May, 2010 J. Rizzi, CapGen Financial (jrizzi@capgen)

1. Presentation to: Risk Minds 2010 Behavioral Basis of the Market Crisis May, 2010 J. Rizzi, CapGen Financial (jrizzi@capgen.com) (The ideas expressed herein are those of the author and not CapGen Financial)

2. Gregory Zuckerman despite sophisticated models mapping past behavior they lacked understanding of human behavior - they need to go beyond statistics of past and include psychology of people effect as at their foundation markets are people and the people effect increases uncertainty reminding us numbers alone are never enough

3. The Setting

4. US Dollar LIBOR-OIS SPREADS (Source: Malcom Knight, Rebuilding the Global Architecture of Financial Regulation, March, 2009) (How many standard deviations is this?…) (…Who cares?)

5. What Happened? (Do you want to believe what you see..) INVESTORS: extrapolated and believed housing prices would not fall Government Monetary Policy Monitoring CRA Regulatory capture Incentives: unintended consequences Risk intermediation reduces risk oversight (originate to distribute model) Too big too fail (TBTF) socialize losses Principal/Agent: management captured by employees Underwriters: Too big to manage resulted in governance breakdown Rating Agencies: Regulatory enforced oligopoly Diversification substitution Knowledge Systemic for Idiosyncratic Risk Pseudo objectivity: math without history equals disaster (…Or what I am telling you?)

6. Structured Finance (Structured finance as a compensation scheme….) Issues: Structure vs. Underlying Substitute systematic for diversifiable risk: default risk on adverse states Ignored joint payoff distributions Incorrect Gaussian Copula methodology: correlation Lacked sufficient historical data on new underlying asset class: they extrapolated on a limited sample based on good times Mispriced: put on real estate index earn 3X more Moral Hazard: perfect moral hazard product for issuers, underwriters, rating agencies and investors Covering up strategic decline with Tail Risk Up to 60% of large bank revenues in 2006 came from structured finance (…disguised as a business)

7. The Problem (Economic Capital is a lighthouse….) • Guided by selective memories and information • Fail to consider what we believe to be false • Influenced by the actions of others • Confuse preferences with prediction • Engage in self serving attribution • Disregard non-conforming views (… for the soon to be shipwrecked)

8. Some Behavioral Effects in Risk Management (Risk Management is the fig leaf …) • Hindsight and Confirmation: I knew it all along and ignore nonconforming evidence • Anchoring: Unduly influenced by first impressions • Sunk Costs: Doubling down • Overconfidence: Infallibility of judgment. Gives raise to illusions of control • Optimism: It will work out • Availability: More weight given to events easily recalled • Threshold: Once frequency drops below threshold it is ignored • Pattern Seeking: Fooled by randomness. Gamblers fallacy (… behind which risk taking takes place)

9. Risk and Uncertainty (Those whom the gods wish to destroy….) Issue: Can you reduce future to quantifiable risks calculated from existing data? Battling Beliefs – history as data and future as output Ergodic – future is statistical shadow of past Nonergodic – path dependent – history matters Uncertainty vs. Risk – the future is uncertain not just risky Risk – calculate odds of game Uncertainty – game changes Result – subjective beliefs of uncertain future Cannot calculate probability of rare events based on past Exposure vs. experiences Consequence: illusion of control based on flawed risk models (…they first teach math)

10. (Source: N. Taleb) (We observe the data….) A MAP on the Limits of Statistics Physical Sciences 1 2 Normal (risk) Considerations: Distributions and payoffs Distribution 3 4 Social Sciences Fat tails/unknown (uncertainty) Simple Complex Payoffs Quadrant 4: Normal techniques fail. Alternatives to consider: Redundancy not optimization Avoid predication: focus on discipline and resiliency Time horizon is longer Moral Hazard: bonuses tied to hidden risks Metrics: standard metrics no longer work Volatility absence is not equal to risk absence Risk numbers are dangerous: framing (…not the process)

11. Humans and Markets (In physics you play against God….) Markets and Hurricanes: they are different (J. Meriwether) Hurricanes are not more likely because more hurricane insurance is written. This is not true for financial markets. An increase in financial insurance increases likelihood of disaster. Those who know you sold the insurance (will trade against you) can make it happen. In a crisis all that matters is who holds what and at what price. Markets are more complex than casinos. The numbers on the Roulette wheel never change. Markets make no guarantee that yesterday’s odds will be the same tomorrow. (… in markets you play against God’s creatures)

12. Decisions at Risk (It is not what we don’t know that gets us in trouble…) Amplifiers Uncertainty Bias Beyond the data experiences Experiences Exposures Black Swans Rare Events Large Impact Explainable Over confidence Illusion of control Hindsight bias Anchoring Incentives Bureaucracy Opaqueness (…it is what we know that ain’t so)

13. Risk Management

14. (Performance – is it luck…) The Setting Dimensions Frequency Exposure Experience Severity Focus: High impact low probability events (HILPEs) HILPEs difficult to understand and frequently ignored History proves HILPEs do happen and can threaten survival of the unprepared Issues Statistical: insufficient data Behavioral: infrequency clouds perception Risk estimates anchored Disaster myopia Social: reduced from regulations collapse once behavior changes Goodhart’s Law Risk Adaptation (… or skill)

15. Risk Management (Not just that risk management fails…) Toolbox Avoidance Ignore Mitigate Transfer Equity Self insure (… but it can produce unintended consequences that amplify damages)

16. (It is the system…) Complex Financial Institutions Complex Simple Tight High Risk Systems: prone to endogenous normal (system) accidents. Manmade catastrophes Complex nonlinear interaction: inevitable but unpredictability uncertain Branching paths Feedback loops Jumps Tight coupling: network effects Governance: prevent management from imposing risks on organization for their own benefit Policy Implications (A ) Tolerate and improve (B ) Restructure (C ) Abandon Loose Alternative costs C B A Catastrophe loss potential (… not the event)

17. Problem and Solution (James Grant: In financial markets…) Problem: HIPLE Rare Decisions Delayed Feedback Limited Understanding Solution: Firm Level: Prisoners Dilemma Regulatory Level: Capture (…all progress is cyclical not cumulative)

18. Conclusion

19. Thinking About Risks: the Shift (Organizati0ns are a social…) Classical Independent Stationary Rational Gaussian Frictionless Consistent beliefs Linear Risk Reward Complete Information Individuals Risk Objective Function Equilibrium Shocks Efficient New Memories Unstable Bias Fat tails Arbitrage limits Inconsistency Nonlinear Asymmetric Information Institutions Uncertainty Principal-Agent Conflicts Creative Destruction Endogenous Adaptive (…not a physical phenomena)

20. Conclusion (Ignore behavioral finance…) • Risk is managed by people not mathematical models • Accept randomness • Discipline not predictions • Expect the unexpected • Avoid catastrophe risk • Focus on what you know and insure against extremes (… at your peril)