Macrofinancial Risk: Fundamental Concepts and the Current International

Context

Dale Gray

Monetary and Capital Markets Department

International Monetary Fund

Dgray@imf.org The views expressed in this presentation are those of the author and

should not be attributed to the International Monetary Fund, its Executive Board, or its management.

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Macrofinancial Risk Analysis

Framework integrates risk-adjusted balance sheets using Contingent Claims Analysis (CCA) with macroeconomic and monetary policy models

CCA models of financial institutions, corporates, and sovereigns are integrated together and with macroeconomic models

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Outline

Contingent Claims Analysis (CCA)

– CCA Models of Financial Institutions (Moody’sKMV)

– Credit Turmoil and Financial Stability Risks

Venezuelan Bank Sector Risk (MKMV)

Global Spillovers to EM Corporates and Banks

Based on papers by Dale Gray, Robert C. Merton and Zvi Bodie in: (i) JOIM 2007, (ii) NBER 2007; (iii) papers with Samuel Malone and new book on Macrofinance (2008); IMF GFSR 2008.

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Core Concept: Merton Model/CCA for Firms and Banks

Assets = Equity + Risky Debt

= Equity + Default-Free Debt – Expected Loss

= Implicit Call Option + Default-Free Debt – Implicit Put Option

Assets

Equity or Jr Claims

Risky Debt

• Value of liabilities derived from value of assets.• Liabilities have different seniority.• Randomness in asset value.

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CCA Credit Risk Measures

Asset Value

Exp. asset Distribution of Asset Valuevalue path

Distress Barrier or promised payments

V0

Time

Probability of Default

T

Distance toDistress: standard

deviations asset value is from debt distress

barrier

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Summary of CCA and Credit Risk Indicators

Value of Risky Debt, D (A= asset, σ=asset volatility B=distress barrier, P=implicit put option)

Default Probability

Risk Neutral DP

Estimated Actual DP

2 0 1( ( ) ( ))rt rt

Risky Debt Default free value Put Option

Be Be N d A N d

20

2

ln2

Af

A

Ar t

Bd

t

1 2 Ad d t

2( )N d *

2 2( ) ( )N d N d t

1ln 1 *Risk Neutral Risk NeutralEICDS LGD EDF

T

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Calibrating Implied Assets and Asset VolatilityImplied asset value and implied asset volatility calibrated from contingent claims analysis.

Merton Model

Moody’s-KMV for firms and financial institutions

Merton-type CCA or hybrid models have been applied to corporates and financial institutions. Moody’sKMV, Kamakura and others have applied these models for credit risk analysis to tens of thousands of firms and banks in over 50 countries around the world.

Sovereign CCA uses local currency liabilities and debt structure to imply sovereign assets and asset volatility, used to then get risk indicators such as spreads on foreign and local currency sovereign debt, default probabilities (MfRisk has been applied to 22 countries).

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Calibrate (Unobservable) Market Value of Asset and Implied Asset Volatility

INPUTS

Value and Volatility of Market Capitalization, E

Debt Distress Barrier B (from Book Value)

Time Horizon

USING TWO EQUATIONS WITH TWO UNKNOWNS

Gives:

Implied Asset

Value A and

Asset Volatility A

Default Probabilities

Spreads, Risk Indicators

)()( 21 dNBedNAE rt

)( 1dNAE AE

KMV maps risk indicators to actual default probabilities (EDFs) using historical default data

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Using CCA MKMV Models to Analyze the Global Crisis

Overview of subrime and related losses

Sharp increases in spreads of banks with and without subprime exposure

Drivers of increased default probabilites for banks in US and Europe

How changes in global risk appetite contribute to higher credit spreads for banks worldwide

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Broad credit deteriorationBroad credit deterioration, a weaker U.S. , a weaker U.S. economy,economy, and and financial deleveraging have financial deleveraging have boosted potential lossesboosted potential losses......

Estimates of Potential Write-downs to Holders of U.S-Issued Securitized and Unsecuritized Debt

Leveraged loans

Corporate credit

Consumer credit

Commercial real estate

Prime residential real estate

Non-prime residential real estate

25%

56%

4%

8% 4%

2%

(March 08, $945 billions)

Source: IMF GFSR 2008

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CDS for Banks and Investment BanksCDS for Banks and Investment Banks

0

50

100

150

200

250

300

Jul Sep Nov Jan Mar

Citigroup

JP Morgan

Barclays

Deutsche Bank

UBS

Credit Suisse

0

100

200

300

400

500

600

700

800

Jul Sep Nov Jan Mar

Bear Stearns

Merrill Lynch

Lehman

Goldman Sachs

Morgan Stanley

Banks(5-year CDS spreads in basis points)

Investment Banks(5-year CDS spreads in basis points)

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MKMV EDF Implied CDS Spreads (EICDS) and Market CDS Spreads for Groups of Banks

Banks with Subprime Exposure/Losses

Banks without Subprime Exposure/Losses

Banks with subprime exposure have higher spreads

0

20

40

60

80

100

120

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160

180

200

1/3/

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/06

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/07

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EICDS

Market CDS

0

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EICDS

Market CDS

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Key Drivers of EDF and EICDS (EDF implied CDS)

1ln 1 *Risk Neutral Risk NeutralEICDS LGD EDF

T

1,( )Risk Neutral A MktEDF N N EDF SR T

( , , )Mkt Leverage AssetEDF f L otherEDF Key Drivers are Market Leverage and Asset Volatility

Key Drivers of credit spreads, EICDS, are (EDF, Market Sharpe Ratio (SR), correlation ρ of bank assets with

market) and Loss Given Default

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Trends in Banks’ Market Leverage and Asset Volatility

Banks with Subprime Exposure/Losses:

Market Leverage and Asset Volatility Both Increasing

Banks without Subprime Exposure/Losses:

Market Leverage Increasing but Asset Volatility Decreasing

This analysis was done by Andrea Maechler

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2.2

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2.8

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Asset volatility(% left scale)

Market Leverage(% rightscale)

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Asset volatility(% left scale)

Market Leverage(% rightscale)

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Significantly Higher Market Sharpe Ratio since July 2007 to Peak in March 2008, still high Now

Market Sharpe Ratio and other indicators show decreased global risk appetite

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Changes in Bank CDS due to Leverage, Volatility and Impact of Increase in Market Price of Risk as of March 20, 2008

(Lower Risk Appetite, Higher Correlation)

With Subprime Exposure/Loss

Without Subprime Loss

CDS January 2007

18 20

Increased Market Leverage

+52 +45

Change in Volatility

+41 +10

Market Price of Risk Increase (SR*ρ)

+75 +70

CDS March 2008

190 bps 145 bps

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US Banks: Economic Capital Ratios with Low and High Market Price of Risk

0

50

100

150

200

250

300

0 0.1 0.2 0.3 0.4

Capital Ratio (Equity/Mkt Value of Assets)

Cre

dit

Sp

read

(B

asis

poi

nts

)

Lower Market Priceof Risk

Higher Market Priceof Risk

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Interbank spreads have widened since July 2007, in three different “spikes”

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Application of CCA MKMV Model to Venzuelan Banks

Default probailities, market leverage, and asset volatility for banking sector in Venzuela

Comparison to USA and Europe

Scenarios

– Lower global risk appetite

– Shock with lower equity, higer volatility

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Venezuelan banks default probabilities (EDF, 1 yr) 2003-2008

0,01

0,1

1

10

25% EDF(%)

50% EDF(%)

75% EDF(%)

Median for all banks; 75% Quartile; and 25% Quartile

Source: MKMV

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0

2

4

6

8

10

12

14

25% ASSETVOLATILITY(%)

50% ASSETVOLATILITY(%)

75% ASSETVOLATILITY(%)

Venezuelan banks asset volatility 2003-2008

Median for all banks; 75% Quartile; and 25% Quartile

Source: MKMV

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40

50

60

70

80

90

100

25% MKT LEVERAGE(%)

50% MKT LEVERAGE(%)

75% MKT LEVERAGE(%)

Venezuelan banks market leverage (debt divided by assets) 2003-2008

Median for all banks; 75% Quartile; and 25% Quartile

Source: MKMV

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Median EDF for Venezuelan Banks slightly higher than US banks which are slightly higher than EU banks

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Highest one-fourth of banks in Venezuela and US have similar default probabilities (EDF), EU slightly lower

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EDFs for Venezuelan Corporates (median, 75% quartile, and 25% quatile) slight increase since 2007

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Spillovers to Emerging Markets (EM) Banks and Corporates

EM banks’ spreads up somewhat, lower global risk appetite is a contributing factor

Certain EM banks, dependent on foreign financing, under strain (e.g. Iceland)

Sharp dropoff in EM corporate bond issuance

EM corporate spreads up, global risk appetite is a factor

Is the credit turmoil leading to reductions in credit to EM corporate and rise in borrowing cost that will have long term effects?

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Emerging Market Bank External Bond Issuance is Down

0

5

10

15

20

25

30

35

40

Q105 Q205 Q305 Q405 Q106 Q206 Q306 Q406 Q107 Q207 Q307 Q407 Q108

LatamEMEAAsia

Emerging Market Bank External Bond Issuance (US$ bn)

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EM Bank Spreads

EM Bank CDS (bps)

0

200

400

600

800

1000

1200

Kazakhstan Banks Icelandic Banks

EM Sovereign CDS

Asian Banks

Russian Banks

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EM Corporate Bond Issuance Down and EM Corporate Bond Issuance Down and EM Corporate Spreads UpEM Corporate Spreads Up

0

5

10

15

20

25

30

35

Q106 Q206 Q306 Q406 Q107 Q207 Q307 Q407 Q108

Asia

EMEA

Latam

100

150

200

250

300

350

400

450

Jan-07 Apr-07 Jul-07 Oct-07 Jan-08

Asia

EMEA

Latin

EM Private Sector Bond Issuance(In billions of U.S. dollars)

EM Corporate Spreads (In basis points)

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Rough Estimates of Drivers of Emerging Market (EM) Banks and (EM) Corporate Credit Spreads

EM Banks EM Corporates

Credit Spreads January 2007

100 170

Increased Market Leverage

+10 +20-50?

Change in Volatility

+10 + 20-50?

Mkt Price of Risk Increase*

+55 +40-80?

Credit Spreads January 2008

175 bps 320 bps

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Thank you, More information see:

Papers by D. Gray, Robert C. Merton, Zvi Bodie:

NBER 12637 (2006)

NBER 13607 (2007)

Sovereign Credit Risk, JOIM v. 5, no. 4, Dec 2007

IMF Global Financial Stability Report (GFSR)

IMF Working Papers: WP 05/155, 04/121, 07/233, Indonesia SIP (2006), Gray and Walsh (WP 08/89), Gray, Lim, Loukoianova, Malone (WP/08), IMF Staff Papers Gapen et. al v 55 #1 2008; Framework for Integrating Macroeconomics and Financial Sector Analysis by Gray, Karam, Malone, N’Diaye (forthcoming)

Macrofinancial Risk Analysis, Gray and Malone (Wiley Finance book Foreword by Robert Merton)