv Orani, Francis Parr, and Gong Su describes a conceptual architecture for asystemic risk management system. The authors examine what this system must beable to accomplish and the resource requirements for such a system.

Part XI, Accounting Issues, is edited by Trevor S. Harris and covers extensiveground although it contains but one chapter. It is authored by Trevor S. Harris,Robert Herz, and Doron Nissim and explains the role, purpose and limitations ofexternal financial reporting and suggests that there are aspects of the current ac-counting system that may help provide early warnings of and help mitigate poten-tial systemic risks and others that may mask and exacerbate these risks.

The Handbook introduces the reader to several of the areas of interest for re-searchers in systemic risk. It should not be expected that for such a complex topicas systemic risk that the Handbook would be comprehensive. Notably absent arearticles addressing politics and cyber security. The events from 2008 through 2012illustrate how intertwined the health of the economy and financial markets are withpolitics. Regulators are constrained by decisions to reduce budgets or to excludecompanies from specific regulatory requirements. Modeling the financial marketsto better understand systemic risk must recognize that national and global politicalprocesses are parts of the system that are critical factors in times of systemic cri-sis. The financial system is heavily reliant upon computers and the internet. Tradedata, analytics, position data, and other confidential data is passed within a firm;trading data and trade instructions are passed between firms, exchanges, clearinghouses, and regulatory agencies; price information is made publically available orrestricted to subscribers. Almost every aspect of daily financial activity is touchedby the internet. The security of the internet and other communications systems isa source of systemic risk that has received too little attention. This is very surpris-ing given the well-publicized damage from the massive disclosures of confidentialState Department memos, given the many breaches of “secure” files by hackergroups, and given known attacks on the files of contractors to the US Defense De-partment. These attacks are suspected of being supported by governments anxiousto gain US defense secrets. Cyber warfare poses a growing threat to the finan-cial markets. A successful attempt to place sizable numbers of bogus trades couldcause investors to lose confidence in the financial markets. A successful attempt byan unfriendly country to disrupt the internet for a significant period of time coulddisrupt all market activity and cause a serious systemic crisis. Greater research is






xxviii Introduction

required to design better protective measures for the trading environment and forthe protection of government collected position and transaction data.

The absence of an accepted definition of systemic risk was acknowledged earlierin this introduction. This is not simply an abstract academic issue. Having clear def-initions is a fundamental requirement for modeling. Policy makers and regulatorsrequire coherent models of the financial markets to design policies and to antici-pate the impact of actions. Effective management of systemic risk requires manyof the same models required for micro-prudential regulation and for risk manage-ment of individual significantly important institutions. It also requires new classesof analytics and models to analyze networks and the evolution of the system tomultiple types of shocks. These models must incorporate behavioral aspects thathelp explain the transition from well behaving markets to markets with increasingsystemic risk and to markets in crisis. Remedial actions, whether for preventive orcurative purpose, impact the financial market and have the potential for doing harmas well as good. Without a well-defined definition of systemic risk and metrics formeasuring the amount and nature of the risks, it would be difficult to effectively tar-get regulatory mitigating action without running the real risk of doing more harmthan good.

This Handbook is designed to help educate policy makers of the importance ofnew research to better understand and then protect against debilitating economiccrisis in the financial markets. It is designed to encourage researchers to betterunderstand the nature of the problem. Readers of the Handbook should begin tounderstand the complexity of systemic risk. Micro-prudential regulation that ad-dresses the stability of individual financial institutions needs to be coordinatedwith macro-prudential policies that address the stability of the financial system.The modern financial market with global movement of capital, complex securitiesand computer aided trading strategies, including high speed algorithmic trading,bears little resemblance to the financial markets for which regulations and regula-tory policies were first promulgated. The models and academic theories developedfor yesterday’s financial markets are inadequate to address today’s global markets.These need to be enhanced to capture the dynamics and evolutionary relationshipsamong the participants in today’s global financial market. Understanding the na-ture of systemic risk, and developing preventive and curative tools requires well-funded multi-disciplinary research. Our hope is that this Handbook stimulates thesupport and research necessary to protect the financial markets which are essentialfor global economic growth.






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