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.

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.

Foreword
Preface
Introduction
Overview Of Finance, Macroeconomics, And Risk Concepts
A Brief History of Macroeconomics, and Why the Theory of Asset Pricing and Contingent Claims Should Shape its Future
A brief history of macroeconomics
How uncertainty is incorporated into macroeconomic models
Missing components in macro models: balance sheets with risk, default and (nonlinear) risk exposures
Asset pricing theory, financial derivatives pricing and contingent claims analysis
Autoregression in economics vs. random walks in finance
Asset price process related to a threshold or barrier
Relating finance models and risk analytics to macroeconomic models
Toward macrofinancial engineering
Summary
References
Macroeconomic Models
The Hicks-Hansen IS-LM model of a closed economy
The Mundell-Fleming model of an open economy
A dynamic, stochastic, five-equation small open economy macro model
Summary
References
Stochastic Processes, Asset Pricing, and Option Pricing
Stochastic processes
Ito's lemma
Asset pricing: Arrow-Debreu securities and the replicating portfolio
Put and call option values
Pricing the options using the Black-Scholes-Merton formula
Market price of risk
Implications of incomplete markets for pricing
Summary
Primer on relationship of put, call, and exchange options
Physics, Feynman, and finance
References
Balance Sheets, Implicit Options, and Contingent Claims Analysis
Uncertain assets and probability of distress or default on debt
Probability of distress or default
Debt and equity as contingent claims
Payoff diagrams for contingent claims
Understanding why an implicit put option equals expected loss
Using the Merton model and Black-Scholes-Merton formula to value contingent claims
Measuring asset values and volatilities
Estimating implied asset value and asset volatility from equity or junior claims
Risk measures
Summary
References
Further Extensions and Applications of Contingent Claims Analysis
Extensions of the Merton model
Applications of CCA with different types of distress barriers and liability structures
Risk adjusted and actual probabilities using the market price of risk, Sharpe ratios, and recovery rates
Moody's-KMV's approach
CCA using skewed asset distributions modeled with a mixture of lognormals
Maximum likelihood methods
Incorporating stochastic interest rates and interest rate term structures into structural CCA balance sheet models
Other structural models with stochastic interest rates
Summary
Calculating parameters in the Vasicek model
References
The Macrofinance Modeling Framework
The Macrofinance Modeling Framework: Interlinked Sector Balance Sheets
Contingent claim balance sheets for sectors
Measuring asset values and volatilities
Measuring risk exposures
Linkages in a simple four-sector framework
Integrated value and risk transmission between sectors
Policy effectiveness parameters in implicit options
Advantages of an integrated balance sheet eiskapproach
Summary
References
The Macrofinance Modeling Framework: A Closer Look at the Sovereign CCA Balance Sheet
CCA balance sheet for the government and monetary authorities
Sovereign distress
Calculat
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Macrofinancial Risk Analysis

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