Advanced Analytical Methods for Climate Risk and ESG Risk Management

JORGE SOBEHART has over 35 years of experience in advanced quantitative modelling in industry and government, having worked for prestigious institutions including the Atomic Energy Commission of Argentina (Nuclear Fusion Division), the Center for Nonlinear Studies at the US Los Alamos National Laboratory, Moody’s Investors Service, and CASA, a cutting-edge financial consulting start-up, making contributions in the fields of risk management, behavioral finance, theoretical and applied physics, computation and mathematical modeling. He also acted as a technical reviewer for several book editors and over a dozen professional journals in these fields. He is currently a Managing Director at a large global financial institution, leading analytics for wholesale credit and climate risk and risk ratings. During his career, he designed and developed frameworks for wholesale credit risk capital and allocation, credit and climate risk stress testing (CCAR, ICAAP, Climate Risk), credit reserves (CECL, IFRS9, FAS5), risk ratings, probability of default and various early warning tools of credit deterioration.

Introduction: Climate Risk and Environmental, Social and Governance Challenges xiii

Chapter 1 Introduction to Climate Risk 1

Dimensions of Climate Risk 1

Basic Concepts of Climate 2

Carbon Dioxide, Greenhouse Gases (GHG), and Air Pollution 5

The Science of Climate Change 6

Climate Change, the Intergovernmental Panel on Climate Change (IPCC) Reports, and Social Change 10

References 12

Chapter 2 Forces of Nature 15

The Astronomical Theory of Climate Change 15

The Sun 24

The Earth 27

Air and Wind 30

Water and Ice 32

The Carbon Cycle 34

Note 36

References 36

Chapter 3 A Brief History of Climate Change 39

Natural Drivers of Climate Change Over the Ages 39

Frozen Earth 40

Warming and Freezing Cycles and Periodic Glaciations 41

The Last Ice Age, Younger Dryas, and Climate Cycles 42

Climate Change in Ancient Times 43

Roman Warm Period 44

The Climate in the Dark Ages 44

The Medieval Warm Period 45

The Little Ice Age 46

The Industrial Revolution and Man-Made Effects 48

Today and Tomorrow 52

References 52

Chapter 4 Science, Politics, and Public Policy 55

Science, Facts, Perception, Social Influence, Misinformation, and Fear 55

Behavioral Aspects of Risk Taking and Decision Making 56

Perception and Plausibility of Events 59

Trust, Deception, Credibility, and Fake News 60

Social Pressure, Conformity, and Media Bias 63

Social Polarization 65

Opinion Polarization under Social Pressure and Media Bias 67

Social Pressure, Media Bias, and Perception for Different Groups 70

Choice Impact for Different Groups 74

What’s Next? Tackling the Climate Change Challenge 76

References 78

Chapter 5 Global Shift in Response to Climate Change 81

The Shift in the Global Economy in Response to Climate Change 81

Technology Change: First Movers, Competitive Landscape, and Economic Environments 87

Climate Risk Uncertainty in Competitive Business Environments 90

Innovation and Product Dynamics 93

Product Adoption 95

Product Competition 98

Multiple Competitor Environments 100

Uncertainty in Competitive Environments 103

Notes 107

References 107

Chapter 6 Risk Management for Climate Risk and ESG 111

Overview, Purpose, Scope of Risk Management, and Governance 111

Risk Identification, Measurement, and Management 113

Regulatory Environment and Climate Risk 126

Operational Readiness and Resilience for Climate-Related Effects 128

Risk Monitoring and Reporting 132

Risk Reporting and Analysis 133

Reshaping the Industry Landscape: Winners, Losers, and Synergies 135

Sustainability, Competitive Environment, and a Level Playing Field 138

Climate-Related Financial Disclosures 138

Climate Risk Financial Disclosures 143

Building a Stress-Testing Framework for Climate Risk Using ThreeCorePillars 155

References 161

Chapter 7 Pillar 1: Competitive Landscape and Climate Risk Scenarios for Stress Testing 163

Assessing the Industry and Regulatory Landscape, Synergies, and Complexities of Competitive Business Environments 163

Scenarios for the Global Economy: Economic, Business, and Credit Cycles 164

Business Cycles, Credit Supply, and Demand 171

Economic Drivers 173

Economic Activity and Credit Demand 174

The Impact of Local Economic Conditions on Global Obligors 206

References 208

Chapter 8 Pillar 2: Demand for Credit: Modeling Default Risk and Loss Severity 211

Supply and Demand for Credit: Excess Credit Demand 211

Analysis of Economic Activity 216

Defining Key Concepts: Default, Loss Likelihood, and Loss Severity 217

Credit Correlation 232

Note 239

References 239

Chapter 9 Pillar 2: Demand for Credit: Risk Assessment and Credit Risk Ratings 245

The Path to Business Failure 245

Risk Assessment and Credit Risk Ratings 246

Credit Risk Ratings 248

Default and Loss Concepts and Risk Ratings 259

Default Rate Statistics by Rating Category 261

Rating Transition Matrices 264

Rating Transitions and the Term Structure of Default Rates 265

Portfolio Risk Rating 267

Portfolio Trend Rating 267

Risk Management Rating 267

Rating Stability 270

Quantifying Analysts’ Perception of Credit Risk: A Behavioral Model 271

Notes 295

References 295

Chapter 10 Pillar 2: Demand for Credit: The Value of Financial Information 297

The Value of Financial Information: Balance Sheet, Income Statement, and Statement of Cash Flows 297

The Balance Sheet 298

The Income Statement 305

The Statement of Cash Flows 309

Financial Information and Uncertainty 313

Cash Liquidity and Debt Capacity 314

Cash Shortfall, Business Uncertainty, and Financial Distress 317

Note 321

References 321

Chapter 11 Pillar 2: Demand for Credit: Models of Business Failure 325

Credit Risk Models of Business Failure 325

Model Selection 329

Statistical and Econometric Models 330

Credit Scoring and Statistical Discriminant Analysis 333

Models of Probability of Default 340

Nonlinear Models 343

Statistical Inference and Bayesian Methods 345

Model Selection Criteria: Least Squares and Likelihood Methods 347

Information Entropy Methods and Model Selection 348

A Primer on Neural Networks 356

Validating Statistical Models 361

Measuring Model Accuracy 361

A Validation Approach for Quantitative Models 363

Resampling 368

Model Performance and Benchmarking 368

References 380

Chapter 12 Pillar 2: Structural Models 383

The Role of Market Information in the Pricing of Risky Debt 383

Options Pricing, Randomness, and the Notion of Limit 386

Options Pricing and Stochastic Calculus 386

Ito Stochastic Integrals, Convergence, and the Notion of Limit 389

Hedging Portfolio Returns in the Limit vs. Hedging the Limit of Portfolio Changes 391

Residual Risk and Volatility Skews 394

Hedging Strategies and Residual Risk 395

Models and Assumptions 397

Asset-Based Models and Market Uncertainty 398

Forward-Looking, Singular Perturbation Analysis 400

Market Uncertainty and the Valuation of Equity and Debt 408

Revisiting the Default Point 412

The Role of the Company’s Borrowing Capacity 413

Joint Distribution of Assets, Equity, and Debt 415

Uncertainty, Arbitrage, and Equity-Debt Relationship 421

Notes 424

References 424

Chapter 13 Pillar 3: Supply of Credit: Modeling Lender’s Behavior and Business Strategies 429

Portfolio Management 429

Estimating Portfolio Losses 434

References 448

Acknowledgments 451

About the Author 453

Index 455