the national institute of finance. did they know what was going on? did they have a choice?
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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
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