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 xiiiChapter 1 Introduction to Climate Risk 1Dimensions of Climate Risk 1Basic Concepts of Climate 2Carbon Dioxide, Greenhouse Gases (GHG), and Air Pollution 5The Science of Climate Change 6Climate Change, the Intergovernmental Panel on Climate Change (IPCC) Reports, and Social Change 10References 12Chapter 2 Forces of Nature 15The Astronomical Theory of Climate Change 15The Sun 24The Earth 27Air and Wind 30Water and Ice 32The Carbon Cycle 34Note 36References 36Chapter 3 A Brief History of Climate Change 39Natural Drivers of Climate Change Over the Ages 39Frozen Earth 40Warming and Freezing Cycles and Periodic Glaciations 41The Last Ice Age, Younger Dryas, and Climate Cycles 42Climate Change in Ancient Times 43Roman Warm Period 44The Climate in the Dark Ages 44The Medieval Warm Period 45The Little Ice Age 46The Industrial Revolution and Man-Made Effects 48Today and Tomorrow 52References 52Chapter 4 Science, Politics, and Public Policy 55Science, Facts, Perception, Social Influence, Misinformation, and Fear 55Behavioral Aspects of Risk Taking and Decision Making 56Perception and Plausibility of Events 59Trust, Deception, Credibility, and Fake News 60Social Pressure, Conformity, and Media Bias 63Social Polarization 65Opinion Polarization under Social Pressure and Media Bias 67Social Pressure, Media Bias, and Perception for Different Groups 70Choice Impact for Different Groups 74What’s Next? Tackling the Climate Change Challenge 76References 78Chapter 5 Global Shift in Response to Climate Change 81The Shift in the Global Economy in Response to Climate Change 81Technology Change: First Movers, Competitive Landscape, and Economic Environments 87Climate Risk Uncertainty in Competitive Business Environments 90Innovation and Product Dynamics 93Product Adoption 95Product Competition 98Multiple Competitor Environments 100Uncertainty in Competitive Environments 103Notes 107References 107Chapter 6 Risk Management for Climate Risk and ESG 111Overview, Purpose, Scope of Risk Management, and Governance 111Risk Identification, Measurement, and Management 113Regulatory Environment and Climate Risk 126Operational Readiness and Resilience for Climate-Related Effects 128Risk Monitoring and Reporting 132Risk Reporting and Analysis 133Reshaping the Industry Landscape: Winners, Losers, and Synergies 135Sustainability, Competitive Environment, and a Level Playing Field 138Climate-Related Financial Disclosures 138Climate Risk Financial Disclosures 143Building a Stress-Testing Framework for Climate Risk Using ThreeCorePillars 155References 161Chapter 7 Pillar 1: Competitive Landscape and Climate Risk Scenarios for Stress Testing 163Assessing the Industry and Regulatory Landscape, Synergies, and Complexities of Competitive Business Environments 163Scenarios for the Global Economy: Economic, Business, and Credit Cycles 164Business Cycles, Credit Supply, and Demand 171Economic Drivers 173Economic Activity and Credit Demand 174The Impact of Local Economic Conditions on Global Obligors 206References 208Chapter 8 Pillar 2: Demand for Credit: Modeling Default Risk and Loss Severity 211Supply and Demand for Credit: Excess Credit Demand 211Analysis of Economic Activity 216Defining Key Concepts: Default, Loss Likelihood, and Loss Severity 217Credit Correlation 232Note 239References 239Chapter 9 Pillar 2: Demand for Credit: Risk Assessment and Credit Risk Ratings 245The Path to Business Failure 245Risk Assessment and Credit Risk Ratings 246Credit Risk Ratings 248Default and Loss Concepts and Risk Ratings 259Default Rate Statistics by Rating Category 261Rating Transition Matrices 264Rating Transitions and the Term Structure of Default Rates 265Portfolio Risk Rating 267Portfolio Trend Rating 267Risk Management Rating 267Rating Stability 270Quantifying Analysts’ Perception of Credit Risk: A Behavioral Model 271Notes 295References 295Chapter 10 Pillar 2: Demand for Credit: The Value of Financial Information 297The Value of Financial Information: Balance Sheet, Income Statement, and Statement of Cash Flows 297The Balance Sheet 298The Income Statement 305The Statement of Cash Flows 309Financial Information and Uncertainty 313Cash Liquidity and Debt Capacity 314Cash Shortfall, Business Uncertainty, and Financial Distress 317Note 321References 321Chapter 11 Pillar 2: Demand for Credit: Models of Business Failure 325Credit Risk Models of Business Failure 325Model Selection 329Statistical and Econometric Models 330Credit Scoring and Statistical Discriminant Analysis 333Models of Probability of Default 340Nonlinear Models 343Statistical Inference and Bayesian Methods 345Model Selection Criteria: Least Squares and Likelihood Methods 347Information Entropy Methods and Model Selection 348A Primer on Neural Networks 356Validating Statistical Models 361Measuring Model Accuracy 361A Validation Approach for Quantitative Models 363Resampling 368Model Performance and Benchmarking 368References 380Chapter 12 Pillar 2: Structural Models 383The Role of Market Information in the Pricing of Risky Debt 383Options Pricing, Randomness, and the Notion of Limit 386Options Pricing and Stochastic Calculus 386Ito Stochastic Integrals, Convergence, and the Notion of Limit 389Hedging Portfolio Returns in the Limit vs. Hedging the Limit of Portfolio Changes 391Residual Risk and Volatility Skews 394Hedging Strategies and Residual Risk 395Models and Assumptions 397Asset-Based Models and Market Uncertainty 398Forward-Looking, Singular Perturbation Analysis 400Market Uncertainty and the Valuation of Equity and Debt 408Revisiting the Default Point 412The Role of the Company’s Borrowing Capacity 413Joint Distribution of Assets, Equity, and Debt 415Uncertainty, Arbitrage, and Equity-Debt Relationship 421Notes 424References 424Chapter 13 Pillar 3: Supply of Credit: Modeling Lender’s Behavior and Business Strategies 429Portfolio Management 429Estimating Portfolio Losses 434References 448Acknowledgments 451About the Author 453Index 455