1. Financial crisis How to make sense of it

2. Objectives  Scan literature  Organize using graphical representation  Build up  Collapse  Identify likely solutions

3. Build up More lending Low Interest rates More lending Low Interest rates Higher housing demand Higher home prices Higher collateral, Higher housing demand Higher home prices Higher collateral, Lower expected loss & probability of loss due to defaults Lax lending practices Securitization Lack of transparency Bad compensation schemes High credit rating on ABS/CDO tranches Bad modelling Bad stress testing Over reliance on credit rating High demand for CDOs Overconfidence about repaying loan More loans securitized in CDOs Short term incentives for managers High profits Shift risk originators to investors

4. Build up – fundamental causes More lending Low Interest rates More lending Low Interest rates Higher housing demand Higher home prices Higher collateral, Higher housing demand Higher home prices Higher collateral, Lower expected loss & probability of loss due to defaults Lax lending practices Securitization Lack of transparency Bad compensation schemes High credit rating on ABS/CDO tranches Bad modelling Bad stress testing Over reliance on credit rating High demand for CDOs Overconfidence about repaying loan More loans securitized in CDOs Short term incentives for managers High profits Shift risk originators to investors

5. Build up – self sustaining reaction More lending Low Interest rates More lending Low Interest rates Higher housing demand Higher home prices Higher collateral, Higher housing demand Higher home prices Higher collateral, Lower expected loss & probability of loss due to defaults Lax lending practices Securitization Lack of transparency Bad compensation schemes High credit rating on ABS/CDO tranches Bad modelling Bad stress testing Over reliance on credit rating High demand for CDOs Overconfidence about repaying loan More loans securitized in CDOs Short term incentives for managers High profits Shift risk originators to investors

6. Collapse House prices fall Default rates increase, correlation of default increases No lending between financial institutions Low liquidity on credit instruments High loss aversion Institutions’ books shrink Can’t sell off Cannot honour contractual obligations Default Cannot honour contractual obligations Default ARMs reset after teaser period ends Foreclosures increase High leverage Losses to credit instruments Counterparty defaults increase

7. Collapse House prices fall Default rates increase, correlation of default increases No lending between financial institutions Low liquidity on credit instruments High loss aversion Institutions’ books shrink Can’t sell off Cannot honour contractual obligations Default Cannot honour contractual obligations Default ARMs reset after teaser period ends Foreclosures increase High leverage Losses to credit instruments Counterparty defaults increase

8. More info For a more in-depth discussion see Irina I, Alex F. (2009) Financial Crisis event chains

9. Focus for this presentation - Models More lending Low Interest rates More lending Low Interest rates Higher housing demand Higher home prices Higher collateral, Higher housing demand Higher home prices Higher collateral, Lower expected loss & probability of loss due to defaults Lax lending practices Securitization Lack of transparency Bad compensation schemes High credit rating on ABS/CDO tranches Bad modelling Bad stress testing Over reliance on credit rating High demand for CDOs Overconfidence about repaying loan More loans securitized in CDOs Short term incentives for managers High profits Shift risk originators to investors

10. Gaussian Copula  Default events described by Poisson distribution  Defaults are correlated  Hard to draw correlated Poissons  Easy to draw correlated Normals (Gaussian dist.) Gaussian copula:  Transform to Normal (CDF Poisson  CDF Normal)  Draw correlated Normals instead

11. Gaussian Copula - Problem Problem: Correlations change, in particular they increase during extreme events (Tail correlation) Solutions:  Use higher static correlations  Use time-varying correlations (GARCH etc..)  Different copula (double-t copula etc..)

12. Models weren’t REALLY the problem  Institutions did use higher static correlations!  We know this by implying correlations from (high) yields.  So what was the real problem?

13. Ratings  Credit rating based on probability of default (or expected loss) – a single number!  Rating of bond can be same as of CDO tranche but probability distributions are different

14. Real problem  Misunderstood credit ratings  Didn’t do own models  Thought high yield came without risk   Models vindicated! (somewhat)

15. More info Again, for a more in-depth discussion see Irina I, Alex F. (2009) Financial Crisis event chains as well as bibliography.