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Macrofinancial Risk Analysis

ISBN: 978-0-470-05831-2
362 pages
April 2008
Macrofinancial Risk Analysis (0470058315) cover image
Macrofinancial risk analysis


Dale Gray and Samuel Malone


Macrofinancial Risk Analysis provides a new and powerful framework with which policymakers and investors can analyze risk and vulnerability in economies, both emerging market and industrial. Using modern risk management and financial engineering techniques applied to the macroeconomy, an economic value can be placed on the risks posed by inter-linkages between sectors, the risk of default of different sectors on their outstanding debt obligations quantified, and the value ex-ante of guarantees to private sector entities by the government calculated. This book guides the reader through the basic macroeconomic and financial models necessary to understand the framework, the core analytical tools, and more advanced contributions that will be of interest to researchers. This unique synthesis of ideas from finance and macroeconomics offers several original contributions to the theory of financial crises, as well as a range of new policy options for governments interested in achieving a better tradeoff between economic growth and macro risk.
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Foreword

Preface

1 Introduction

PART I OVERVIEW OF FINANCE, MACROECONOMICS, AND RISK CONCEPTS

2 A Brief History of Macroeconomics, and Why the Theory of Asset Pricing and Contingent Claims Should Shape its Future

2.1 A brief history of macroeconomics

2.2 How uncertainty is incorporated into macroeconomic models

2.3 Missing components in macro models: balance sheets with risk, default and (nonlinear) risk exposures

2.4 Asset pricing theory, financial derivatives pricing and contingent claims analysis

2.5 Autoregression in economics vs. random walks in finance.

2.6 Asset price process related to a threshold or barrier

2.7 Relating finance models and risk analytics to macroeconomic models

2.8 Toward macrofinancial engineering

2.9 Summary

References

3 Macroeconomic Models

3.1 The Hicks–Hansen IS-LM model of a closed economy

3.2 The Mundell–Fleming model of an open economy

3.3 A dynamic, stochastic, five-equation small open economy macro model

3.4 Summary

References

4 Stochastic Processes, Asset Pricing, and Option Pricing

4.1 Stochastic processes

4.2 Itô’s lemma

4.3 Asset pricing: Arrow–Debreu securities and the replicating portfolio

4.4 Put and call option values

4.5 Pricing the options using the Black–Scholes–Merton formula

4.6 Market price of risk

4.7 Implications of incomplete markets for pricing

4.8 Summary

Appendix 4A Primer on relationship of put, call, and exchange options

Appendix 4B Physics, Feynman, and finance

References

5 Balance Sheets, Implicit Options, and Contingent Claims Analysis

5.1 Uncertain assets and probability of distress or default on debt

5.2 Probability of distress or default

5.3 Debt and equity as contingent claims

5.4 Payoff diagrams for contingent claims

5.5 Understanding why an implicit put option equals expected loss

5.6 Using the Merton model and Black–Scholes–Merton formula to value contingent claims

5.7 Measuring asset values and volatilities

5.8 Estimating implied asset value and asset volatility from equity or junior claims

5.9 Risk measures

5.10 Summary

References

6 Further Extensions and Applications of Contingent Claims Analysis

6.1 Extensions of the Merton model

6.2 Applications of CCA with different types of distress barriers and liability structures

6.3 Risk adjusted and actual probabilities using the market price of risk, Sharpe ratios, and recovery rates

6.4 Moody’s-KMV’s approach

6.5 CCA using skewed asset distributions modeled with a mixture of lognormals

6.6 Maximum likelihood methods

6.7 Incorporating stochastic interest rates and interest rate term structures into structural CCA balance sheet models

6.8 Other structural models with stochastic interest rates

6.9 Summary

Appendix 6A Calculating parameters in the Vasicek model

References

PART II THE MACROFINANCE MODELING FRAMEWORK

7 The Macrofinance Modeling Framework: Interlinked Sector Balance Sheets

7.1 Contingent claim balance sheets for sectors

7.2 Measuring asset values and volatilities

7.3 Measuring risk exposures

7.4 Linkages in a simple four-sector framework

7.5 Integrated value and risk transmission between sectors

7.6 Policy effectiveness parameters in implicit options

7.7 Advantages of an integrated balance sheet eiskapproach

7.8 Summary

References

8 The Macrofinance Modeling Framework: A Closer Look at the Sovereign CCA Balance Sheet

8.1 CCA balance sheet for the government and monetary authorities

8.2 Sovereign distress

8.3 Calculating implied sovereign assets and implied sovereign asset volatility using CCA for the public sector balance sheet

8.4 Applications of the macrofinancial risk framework to sovereigns

8.5 Sovereign risk-neutral and estimated actual default probabilities on foreign-currency-denominated debt

8.6 Spreads on sovereign foreign currency and local currency debt

8.7 Breaking down sovereign assets into key components

8.8 Risk-based scenario and policy analysis using calibrated sovereign CCA related to spreads on foreign currency debt

8.9 Short-term and long-term government CCA balance sheets with monetary authority

8.10 Summary

Appendix 8A Value and volatility of local currency liabilities and base money

References

9 The Macrofinance Modeling Framework: Linking Interest Rate Models in Finance and Macroeconomics

9.1 Overview of interest rate term structure models in finance

9.2 Two early theories: liquidity preference and the market for loanable funds

9.3 Monetary policy, Taylor rules, and interest rates

9.4 Reconciling different perspectives on interest rate behavior

9.5 What to do when the monetary authority is linked closely to the government balance sheet

9.6 Summary

References

10 Macrofinance Modeling Framework: Financial Sector Risk and Stability Analysis

10.1 Calculating risk indicators for individual banks or financial institutions

10.2 Time series of financial system risk indicators

10.3 Snapshot of system risk

10.4 Expected loss as a portfolio of implicit put options

10.5 Using a structural Merton model with stochastic interest rates for capital adequacy estimates

10.6 Factor model to assess key drivers of system risk and for scenario analysis

10.7 Multifactor risk analysis using copulas

10.8 Household balance sheet risk

10.9 Linking banking sector loans to corporate, household, and other borrowers

10.10 Foreign-currency-denominated loans and the impact of the presence of foreign banks on banking system risk

10.11 Financial stability indicators for links to macro models

10.12 Summary

Appendix 10A CCA model for banks and borrowers with foreign-currency-denominated debt and lending spreads based on credit risk

References

11 Macrofinancial Modeling Framework: Extensions to Different Exchange Rate Regimes

11.1 Floating exchange rate regimes, interest rates, and the sovereign balance sheet

11.2 Fixed exchange rate regimes, interest rates, and the sovereign balance sheet

11.3 The impact of capital flows on the CCA sovereign balance sheet

11.4 Role of quasi-public entities in exchange rate management

11.5 Summary

References

PART III LINKING MACROFINANCIAL AND MACROECONOMIC FRAMEWORKS

12 Sovereign Reserve, Debt, and Wealth Management from a Macrofinancial Risk Perspective

12.1 Reserves adequacy and asset allocation: moving from simple rules to a national framework

12.2 CCA for a firm with a subsidiary and its wealth management

12.3 Constructing contingent claim balance sheets for the national economy

12.4 Macro risk and wealth management

12.5 Summary

References

13 Macrofinancial Modeling Framework: Relationship to Accounting Balance Sheets and the Flow of Funds

13.1 Economy-wide macro contingent claim balance sheets and risk exposures

13.2 Recovering traditional macroeconomic budget constraints and flow identities from CCA valuation equations when volatility is zero

13.3 Inter-linkages between CCA balance sheets, flows, and risk premiums

13.4 Using the production function to link corporate and household assets

13.5 Macrofinance, macroeconomic flows, and the business cycle

13.6 Summary

Appendix 13A Cross-holding by households and financial sectors of contingent claims in other sectors

Appendix 13B Contingent claim values and returns of different sectors

References

14 Macrofinancial Risk Framework Linked to Macroeconomic Models

14.1 Adding risk analytics to the spectrum of macroeconomic models

14.2 The Mundell–Fleming model and default risk

14.3 Linking macrofinance outputs to DSGE models

14.4 Linking macrofinance outputs to dynamic, stochastic macroeconomic

14.5 Linking macrofinance outputs to macroeconometric VAR models

14.6 An integrated policy framework

14.7 Summary

References

PART IV CRISIS AND DISTRESS IN ECONOMIES

15 Macroeconomic Models vs. Crisis Models: Why Nonlinearity Matters

15.1 Recent financial crises and crisis models

15.2 Summary

References

16 Sensitivity Analysis, Destabilization Mechanisms, and Financial Crises

16.1 Sensitivity analysis, the “Greeks”, and the valuation multiplier effect

16.2 The volatility leverage effect

16.3 Feedback between the forward rate and domestic interest rates on local currency debt

16.4 Feedback between local currency debt issuance and local currency spreads in the presence of contingent liability constraints

16.5 Summary

References 17 The Case of Thailand 1996-1999

17.1 Background

17.2 A macrofinance analysis of the Thai crisis

17.3 Scenario analysis

17.4 Summary

Appendix 17.A Banking and corporate sector risk analysis with scenarios

References

18 The Brazil Crisis of 20022003

18.1 Background

18.2 A macrofinance analysis of the Brazil crisis

18.3 Summary

References

PART V MACROFINANCIAL MODEL APPLICATIONS AND ANALYTICAL ISSUES

19 International Shocks, Risk Transmission, and Crisis Prevention

19.1 Changing global environment and global risk

19.2 Types of global shocks and the interaction with macrofinancial risk models

19.3 The international financial system and crisis prevention

19.4 Structuring an effective risk management hierarchy from the international level down to the country authorities

19.5 Summary

References

20 Macro Risk Management: Ways to Mitigate, Control, and Transfer Risk in the Economy

20.1 Overview of ways to manage risk

20.2 Direct change in financial structure

20.3 Risk transfer

20.4 Management of guarantees

20.5 Longer term risk management via institutional and policy change

20.6 Summary

References

21 Integrated Framework for Corporate and Sovereign Relative Value and Capital Structure Arbitrage

21.1 Capital structure arbitrage for firms and financial institutions

21.2 Credit and equity cycles

21.3 Sovereign capital structure relative value

21.4 Summary

References

22 Conclusion and New Directions for Macrofinance

22.1 Summary of conceptual issues

22.2 The roadmap for an integrated contingent claims analysis-macroeconomic model

Appendix A The Mundell-Fleming Model with Default Risk

A.1 The market for loanable funds

A.2 Some properties of the IS-LM-BP-RP model

A.3 Monetary and fiscal policy

A.4 Effect of changes in μ and σ on equilibrium

Index

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Dr. DALE GRAY is the Senior Risk Expert in the Monetary and Capital Markets Department of the International Monetary Fund (IMF). He is founder and President of Macro Financial Risk, Inc. (Mf Risk) a pioneer in the application of risk management tools to economies (board members include Robert Merton and Zvi Bodie). He has worked for investment banks, hedge funds, Moody’s Investors Service, IMF, World Bank, IFC as well as advising governments on macro risk analysis, management of sovereign wealth funds, and the design of risk mitigation strategies. He has worked on over thirty countries, is a frequent lecturer with numerous publications. He has a Ph.D. from MIT, MS from Stanford and is a certified Financial Risk Manager.

Dr. SAMUEL W. MALONE is a professor of finance at the IESA, a business school in Caracas, and director of ProAlea, Inc., a risk and strategy consultancy based in Latin America.  He holds a doctorate in economics from the University of Oxford, UK, and undergraduate degrees in mathematics and economics from Duke University, where he graduated Phi Beta Kappa with summa cum laude Latin honors. Elected to attend Oxford as a Rhodes Scholar representing the United States, Malone is also a four-time winner of the international Mathematical Contest in Modeling, an intensive problem-solving competition in which participants devise and write up solutions to real-world problems chosen by experts in government and industry. Author of several articles in applied mathematics and economics, he has consulted for the International Monetary Fund and the Inter-American Development Bank in Washington, DC.

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