Table of contents for Risk measures in the 21st century / edited by Giorgio Szegèo.


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CONTENTS
About the Contributors xiii
1 On the (Non)Acceptance of Innovations 1
Giorgio Szeg"o
1.1 Introduction 1
1.2 The path towards acceptance of previous
innovations 4
1.3 How to answer 5
1.4 Conclusions 6
References 6
PART I RISK MEASURES AND REGULATION 11
2 The Emperor has no Clothes: Limits to Risk
Modelling 13
J'on Dan'yelsson
2.1 Introduction 13
2.2 Risk modelling and endogenous response 15
2.3 Empirical properties of risk models 17
2.3.1 Background 18
2.3.2 Robustness of risk forecasts 18
2.3.3 Risk volatility 19
2.3.4 Model estimation horizon 22
2.3.5 Holding periods and loss horizons 23
2.3.6 Non-linear dependence 24
2.4 The concept of (regulatory) risk 25
2.4.1 Volatility 25
2.4.2 Value-at-risk 26
2.4.3 Coherent risk measures 27
2.4.4 Moral hazard - massaging VaR numbers 28
2.4.5 The regulatory 99% risk level 28
2.5 Implications for regulatory design 29
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2.6 Conclusion 30
Acknowledgements 31
Appendix A: Empirical study 31
References 32
3 Upgrading Value-at-Risk from Diagnostic Metric to Decision
Variable: A Wise Thing to Do? 33
Henk Grootveld and Winfried G. Hallerbach
3.1 Introduction 33
3.2 Preliminaries 34
3.2.1 VaR and downside risk 34
3.2.2 Downside risk portfolio selection 35
3.2.3 Incomplete risk meaure 35
3.2.4 Computational issues 36
3.3 The mean-value-at-risk portfolio selection model 36
3.3.1 Deriving the mean-VaR portfolio selection model 37
3.3.2 Distinctive properties of the mean-VaR portfolio
selection model 38
3.3.3 Solving the mean-VaR portfolio selection problem 39
3.4 The mean-value-at-risk portfolio selection model in practice 40
3.4.1 Data 40
3.4.2 Methodology 41
3.4.3 Results 43
3.5 Conclusions 47
Acknowledgements 48
References 48
4 Concave Risk Measures in International Capital Regulation 51
Imre Kondor, Andr'as Szepessy and T"unde Ujv'arosi
4.1 Introduction 51
4.2 Risk measures implied by the trading book regulation 52
4.2.1 Specific risk of bonds 53
4.2.2 Foreign exchange 53
4.2.3 Equity risk 55
4.2.4 The general risk of bonds 55
4.3 Conclusion 58
Acknowledgements 58
References 58
5 Value-at-Risk, Expected Shortfall and Marginal Risk Contribution 61
Hans Rau-Bredow
5.1 Introduction 61
5.2 Value-at-risk as a problematic risk measure 62
5.3 Derivatives of value-at-risk and expected shortfall 63
5.3.1 Preliminary remarks 63
5.3.2 First and second derivative of value-at-risk 63
5.3.3 First and second derivative of expected shortfall 64
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5.4 Outlook 65
Appendix 65
References 67
6 Risk Measures for Asset Allocation Models 69
Rosella Giacometti and Sergio Ortobelli Lozza
6.1 Introduction 69
6.2 Portfolio risk measures 70
6.2.1 Safety risk measures 71
6.2.2 Dispersion measures 74
6.3 Portfolio choice comparison based on historical data 76
6.4 Portfolio choice comparison based on simulated returns 79
6.4.1 Portfolio choice comparison with jointly Gaussian returns 79
6.4.2 Portfolio choice comparison with jointly stable non-Gaussian
returns 81
6.5 Conclusions 84
Acknowledgements 85
References 85
7 Regulation and Incentives for Risk Management in Incomplete Markets 87
J'on Dan'yelsson, Bjorn N. Jorgensen and Casper G. de Vries
7.1 Introduction 87
7.1.1 Complete and incomplete markets 88
7.2 Moral hazard regarding project choice 89
7.2.1 Deposit insurance and moral hazard 90
7.2.2 Threat of an alternative project choice 93
7.3 Moral hazard regarding risk management 95
7.3.1 The basic principal-agent model 96
7.3.2 Supervision 99
7.4 Risk monitoring and risk management 100
7.4.1 Coarser risk monitoring without regulation 101
7.4.2 Indirect risk monitoring with regulation 102
7.4.3 Finer risk monitoring: no regulation 104
7.4.4 Direct risk monitoring with regulation 104
7.4.5 Evaluation 105
7.5 Conclusion 107
References 108
8 Granularity Adjustment in Portfolio Credit Risk Measurement 109
Michael B. Gordy
8.1 Introduction 109
8.2 Granularity adjustment of VaR for homogeneous portfolios 110
8.3 Granularity adjustment of ES for homogeneous portfolios 115
8.4 Application to heterogeneous portfolios 117
Appendix: Wilde's formula for á 119
Acknowledgements 120
References 120
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9 A Comparison of Value-at-Risk Models in Finance 123
Simone Manganelli and Robert F. Engle
9.1 Introduction 123
9.2 Value-at-risk methodologies 124
9.2.1 Parametric models 125
9.2.2 Nonparametric models 126
9.2.3 Semiparametric models 127
9.3 Expected shortfall 133
9.4 Monte Carlo simulation 134
9.4.1 Simulation study of the threshold choice for EVT 134
9.4.2 Comparison of quantile methods performance 136
9.5 Conclusion 139
References 139
Appendix: Tables 141
PART II NEW RISK MEASURES 145
10 Coherent Representations of Subjective Risk-Aversion 147
Carlo Acerbi
10.1 Forewords and motivations 147
10.1.1 In defense of axiomatics 147
10.1.2 Scope and objectives 151
10.1.3 Outline of the work 152
10.2 Building a risk measure: the expected shortfall 153
10.2.1 A close look into VaR's definition 153
10.2.2 A natural remedy to probe the tail: the expected shortfall 156
10.2.3 Coherency of ES 160
10.2.4 Estimation of ES 166
10.3 Spectral measures of risk 168
10.3.1 Estimation of spectral measures of risk 176
10.3.2 Characterization of spectral measures via additional conditions 179
10.3.3 Spectral measures and capital adequacy 185
10.4 Optimization of spectral measures of risk 186
10.4.1 Coherent measures and convex risk surfaces 186
10.4.2 Minimization of expected shortfall 191
10.4.3 Minimization of general spectral measures 194
10.4.4 Risk-reward optimization 197
10.5 Statistical errors of spectral measures of risk 200
10.5.1 Variance of the estimator 200
10.5.2 Some meaningful examples 202
Acknowledgements 206
References 206
11 Spectral risk measures for credit portfolios 209
Claudio Albanese and Stephan Lawi
11.1 Introduction 209
11.2 Test-portfolios with market risk and entity-specific risk 212
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11.3 Properties of risk measures 214
11.4 Discussion of test-portfolios 217
11.5 Concluding remarks 223
Acknowledgements 224
References 225
Appendix: Tables 226
12 Dynamic Convex Risk Measures 227
Marco Frittelli and Emanuela Rosazza Gianin
12.1 Introduction 227
12.1.1 Notations 228
12.1.2 Axioms 229
12.1.3 Coherent risk measures 232
12.2 Convex risk measures 233
12.2.1 Representation of convex risk measures 233
12.2.2 Law-invariant convex risk measures 234
12.3 Indifferent prices and risk measures 235
12.4 Dynamic risk measures 239
12.5 Appendix 243
References 247
13 A Risk Measure for Income Processes 249
Georg Ch. Pflug and Andrzej Ruszczy'nski
13.1 Introduction 249
13.2 The one-period case 252
13.3 Risk of multi-period income streams 255
13.4 Finite filtrations 257
13.5 Properties of the risk measure 258
13.6 Mean-risk models 258
13.7 Examples 260
13.8 A comparison with the ADEHK approach 265
13.9 The discounted martingale property for final processes 267
References 268
PART III COPULA FUNCTIONS FOR THE ANALYSIS OF
DEPENDENCE STRUCTURES 271
14 Financial Applications of Copula Functions 273
Jean-Fr'ed'eric Jouanin, Ga"el Riboulet and Thierry Roncalli
14.1 Introduction 273
14.2 Copula functions 274
14.3 Market risk management 277
14.3.1 Non-Gaussian value-at-risk 277
14.3.2 Stress testing 280
14.3.3 Monitoring the risk of the dependence in basket derivatives 282
14.4 Credit risk management 286
14.4.1 Measuring the risk of a credit portfolio 286
14.4.2 Modelling basket credit derivatives 293
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14.5 Operational risk management 297
14.5.1 The loss distribution approach 297
14.5.2 The diversification effect 298
References 300
15 Hedge Funds: A Copula Approach for Risk Management 303
H'elyette Geman and C'ecile Kharoubi
15.1 Introduction 303
15.2 Hedge funds industry, strategies and data 304
15.2.1 Hedge funds industry: definitions and description 304
15.2.2 The different strategies 306
15.2.3 Biases in hedge funds data 308
15.2.4 Hedge funds indices: descriptive statistics 308
15.3 Copulas and hedge funds 312
15.4 Value-at-risk with copulas 314
15.4.1 Monte Carlo simulation 314
15.4.2 Value-at-risk computation 315
15.5 Conclusion 318
Acknowledgements 319
References 319
16 Change-point Analysis for Dependence Structures in Finance
and Insurance 321
Alexandra Dias and Paul Embrechts
16.1 Introduction 321
16.2 Statistical change-point analysis 322
16.2.1 The test statistic 322
16.2.2 An example: the Gumbel case 325
16.2.3 The power of the test 328
16.2.4 The time of the change and corresponding
confidence intervals 329
16.2.5 Multiple changes 331
16.3 A comment on pricing 332
16.4 An example with insurance data 333
16.5 Conclusion 334
Acknowledgements 334
References 335
PART IV ADVANCED APPLICATIONS 337
17 Derivative Portfolio Hedging Based on CVaR 339
Siddharth Alexander, Thomas F. Coleman and Yuying Li
17.1 Introduction 339
17.2 Minimizing VaR and CVaR for derivative portfolios 341
17.2.1 How well is the minimum risk derivative
portfolio defined? 342
17.2.2 Difficulties due to ill-posedness 344
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17.3 Regularizing the derivative CVaR optimization 348
17.3.1 Example 1: Hedging a short maturity at-the-money call 349
17.3.2 Example 2: Hedging a portfolio of binary options 353
17.4 Minimizing CVaR efficiently 357
17.4.1 Efficiency for CVaR minimization using an LP approach 357
17.4.2 A smoothing technique for CVaR minimization 358
17.5 Concluding remarks 361
Acknowledgements 362
References 362
18 Estimation of Tail Risk and Portfolio Optimisation with Respect
to Extreme Measures 365
Giorgio Consigli
18.1 Introduction 365
18.2 From risk measurement to risk control: the setup 367
18.2.1 VaR control with non-normal return distributions 369
18.3 Beyond VaR: From non coherent to coherent measures 372
18.3.1 Risk measures in the tails: methods accuracy 373
18.3.2 A case study. Application 1: Risk measurement 378
18.3.3 Multidimensional Poisson-Gaussian model 387
18.4 Risk control based on portfolio optimisation 390
18.4.1 Risk-return and trade-off optimisation:
QP and LP solvability 391
18.4.2 Optimal portfolios during periods of market instability 393
18.5 Conclusions and future research 397
Acknowledgements 398
References 398
19 Risk Return Management Approach for the Bank Portfolio 403
Ursula A. Theiler
19.1 Introduction 403
19.2 Step 1 of the RRM approach: optimization model for the bank portfolio 405
19.2.1 Survey 405
19.2.2 Modeling the internal risk constraint 405
19.2.3 Integration of the regulatory risk constraint into the
optimization model 410
19.2.4 Summary of the optimization model of step 1 of the RRM
Approach 416
19.3 Step 2 of the RRM Approach: risk return keys for the optimum portfolio 417
19.3.1 Survey 417
19.3.2 Derivation of risk return keys on the asset level 417
19.3.3 Aggregation of risk return keys on the profit center level 422
19.3.4 Summary of the risk return ratios generated by the RRM
Approach 423
19.4 Application example 424
19.4.1 Situation and problem statement 424
19.4.2 Results 425
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19.5 Conclusion 429
References 430
PART V LAST, BUT NOT LEAST 433
20 Capital Allocation, Portfolio Enhancement and Performance
Measurement: A Unified Approach 435
Winfried G. Hallerbach
20.1 Introduction 435
20.2 Preliminaries 437
20.3 Portfolio optimization, RAROC and RAPM 441
20.3.1 Portfolio optimization without risk-free rate 442
20.3.2 Portfolio optimization allowing for risk-free activities 444
20.4 Conclusions 447
Appendix 448
Acknowledgements 449
References 449
21 Pricing in Incomplete Markets: From Absence of Good Deals
to Acceptable Risk 451
H'elyette Geman and Dilip B. Madan
21.1 Introduction 451
21.2 No-good-deal pricing in incomplete markets 454
21.2.1 Good-deal asset price bounds (Cochrane and
Sa'a-Requejo, 2000) 454
21.2.2 Gain, loss and asset pricing (Bernardo and Ledoit, 2000) 457
21.2.3 The theory of good-deal pricing (Cerny and Hodges, 2001) 460
21.3 Pricing with acceptable risk 462
21.3.1 The economic model 464
21.3.2 The first fundamental theorem 466
21.3.3 The second fundamental theorem 468
21.3.4 Pricing under acceptable incompleteness 470
21.4 Conclusion 473
References 473
Index 475




Library of Congress Subject Headings for this publication: Asset-liability management Mathematical models, Risk assessment