The National Institute of Finance

Did they know what was going on? Did they have a choice?

Exposed to Lehman Brothers –Owned $785M Lehman bonds

‘Broke the Buck’ Share price cut to 97¢

$2 Trillion Market

Exposed to Lehman Brothers –Owned $785M Lehman bonds

‘Broke the Buck’ Share price cut to 97¢

$2 Trillion Market

“If this crisis has taught us anything, it has taught us that risk to our system can come from almost any quarter. We must be able to look in every corner and across the horizon for dangers and our system was not able to do that.” Secretary Geithner, opening remarks, testimony to Senate Banking Committee, June 18, 2009.

New equilibrium below full production

Disruption of access to credit

Punishing the system, not the firm

$3T CDS Notional outstanding

$3T CDS Notional outstandingAIG goes down, who else goes?

$185b Gov. Loans

Portfolio insurance, trading strategy – Mimic put option, sell stock in decline

Rating Agency Arbitrage + Mortgage market decline = Toxic Assets

Stressed firms sell assets (adjust balance sheet)

Contagion I - Market (Liquidity) failure, firms sell new assets and stress new markets

Contagion II - Market panic and there are runs on markets

Hysteresis - Long term freezing of markets

What is the correlation?

Hunt Brothers ‘cornered’ Silver market • 1980 controlled 1/3 of world silver• Family fortune of $5b• Margin requirements were changed• Price dropped 50% on March 27, 1980

$21.62 $10.80

Hunt Brothers ‘cornered’ Silver market • What else did the Hunt Brother’s own?

Fire sale in silver Liquidity dried up Fire sale in cattle Correlations driven by?

The Russian Financial Crisis• 1998 Long Term Capital Management

Small exposure to Russian debt Large leveraged exposure to Danish debt

The Russian Financial Crisis• 1998 Long Term Capital Management

Russia defaulted 1998 Holders of Danish debt hit by default Fire sale in Danish debt LTCM connected to everyone

The Credit Crisis• Citibank’s exposure to CP Market?

The Credit Crisis• Citibank’s exposure to CP Market?

Off balance sheet, obligation to provide short term financing to SIVs Citi had invented and formed.

The Credit Crisis• Citibank’s exposure to MBS Market?

SIVs bankruptcy remote – have to sell when in trouble and what did they own – MBS ‘Toxic Assets’

Confidence in the market is gone, no-one knows who is solvent

Flight to quality (US Treasury), credit markets freeze

How long can companies ‘hold their breath’?

The Economy is ‘path dependent’

Experiment

RepeatExperiment

Predicting Fire Sales• Leverage of System• Liquidity Capacity

Velocity, depth of trading Capacity for bargain hunting

• Linkages – Book Correlation

Loss Distribution• Tail events are rare – very little data• Typically strong model assumptions

Loss Distribution• Tail events are rare – very little data• Typically strong model assumptions• Liquidity Failures

Can’t hedge No replicating portfolios Mean & Variance Game Theory

We are not in Kansas anymore

Loss Distribution• Tail events are rare – very little data• Typically strong model assumptions• Liquidity Failures• Scenario Analysis

Linkages – rights, obligations (Not Netting!) Granular Macro Economics Understanding Domino Risk

Loss Distribution• Tail events are rare – very little data• Typically strong model assumptions• Liquidity Failures• Scenario Analysis• Economic Impact

CaR – Credit at Risk DoL – Distribution of Loss

Monitoring health of Economy Regime shifting models Summaries reflecting stress

Historical data Derivatives data

Looking for Black Swans Leverage measures Concentrations, Bubbles Liquidity capacity Linkages and Transparency

Not predicting cascading failures

Determine loss by counterparty

Do not predict probability of failure of counterparties

Do not account for Linkages

Legal authorities must be strengthened

Regulators must understand the network

Regulators must understand aggregation

Regulators are ‘outgunned’

Exchanges and Clearing Houses• Increase Liquidity• Concentrate Risk

System views with existing resources• Historical Data • Market Data• Firm Risk Systems

Data Transparency

• Reference Data – Legal entities Product descriptions (Prospectus, Cash-flows, …) Details that ‘fit into’ a model

• Transactions/Price Data – Exchange, Clearing House, OTC (like TRACE) Position (Trading Book) data Essential for calibrating models

Model Transparency

• Price a complex OTC (How many can price?)

Model Transparency

• Getting a 2nd opinion

Model Transparency

• Getting a 2nd opinion• Building an active research community

Banks are not doing long-term research Regulators have limited efforts Academics have hard time getting data and

funding

Model Transparency

• Getting a 2nd opinion• Building an active research community• Current research efforts are incomplete

Models under stress/Transition to new equilibrium

Are markets complete (hedge-able)? National Weather Service equivalent? Competitive modeling environment (multiple

Hurricane models).

Proposed by concerned citizens

Part of regulatory reform legislation

Collect system-wide transaction data

Develop analytic tools

Part of the Federal Government

Protect data at highest level of security

Metrics to monitor risk – early warning

NTBS – post-mortum investigations

Is it feasible?

Market participants are close

Prototypes-Reference Data-Systemic Model (MBS)

Internal Systems (All Obligation)-Reference Data-Reporting Language

Hedge Fund Risks-Hedge Fund Counter-party network-Hedge Fund wide risk assessment

www.ce-nif.org