BlackRock's Guide to Fixed-Income Risk Management

Name: BlackRock's Guide to Fixed-Income Risk Management
Brand: Wiley
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Inc. BlackRock(Author)

Bennett W. Golub(Editor)

Wiley (Publisher)

1st Edition

Published on 25. October 2023

448 pages

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978-1-119-88489-7 (ISBN)

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Content

Cover
Title Page
Copyright
Contents
Frequently Used Abbreviations
Foreword
Preface
Acknowledgments
Section I An Approach to Fixed-Income Investment Risk Management
Chapter 1 An Investment Risk Management Paradigm
1.1 Introduction
1.2 Elements of Risk Management
1.3 BlackRock's Investment and Risk Management Approach
1.4 Introduction to the BlackRock Investment Risk Management Paradigm
Notes
Chapter 2 Parametric Approaches to Risk Management
2.1 Introduction
2.2 Measuring Interest Rate Exposure: Analytical Approaches
2.2.1 Macaulay and Modified Duration and Convexity
2.2.2 Option-Adjusted Framework: OAV, OAS, OAD, OAC
2.2.3 Dynamic Nature of Local Risk Measures: Duration and Convexity Drift
2.2.4 Interest Rate Scenario Analysis
2.3 Measuring Interest Rate Exposure: Empirical Approaches
2.3.1 Coupon Curve Duration
2.3.2 Empirical (Implied) Duration
2.4 Measuring Yield Curve Exposure
2.4.1 Key Rate Durations
2.5 Measuring and Managing Volatility Related Risks
2.5.1 Volatility Duration
2.5.2 Option Usage in Portfolio Management
2.6 Measuring Credit Risk
2.6.1 Spread Duration
2.6.2 Duration Times Spread (DxS)
2.7 Measuring Mortgage-Related Risks
2.7.1 Prepayment Duration
2.7.2 Mortgage/Treasury Basis Duration
2.8 Measuring Impact of Time
Notes
Chapter 3 Modeling Yield Curve Dynamics
3.1 Probability Distributions of Systematic Risk Factors
3.2 Principal Component Analysis: Theory and Applications
3.2.1 Introduction
3.2.2 Principal Components Analysis
3.2.3 The First Principal Component and the Term Structure of Volatility
3.2.4 Example: Historical Steepeners and Flatteners of the US Treasury Curve
3.3 Probability Distributions of Interest Rate Shocks
Notes
Chapter 4 Portfolio Risk: Estimation and Decomposition
4.1 Introduction
4.2 Portfolio Volatility and Factor Structure
4.3 Covariance Matrix Estimation
4.3.1 Weighting of Historical Data
4.3.1.1 Exponential Decay Weighting
4.3.1.2 Alternative Weighting Schemes and Stress Scenarios
4.3.1.3 Enhancing Volatility Responsiveness Dynamically
4.3.2 Asynchronicity
4.3.2.1 Overlapping Covariance Matrix
4.3.2.2 Newey-West Estimation
4.3.3 Factor Model Structure: Generalizations
4.3.3.1 Optimization of the Error-Bias Trade-Off
4.3.3.2 Misspecification and Omitted Covariation
4.3.4 Covariance Matrix Estimation: Summary and Recommendations
4.4 Ex Ante Risk and VaR Methodologies
4.4.1 VaR Estimation Approaches
4.4.2 Enhanced HVaR
4.4.2.1 EHVaR Systematic Risk Methodology
4.4.2.2 EHVaR Idiosyncratic Risk Methodology
4.4.3 VaR Estimation: Summary
4.5 Introduction to Risk Decomposition
4.6 Alternative Approaches to Risk Decomposition
4.6.1 A Comparison of the Different Approaches
4.7 Risk Decomposition Using CTR
4.7.1 Security-Level Contributions and Aggregations
4.7.2 Factor-Level Contributions and Aggregations
4.7.3 Decomposing Contribution to Risk into Atomic Contributions
4.7.4 Decomposing Contribution to Risk into Exposure, Volatility, and Correlation
4.7.5 Decomposing Contribution to Risk Using ANOVA
4.8 Risk Decomposition Through Time
4.9 Risk Decomposition: Summary
Appendix A. EHVaR: Idiosyncratic Risk Estimation
Appendix B. EHVaR: Aggregation
Notes
Chapter 5 Market-Driven Scenarios: An Approach for Plausible Scenario Construction
5.1 Introduction
5.2 Implied Stress Testing Framework
5.2.1 Market-Driven Scenario Framework
5.2.2 Scenario Likelihood
5.2.3 From Likelihood to Probability
5.2.4 Decomposing the Scenario Z-Score
5.2.5 Specifying a Covariance Matrix
5.3 Developing Useful Scenarios
5.3.1 Scenario Definition
Step 1: Define a Market Event or Macro Regime
Step 2: Select Policy Variables
Step 3: Calibrate Shock Sizes to the Policy Variables
Step 4: Generate Nonpolicy Factor Shocks from the Policy Factor Shocks
Step 5: Generate Portfolio Stress Test P&L
5.4 A Market-Driven Scenario Example: Brexit
5.4.1 Describing Different Brexit Scenario Outcomes
5.4.2 Identifying Key Policy Shocks in Soft Brexit Scenario
5.5 Conclusion
Appendix: Decomposition of Scenario Z-score
Notes
Chapter 6 A Framework to Quantify and Price Geopolitical Risks
6.1 Introduction
6.2 Setting the Scene
6.2.1 Short and Sharp
6.2.2 Shades of Gray
6.3 BlackRock's Framework for Analyzing Geopolitical Risks
6.4 Global Trade Deep Dive
6.4.1 Calibrating the Shocks
6.5 What Is Already Priced In?
6.5.1 Is It Priced In?
6.5.2 Adjusted Impacts
6.5.3 Assessing Likelihood
6.5.4 Takeaways
6.6 Taking Action
6.6.1 Key Drivers
6.6.2 BGRI-Specific Assets
6.6.3 The Path Forward
6.7 Caveats and Cautions
Notes
Chapter 7 Liquidity Risk Management
7.1 Introduction
7.2 A BRIEF HISTORY OF LIQUIDITY RISK MANAGEMENT
7.3 A Fund Liquidity Risk Framework
7.4 Asset Liquidity
7.4.1 Importance of Data Modeling for Liquidity Risk Management
7.4.2 Asset Liquidity: Days-to-Liquidate
7.4.3 Asset Liquidity: Corporate Bond Transaction Costs (T-Costs)
7.5 Redemption Risk
7.5.1 Managing Redemptions and Outflow Risk
7.6 Liquidity Stress Testing
7.7 Extraordinary Measures
7.8 Fixed-income Data Availability Limitations
7.8.1 Modeling Asset Liquidity
7.8.1.0 Modeling Trading Volumes
7.8.1.0 Modeling Transaction Costs
7.8.1.0 Similarity and Localization of Models
7.8.2 Modeling Redemption-at-Risk
7.8.3 Modeling Liquidity Optimization
7.9 Conclusion
Notes
Chapter 8 Using Portfolio Optimization Techniques to Manage Risk
8.1 Risk Measurement Versus Risk Management
8.2 Typical Fixed-income Hedges
8.3 Parametric Hedging Techniques
8.4 Generalized Approach to Hedging
8.4.1 Hedging as Constrained Portfolio Optimization
8.4.2 Mathematical Formulation
8.4.2.1 Exposure Hedging
8.4.2.2 Managing a Portfolio Against a Benchmark
8.4.2.3 Stress Scenario Hedging
8.4.3 Examples of Optimized Risk Management Strategies
8.4.3.1 Creating an ESG Tilt While Managing a Fixed-Income Portfolio Relative to a Benchmark
8.4.3.2 Hedging Stress Scenario Exposure
8.5 Advanced Portfolio Optimization and Risk Management Techniques
8.5.1 Risk Budgeting/Parity
8.5.2 Going Beyond a Single Fund/Single Period in Portfolio Risk Management
8.5.2.1 Multi-Fund Portfolio Construction and Risk Management
8.5.2.2 Multi-Period Portfolio Construction and Risk Management
8.5.2.3 Risk Management Using Scenario Optimization
8.5.3 Example: Risk Budgeting for Factor-Based Investing
Notes
Chapter 9 Risk Governance
9.1 Introduction
9.2 Risk Scan Standard Framework
9.3 Risk and Performance Target (RPT) Framework
9.4 Governance
Notes
Chapter 10 Risk-Return Awareness and Behavioral Finance
10.1 Introduction
Deliberate, Diversified, and Scaled Risks
10.2 Portfolio and Risk Manager Partnership
10.3 Behavioral Risk Management for Fixed Income
10.4 Decision-making Analytics
10.4.1 Loss Aversion
10.4.1.1 The Disposition Bias
10.4.1.2 The Endowment Effect
10.5 Investment Process
10.5.1 Leveraging the Wisdom of the Crowds
10.5.2 Bolster System II Thinking
10.5.3 Facilitate Continuous Learning
10.6 Conclusion
Notes
Chapter 11 Performance Attribution
11.1 Introduction
11.2 Brinson Attribution and Beyond
11.2.1 Comparing Market Value Brinson Attribution to Beta-Adjusted Attribution
11.3 Factor-based Attribution
11.4 Equity Fundamental Factor-based Attribution
Notes
Chapter 12 Performance Analysis
12.1 Introduction
12.2 Performance Governance
12.3 Performance Metrics
12.3.1 Active Performance Measurement
12.3.1.1 Alpha Target Ratio
12.3.1.2 Weighted Peer Percentile
12.3.1.3 Strengths and Weaknesses of the ATR and Weighted Peer Percentile
12.3.1.4 Alpha Dollars
12.3.1.5 Strengths and Weaknesses of Alpha Dollars
12.3.2 Index Performance Metrics
12.3.2.1 Direct Tracking Basis Points (BP)
12.3.2.2 Strengths and Weaknesses of Direct Tracking BP
12.4 Conclusion
Notes
Chapter 13 Evolving the Risk Management Paradigm
13.1 Introduction
13.2 Traditional Buy-side Risk Management Framework
13.3 Evolving the IRMP: In Pursuit of Investment Risk Management at Scale
13.4 Risk Governance
13.5 Supporting Risk Governance Through Technology
13.6 Implementing a Risk Governance Framework Through Aladdin
13.7 Aladdin's Risk Radar Example
13.7.1 Aladdin's Risk Radar Overview
13.7.2 Rules and Portfolio Subscriptions
13.7.3 Exceptions and Tasks
13.7.4 Exception Classification
13.7.5 Risk Exception Reporting and Audit
13.7.6 What Is Next for Technology-Enabled Investment Risk Oversight?
13.8 Conclusion
Notes
Section II Fixed-Income Risk Management-Then and Now
Chapter 14 The Modernization of the Bond Market
14.1 Charting the Evolution of Bond Markets
14.1.1 The Current State of Bond Market Liquidity
14.1.2 The Modernization of Bond Market Structure
14.1.3 Continued Growth in Electronic Bond Trading
14.2 The Development of an Index-based Ecosystem
14.2.1 Fixed-Income ETFs: Continued Strong Growth and Adoption
14.2.2 Portfolio Trading and Fixed-Income ETFs
14.2.3 Continued Growth in Bond Index Derivatives Markets
14.2.4 Fixed-Income ETF Options
14.3 Implications for Investing, Portfolio Management, and Risk Management
14.3.1 Use Cases for Fixed-Income ETFs and Other Index Exposures
14.4 The Future State of Portfolio Construction
14.4.1 Portfolio Engineering and Construction
14.5 Conclusion
Notes
Chapter 15 The LIBOR Transition
15.1 Introduction
15.2 Implications to Portfolio and Risk Management
15.3 Shift from LIBOR to SOFR
15.4 Risk Management Impact and Coordination
15.5 Reflections on a Benchmark Reforms
Notes
Chapter 16 Derivatives Reform: The Rise of Swap Execution Facilities and Central Counterparties
16.1 The Call for Change: 2008 Global Financial Crisis
16.1.1 SEFs
16.1.2 CCPs
16.2 The Value of Derivatives in Fixed-income Portfolios
16.3 Trading Fixed-income Derivatives: The Rise of SEFs
16.4 Clearing Fixed-income Derivatives: The Rise of CCPs
16.5 CCP Risk Mitigation Techniques
16.5.1 CCP Risk Mitigation Techniques: What Could Go Wrong?
16.6 The Call for Change: Market Participants Ask for Stronger CCPs
16.7 Conclusion
Notes
Section III Lessons from the Credit Crisis and Coronavirus Pandemic
Chapter 17 Risk Management Lessons Worth Remembering from the Credit Crisis of 2007-2009
17.1 Introduction
17.2 The Paramount Importance of Liquidity
17.2.1 Price ? Intrinsic Value Unless Special Conditions Hold
17.2.2 Cash and Cash Flow Are the Only Robust Sources of Liquidity
17.2.3 Complexity and Opacity Matter More Than You Think
17.2.4 Collateralization Can Be a Two-edged Sword
17.2.5 Liquidity Is a Common Risk Factor
17.3 Investors in Securitized Products Need to Look Past the Data to the Underlying Behavior of the Assets
17.4 Certification Is Useless During Systemic Events
17.5 Market Risk Can Change Dramatically
17.6 The Changing Nature of Market Risk
17.7 By the Time a Crisis Strikes, It's Too Late to Start Preparing
17.8 Conclusion
Notes
Chapter 18 Reflections on Buy-Side Risk Management After (or Between) the Storms
18.1 Introduction
18.2 Risk Management Requires Institutional Buy-In
18.3 The Alignment and Management of Institutional Interests
18.4 Getting Risk Takers to Think Like Risk Managers
18.5 Independent Risk Management Organizations
18.6 Clearly Define Fiduciary Obligations
18.7 Bottom-up Risk Management
18.8 Risk Models Require Constant Vigilance
18.9 Risk Management Does Not Mean Risk Avoidance
Notes
Chapter 19 Lessons Worth Considering from the COVID-19 Crisis
19.1 Introduction
19.2 Background
19.3 Core Principles Underpinning Recommendations
19.4 March 2020: Capital Markets Highlights and Official Sector Intervention
19.5 COVID-19 Lessons: What Worked and What Needs to be Addressed
19.6 Recommendations to Enhance the Resilience of Capital Markets
19.6.1 Recommendations Regarding Bank Regulations
19.6.2 Recommendations Regarding Market Structure
19.6.2.1 Treasuries
19.6.2.2 Short-Term Markets
19.6.2.3 Fixed-Income Markets
19.6.2.4 Central Clearing Counterparties (CCPs)
19.6.2.5 Equities
19.6.2.6 Indices
19.6.2.7 Data
19.6.3 Recommendations Regarding Asset Management
19.7 Concerns with Macroprudential Controls
19.8 Conclusion
19.9 Postscript
Notes
Bibliography
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BlackRock's Guide to Fixed-Income Risk Management

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