Macrofinancial Risk Analysis

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.

Autorentext

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.

Zusammenfassung
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.

Inhalt

Foreword xv

Preface xix

1 Introduction 1

Part I Overview of Finance, Macroeconomics, and Risk Concepts 7

2 An Overview of Macroeconomics, and Why the Theory of Asset Pricing and Contingent Claims Should Shape its Future 9

2.1 An overview of macroeconomics 10

2.2 How uncertainty is incorporated into macroeconomic models 13

2.3 Missing components in macro models: balance sheets with risk, default, and (nonlinear) risk exposures 15

2.4 Asset-pricing theory, financial derivatives pricing, and contingent claims analysis 17

2.5 Autoregression in economics vs. random walks in finance 19

2.6 Asset price process related to a threshold or barrier 21

2.7 Relating finance models and risk analytics to macroeconomic models 23

2.8 Toward macrofinancial engineering 24

2.9 Summary 25

References 26

3 Macroeconomic Models 29

3.1 The HicksHansen IS-LM model of a closed economy 29

3.2 The MundellFleming model of an open economy 33

3.3 A dynamic, stochastic, five-equation, small open economy macro model 38

3.4 Summary 42

References 42

4 Stochastic Processes, Asset Pricing, and Option Pricing 43

4.1 Stochastic processes 43

4.2 Itô's lemma 46

4.3 Asset pricing: ArrowDebreu securities and the replicating portfolio 47

4.4 Put and call option values 48

4.5 Pricing the options using the BlackScholesMerton formula 50

4.6 Market price of risk 52

4.7 Implications of incomplete markets for pricing 54

4.8 Summary 55

Appendix 4A Primer on relationship of put, call, and exchange options 55

Appendix 4B Physics, Feynman, and finance 57

References 57

5 Balance Sheets, Implicit Options, and Contingent Claims Analysis 59

5.1 Uncertain assets and probability of distress or default on debt 59

5.2 Probability of distress or default 60

5.3 Debt and equity as contingent claims 61

5.4 Payoff diagrams for contingent claims 62

5.5 Understanding why an implicit put option equals expected loss 63

5.6 Using the Merton model and BlackScholesMerton formula to value contingent claims 64

5.7 Measuring asset values and volatilities 68

5.8 Estimating implied asset value and asset volatility from equity or junior claims 68

5.9 Risk measures 71

5.10 Summary 72

References 72

6 Further Extensions and Applications of Contingent Claims Analysis 73

6.1 Extensions of the Merton model 73

6.2 Applications of CCA with different types of distress barriers and liability structures 74

6.3 Risk-adjusted and actual probabilities using the market price of risk, Sharpe ratios, and recovery rates 78

6.4 Moody's-KMV approach 80

6.5 CCA using skewed asset distributions modeled with a mixture of lognormals 81

6.6 Maximum likelihood methods 84

6.7 Incorporating stochastic interest rates and interest rate term structures into structural CCA balance sheet models 85

6.8 Other structural models with stochastic interest rates 86

6.9 Summary 87

Appendix 6A Calculating parameters in the Vasicek model 87

References 88

Part II the Macrofinance Modeling Framework 91

7 The Macrofinance Modeling Framework: Interlinked Sector Balance Sheets 93

7.1 Contingent claim balance sheets for sectors 93

7.2 Measuring asset values and volatilities 98

7.3 Measuring risk exposures 100

7.4 Linkages in a simple four-sector framework 100

7.5 Integrated value and risk transmission between sectors 101

7.6 Policy effectiveness parameters in implicit options 105

7.7 Advantages of an integrated balance sheet risk approach 106

7.8 Summary 106

References 107 8 The Macrofinance Modeling Framework: A Closer Look at the Sovereign CCA Balance Sheet 109&...