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Prelims

Angelo Corelli (Associate Professor of Finance, Center of Excellence for Research in Finance and Accounting, American University in Dubai, UAE)

Understanding Financial Risk Management, Second Edition

ISBN: 978-1-78973-794-3, eISBN: 978-1-78973-791-2

Publication date: 28 October 2019

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Citation

Corelli, A. (2019), "Prelims", Understanding Financial Risk Management, Second Edition, Emerald Publishing Limited, Leeds, pp. i-xxvii. https://doi.org/10.1108/978-1-78973-791-220192002

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Emerald Publishing Limited

Copyright © 2019 Emerald Publishing Limited

Half Title Page

Understanding Financial Risk Management

Second Edition

Title Page

Understanding Financial Risk Management

Second Edition

Angelo Corelli

Associate Professor of Finance, Center of Excellence for Research in Finance and Accounting, American University in Dubai, UAE

United Kingdom – North America – Japan – India – Malaysia – China

Copyright Page

Emerald Publishing Limited

Howard House, Wagon Lane, Bingley BD16 1WA, UK

First edition 2019

Copyright © 2019 Emerald Publishing Limited

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ISBN: 978-1-78973-794-3 (Print)

ISBN: 978-1-78973-791-2 (E-ISBN)

ISBN: 978-1-78973-793-6 (Epub)

Dedication Page

To the one and only:

Margherita

Contents

List of Tables xv
List of Figures xvii
About the Author xxi
Preface to the First Edition xxiii
Preface to the Second Edition xxvii
Chapter 1: Risk: An Overview 1
1.1. Introduction 2
 1.1.1. Randomness and Uncertainty 2
 1.1.2. Rationality and Risk Aversion 5
 1.1.3. Types of Risk 10
 Snapshot 1.1: Common Forms of Utility Functions 15
1.2. The Process of Risk Management 16
 1.2.1. Risk in Corporations and Financial Institutions 16
 1.2.2. Identification, Measurement, and Mitigation 19
 1.2.3. Risk Response Strategies 22
1.3. Theory of Markets 23
 1.3.1. Arbitrage 23
 1.3.2. The Efficient Market Hypothesis 25
 1.3.3. The Brownian Motion 29
 Snapshot 1.2: Sampling of Brownian Motion Paths in Excel 33
Summary 34
References 34
Exercises 34
Appendix: Types of Market Failure 37
Chapter 2: Financial Markets and Volatility 39
2.1. Modern Portfolio Theory 40
 2.1.1. The Risk/Return Trade-off 40
 2.1.2. Optimal Portfolios of Risky Assets 44
 2.1.3. Optimal Portfolios with Risk-free Asset 48
 Snapshot 2.1: Portfolio Optimization in Excel 50
2.2. The Capital Asset Pricing Model 51
 2.2.1. Model Assumptions 51
 2.2.2. The Security Market Line 55
 2.2.3. Beyond CAPM 59
2.3. Volatility and Correlation 62
 2.3.1. Types of Volatility 63
 2.3.2. Correlation versus Covariance 66
 2.3.3. Maximum Likelihood Methods 69
 Snapshot 2.2: The Covariance Matrix of Financial Returns 72
Summary 72
References 73
Exercises 73
Appendix: The Table of the Standard Normal Distribution 77
Chapter 3: Conditional Dependence and Time Series 79
3.1. Modeling Financial Comovements 80
 3.1.1. Conditional Covariance 80
 3.1.2. Conditional Correlation 81
3.2. Time Series Analysis 83
 3.2.1. ARCH/GARCH Models 83
 3.2.2. Autocorrelation of Financial Returns 87
 3.2.3. Other Stylized Facts 91
Summary 93
References 93
Chapter 4: Statistical Analysis 95
4.1. Relevant Distributions 96
 4.1.1. Pareto Distribution 96
 4.1.2. Binomial Distribution 100
 4.1.3. Poisson Distribution 103
 Snapshot 4.1: Excel Statistical Functions 108
4.2. Probabilistic Approaches 109
 4.2.1. Scenario Analysis 109
 4.2.2. Decision Trees 110
 4.2.3. Simulations 113
Summary 115
References 116
Exercises 116
Appendix: Itô’s Lemma 120
Chapter 5: Beyond Normality and Correlation 123
5.1. Copula Functions 124
 5.1.1. Basic Properties 124
 5.1.2. Measures of Dependence 127
 5.1.3. Application to Risk Management 130
 Snapshot 5.1: Monte Carlo Simulation of Copulas 133
5.2. Extreme Value Theory 133
 5.2.1. Theoretical Background 134
 5.2.2. Data Application 137
 5.2.3. Extreme VaR 138
5.3. Beyond VaR 140
 5.3.1. Model Back Testing 140
 5.3.2. Expected Shortfall 143
 5.3.3. Conditional VaR 145
Summary 147
References 148
Exercises 149
Appendix: VaR for Portfolios of Derivatives 150
Chapter 6: Conditional Risk Analysis 153
6.1. Beyond VaR 154
 6.1.1. Expected Shortfall 154
 6.1.2. Conditional VaR 156
6.2. Multivariate Return Distributions 158
 6.2.1. GARCH(p, q) Modeling 159
Summary 161
References 161
Chapter 7: High-frequency Data 163
7.1. High-frequency Trading 163
 7.1.1. Data Filtering 163
 7.1.2. Basic Stylized Facts 166
7.2. Intraday Risk Analysis 167
 7.2.1. Heterogeneous Volatility 167
Summary 169
References 170
Chapter 8: Financial Derivatives 171
8.1. Options and Futures 172
 8.1.1. Types of Traders in the Market 172
 8.1.2. Option Structure and Payout 175
 8.1.3. Forwards and Futures 177
 Snapshot 8.1: Volatility Strategy with Strangles 182
8.2. Interest Rate Derivatives 183
 8.2.1. Interest Rate Swaps 183
 8.2.2. Caps and Floors 185
 8.2.3. Swaptions 188
Summary 192
References 192
Exercises 193
Appendix: The Market Price of Risk 194
Chapter 9: Option Pricing and Risk Modeling 197
9.1. Option Pricing Models 198
 9.1.1. Binomial Trees 198
 9.1.2. BSM Model 202
9.2. Portfolio Hedging 207
 9.2.1. Delta Hedging 207
 9.2.2. Gamma and Vega Hedging 210
 9.2.3. The Cost of Hedging 212
Summary 214
References 215
Exercises 215
Chapter 10: Market Risk 217
10.1. Market Risk Metrics 218
10.1.1. Overview of Market Risk 218
10.1.2. Quantile Metrics and Value-at-Risk 220
10.1.3. VaR Rationale and Definition 224
Snapshot 10.1: The Choice of Parameters for VaR 227
10.2. VaR Calculation Methods 228
10.2.1. Historical Simulation Approach 228
10.2.2. Parametric Method 229
10.2.3. Monte Carlo Simulation 231
Snapshot 10.2: Euler’s Theorem on Homogeneous Functions 234
Summary 234
References 235
Exercises 236
Appendix: Factor Mapping for VaR 238
Chapter 11: Inside Value at Risk 241
11.1. VaR Features 241
 11.1.1. Decomposition 242
 11.1.2. Limitations 245
 11.1.3. Analytic Approximations 247
11.2. VaR Testing 249
 11.2.1. Model Back Testing 249
 11.2.2. Stress Testing 251
Summary 253
References 253
Appendix: Factor Mapping for VaR 255
Chapter 12: Interest Rate Risk 257
12.1. The Dynamics of Interest Rates 258
 12.1.1. Bond Prices and Yields 258
 12.1.2. Fixed Income Futures 263
 12.1.3. Yield Shifts and Immunization 267
 Snapshot 12.1: Compounding Frequencies for Interest Rates 272
12.2. Short Rate Models 272
 12.2.1. The Term Structure of Interest Rates 272
 12.2.2. Single-factor Models 276
 12.2.3. Multi-factor Models 280
12.3. IRR Management 282
 12.3.1. Sources and Identification 282
 12.3.2. Measurement Techniques 284
 12.3.3. Duration and Convexity Hedging 286
Summary 290
References 291
Exercises 292
Appendix: Principal Component Analysis of the Term Structure 295
Chapter 13: Credit Risk 297
13.1. Basic Concepts 298
 13.1.1. Default Probabilities 298
 13.1.2. Loss Given Default 302
 13.1.3. Credit Ratings 305
13.2. Structural Models 308
 13.2.1. The KMV-Merton Approach 308
 13.2.2. First Passage Models 313
 13.2.3. CreditMetrics™ 315
13.3. Reduced-form Models 317
 13.3.1. The Jarrow-Turnbull Model 317
 13.3.2. The Duffie-Singleton Model 320
 13.3.3. CreditRisk+™ 321
Summary 324
References 325
Exercises 326
Appendix: Markov Process for Transition Matrices 328
Chapter 14: Liquidity Risk 331
14.1. Market Prices 332
 14.1.1. Market Microstructure 332
 14.1.2. Price Formation 336
 14.1.3. Funding versus Market Liquidity 338
 Snapshot 14.1: Liquidity Black Holes 343
14.2. Models of Liquidity 344
 14.2.1. Theoretical Models 344
 14.2.2. Traceable Models 348
 14.2.3. The Diamond-Dybvig Model 352
14.3. Liquidity Risk and Regulation 355
 14.3.1. Liquidity Coverage Ratio 355
 14.3.2. Net Stable Funding Ratio 358
 14.3.3. Monitoring Tools 359
Summary 362
References 363
Exercises 364
Appendix: Liquidity CAPM 366
Chapter 15: Enterprise Risk 369
15.1. The Fundamentals 370
 15.1.1. Identification and Assessment 370
 15.1.2. The ERM Framework 373
 15.1.3. The COSO ERM 374
15.2. Building and Enhancing 377
 15.2.1 Improving the Process View 377
 15.2.2 Technological Capabilities 380
15.3. Practical Implementation 382
 15.3.1. The Role of the Management 382
 15.3.2. Implementation and Models 385
Summary 386
References 386
Chapter 16: Other Risks 387
16.1. Operational Risk 388
 16.1.1. Identification and Assessment 388
 16.1.2. Treatment and Control 391
 16.1.3. Basel II Approach 393
16.2. Currency Risk 397
 16.2.1. Types of Currency Risk 397
 16.2.2. Foreign Exchange Derivatives 399
 16.2.3. Risk Hedging in FX Markets 404
16.3. Volatility Risk 405
 16.3.1. Implied Volatility 406
 16.3.2. Callable Bonds 407
 16.3.3. Variance Swaps 410
 Snapshot 16.1: Gamma Swaps 413
Summary 414
References 415
Exercises 415
Appendix: Risk-adjusted Return on Capital 417
Chapter 17: Financial Crisis and Securitization 419
17.1. Crisis and Regulation 420
 17.1.1. The Lack in Regulatory Framework 420
 17.1.2. The Crisis in Europe 424
 17.1.3. The Impact on the Financial Industry 428
17.2. Credit Derivatives 430
 17.2.1. Asset Swaps 430
 17.2.2. Credit Default Swaps 435
 17.2.3. CDS Spreads with Counterparty Credit Risk 438
 Snapshot 17.1: The Newton–Raphson Method 441
17.3. Securitization 442
 17.3.1. Structure and Participants 442
 17.3.2. Collateralized Debt Obligations 444
 17.3.3. Advantages and Disadvantages 448
Summary 450
References 451
Exercises 452
Appendix: A Model of SPVs 453
Chapter 18: Hedging Techniques 455
18.1. Market Risk Hedging 456
 18.1.1. Delta Hedging 456
 18.1.2. Gamma and Vega Hedging 458
 18.1.3. The Cost of Hedging 460
18.2. Credit Risk Hedging 463
 18.2.1. Modeling Exposure 463
 18.2.2. Credit Value Adjustment 467
 18.2.3. Monte Carlo Methods 472
18.3. Advanced IRR Hedging 475
 18.3.1. M-Absolute and M-Squared Models 475
 18.3.2. Duration Vectors 477
 18.3.3. Hedging with Fixed Income Derivatives 480
 Snapshot 18.1: Convexity Adjustment for Interest Rate Derivatives 483
Summary 484
References 485
Exercises 486
Chapter 19: Advanced Topics 489
19.1. VaR Advances 490
 19.1.1. Modified Delta VaR 490
 19.1.2. Historical Simulation Revisited 493
 19.1.3. Modified Monte-Carlo and Scenario Analysis 495
19.2. Alternative Risk Transfer 496
 19.2.1. The ART Market 496
 19.2.2. Primary Contracts 498
 19.2.3. Insurance Derivatives 501
19.3. High-frequency Trading 504
 19.3.1. Data Filtering 504
 19.3.2. Basic Stylized Facts 506
 19.3.3. Heterogeneous Volatility 508
Summary 510
References 511
Exercises 512
Appendix: Power Laws for Intraday Data 513
Chapter 20: The Future of Financial Risk Management 515
20.1. The Role of Corporate Governance 516
 20.1.1. Management Failures 516
 20.1.2. Remuneration and Incentive Systems 519
 20.1.3. Post-crisis Perspectives 522
20.2. The Banking Sector 522
 20.2.1. Bank Risk and Business Models 522
 20.2.2. Risk Management Systems 524
 20.2.3. Areas of Future Improvements 528
20.3. Challenges for Research 531
 20.3.1. Interbank Risk 531
 20.3.2. Energy Derivatives 532
 20.3.3. Sovereign Risk Dynamics 535
20.4. Digitalization and Risk Management 537
 20.4.1. The Impact of Fintech 538
 20.4.2. Big Data and Risk 538
Summary 539
References 540
Exercises 540
Index 543

List of Tables

Table 1.1 Risk Likelihood. 21
Table 1.2 Risk Impact. 21
Table 1.3 Risk Priority. 21
EXtable 2.1 50
EXtable 2.2 50
EXtable 2.3 51
EXtable 2.4 68
EXtable 2.5 68
EXtable 2.6 74
EXtable 2.7 75
EXtable 2.8 75
EXtable 2.9 76
EXtable 2.10 76
EXtable 2.11 77
EXtable 2.12 78
EXtable 4.1 108
EXtable 4.2 108
EXtable 4.3 109
EXtable 4.4 110
EXtable 4.5 118
EXtable 4.6 119
Table 8.1 Replication of a Forward Contract by Using the Underlying Asset. 179
EXtable 8.1 193
Table 12.1 Effective Annual Rate Calculation for Different Compounding Frequencies. 259
Table 12.2 Compounding Frequencies. 259
EXTable 12.1 265
EXTable 12.2 265
EXTable 12.3 266
EXTable 12.4 292
EXTable 12.5 292
EXTable 12.6 293
EXTable 12.7 293
Table 13.1 Credit Conversion Factors for PFE Calculation. 302
EXTable 13.1 303
Table 13.2 Credit Ratings Assigned by the Major Credit Agencies. 306
Table 13.3 Credit Ratings on Sovereign Countries. 307
Table 13.4 Altman’s z-Score Factors and Weights. 307
EXTable 13.2 308
Table 13.5 A Typical Example of a Credit Ratings Transition Matrix. 316
EXTable 13.3 326
EXTable 13.4 326
EXTable 13.5 327
Table 14.1 Runoff Rates for the Major Asset Categories. 357
Table 14.2 RSF Factors for the Major Category Components. 360
EXTable 14.1 364
EXTable 14.2 365
EXTable 14.3 365
Table 16.1 Operational Income Factors and Indicators for the Different Business Lines in the Bank. 394
Table 18.1 Volatility Spread Approximations. 469
Table 18.2 Add-on Percentages of the Underlying Amount for Different Types of Contract. 470
EXTable 18.1 486
EXTable 18.2 487

List of Figures

Fig. 1.1 Graph Concave Utility Function. 9
Fig. 1.2 Diversification. 11
Fig. 1.3 Risk Process. 17
Fig. 1.4 Information Subsets. 28
Fig. 2.1 Normal Distribution 1. 41
Fig. 2.2 Normal Distribution 2. 41
Fig. 2.3 Normal Distribution 3. 42
Fig. 2.4 Efficient Frontier for Portfolio or Risky Assets. 45
Fig. 2.5 CML. 49
Fig. 2.6 Leverage. 50
Fig. 2.7 SML. 58
Fig. 2.8 SML Alpha. 59
Fig. 3.1 Autocorrelation. 88
Fig. 3.2 ACF. 89
Fig. 4.1 Pareto Distribution. 98
Fig. 4.2 Binomial Distribution. 102
Fig. 4.3 Poisson Distribution. 106
Fig. 4.4 Tree Nodes. 111
Fig. 4.5 Tree Example 1. 112
Fig. 4.6 Tree Example 2. 113
Fig. 5.1 Copula Gauss Student. 126
Fig. 5.2 Copula Clayton Frank. 127
Fig. 5.3 Copula Gumbel. 127
Fig. 5.4 Frechet Weibull Distribution. 136
Fig. 5.5 Gumbel Distribution. 136
Fig. 8.1 Long Call. 176
Fig. 8.2 Short Call. 176
Fig. 8.3 Long Put. 177
Fig. 8.4 Short Put. 177
Fig. 8.5 Forward. 178
Fig. 8.6 Strangles. 182
Fig. 9.1 Binomial Tree. 198
Fig. 9.2 Price Tree. 200
Fig. 10.1 Normal Distribution VaR. 221
Fig. 10.2 VaR. 223
Fig. 12.1 Yield Shift 1. 267
Fig. 12.2 Yield Shift 2. 267
Fig. 12.3 Yield Shift 3. 268
Fig. 12.4 The Yield Curve, As Resulting from Most Common Models of the Interest Rates, and Observed Empirically, Can Take Different Forms. 273
Fig. 13.1 The KMV Modeling of Expected Default. 312
Fig. 13.2 CreditMetrics™. 315
Fig. 13.3 CreditMetrics™ Thresholds. 317
Fig. 14.1 Liquidity. 340
Fig. 16.1 Structure of Internal Controls. 392
Fig. 16.2 Loss Frequency and Severity. 394
Fig. 16.3 Callable Duration. 409
Fig. 16.4 Convexity. 410
Fig. 17.1 Asset Swap. 431
Fig. 17.2 Market Asset Swap. 432
Fig. 17.3 CDS. 435
Fig. 17.4 Securitization. 443
Fig. 17.5 Tranches. 445
Fig. 17.6 CDO. 446
Fig. 17.7 ABS CDO. 446
Fig. 19.1 Captives. 499
Fig. 19.2 Multi-risk. 500
Fig. 19.3 Cat Swap Before. 502
Fig. 19.4 Cat Swap After. 503
Fig. 19.5 Stylized Facts. 507
Fig. 20.1 Board of Directors. 517
Fig. 20.2 Remuneration. 520
Fig. 20.3 Banking. 525
Fig. 20.4 Diagram of a Crude Oil Swap. 534

About the Author

Angelo Corelli is Associate Professor of Finance at the American University in Dubai. His field of expertise is financial risk management with a focus on credit risk. Angelo’s research topics span from quantitative risk management to term structure analysis and valuation/risk of financial derivatives. The main focus of his teaching lies on corporate finance, with a special emphasis on corporate valuation mechanisms.

Preface to the First Edition

A Modern Approach

Understanding Financial Risk Management offers an innovative approach to financial risk management. With a broad view of theory and the industry, it aims at being a friendly, but serious, starting point for those who encounter risk management for the first time, as well as for more advanced users.

The focus is no longer on the mere measurement, but on the whole package. Risk is also opportunity, and when managing it, one should reach the right balance between opportunity and loss. That is why we propose a new approach that starts from the basic knowledge of classic theory and methodologies and moves to the latest findings in measurement and hedging.

Many books are more exhaustive in covering some of the topics that are treated in this book, but most of them do not offer the wholesome coverage on the horizon of financial risk management as the present book does.

There is no doubt that a deeper analysis of many concepts is possible, but no book in the actual market is able to collect all risks and the managing of them in one single essay. This book is definitely an all-included piece or work that guides the reader from the beginning to the end without ever losing focus on what is more important for good risk-management knowledge.

An Innovative Pedagogy

The foundations of the book rely on three main blocks: theory, analytics, and computational. They all merge in a way that makes it easy for students to understand the exact meaning of the concepts and their representation and applicability in real world contexts. Examples are given throughout the chapters in order to clarify the most intricate aspects; where needed, there are appendices at the end of chapters that give more mathematical insights about specific topics.

Learning comes from the correct combination of the three pillar elements, none of which should be excluded. The trinity stands as the foundation of the whole project.

Preferably, students have a solid background in financial mathematics, statistics, and basic econometrics. Indeed, students facing financial topics for the first time may benefit from using the book as a medium-level introduction to some aspects of financial theory and practice.

In this sense, practitioners represent a possible share of the users of the book. In recent years, due to the global financial crisis, the demand for links between academics and private industry has increased substantially. For this reason, practitioners nowadays like to explore the work done in academic research, and this book provides useful information for managers who want to increase their knowledge about risk management and understand what may have been the lacking in their own systems.

A Selected Audience

The book is meant for third- or fourth-year undergraduate students of business finance, quantitative finance, and financial mathematics. Most of the universities that the book would target offer the kind of training in mathematics and statistics that would be prerequisites for the successful completion of a course using Understanding Financial Risk Management. Potential users include students of universities, technical schools, and business schools offering courses in financial risk management.

This book offers a unique approach and represents a clear improvement on existing textbooks in the field of finance. Most textbooks on financial risk management focus on measurement or on some specific kind of risk. There is no challenge or criticism in them, and there is no drive for understanding risk management in the critical sense. That is exactly what this book will offer.

Quantitative approaches now incorporate a more critical view and contribute to a vision that does not blindly rely on numbers, but takes into account the variety of (sometimes unpredictable) situations that characterize financial markets.

Certainly, it is not an easy book, but it is a book that never abandons the reader. Even in the most complicated parts, the student is guided through the processes and given the tools he needs; nothing is cryptic.

A Reliable Partner for Instructors

Understanding Risk Management is tailored mostly for in-class lectures, and it has the best effect if combined with good quality lecture slides from the instructor. Secondarily, given its overall flexibility (a result of its simple structure), it can also be used for online learning. However, the medium-high level of difficulty of the book suggests the need for a closer relation with the instructor and the possibility of in-person explanations.

The structure of Understanding Financial Risk Management lends itself to a typical Swedish course of approximately six ECTS. The 10 chapters, of at most 60 pages each, can fit a course design of about 14–16 lectures of 1.5 hours effective teaching. That would also fit an overall international standard of a course with two lectures per week spanned over a two-month teaching term. The overall contents in the book can fill approximately 40–60 hours of teaching.

Richness in Content

This book is the ultimate tool for understanding the many aspects of financial risk management, and it comes with a solid theoretical set.

This first edition has been edited to help educators around the world, suiting users dealing with financial risk for the first time, as well as more advanced users looking for an innovative approach.

As a textbook, the richness in content, exercises, and applications makes the book the perfect partner for the students of all areas in the world, all shaped in a book featuring:

  • (a)

    14 chapters,

  • (b)

    70 major and 126 detailed learning outcomes,

  • (c)

    numerous tasks (questions and exercises),

  • (d)

    snapshots and appendices wherever relevant, and

  • (e)

    numerous selected references.

Every chapter follows the same structure, where the full text is complemented by snapshots relating to cutting-edge research and up-to-date news. At the end of each chapter, there is an exercise section with targeted tasks.

Preface to the Second Edition

The second edition of Understanding Financial Risk Management aims to improve the first edition by introducing a more structured approach to the sources of risk in the organization, and the methods used to manage it.

From identification to assessment and management, all types of financial risks a company faces daily are analyzed, together with the tools and techniques that can be used to limit their impact and manage their connected risk events.

Built on the solid pedagogical approach used in the first edition, the second edition improves it by extending the narrative to modern and innovative topics like enterprise risk.

The result is a 20-chapter textbook that takes the student into a full-immersion experience. After an introductory part where distributional issues, statistical tools, and other foundation topics are analyzed, the chapters start digging deep into all types of financial risk that are normally presented to the organization on a daily basis.

An improved coverage of major risks, together with ample narrative on how to use financial derivatives to hedge risk, offer a complete view on past, current, and future trends in financial risk management.

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