Managing Synthetic CDO Tranches using Base Correlations
Managing Synthetic CDO Tranches using Base Correlations Managing Synthetic CDO Tranches using Base Correlations
Base correlation framework Each tranche is decomposed into two “virtual” equity tranches Incorporate entire capital structure V = V ( s, ρb) −V0, ( s, ρ ) a, b 0, b a a Why Some analogy with pricing equity options with multiple strikes Consistency across a fixed maturity (inconsistent across different tenors) More importantly, empirical evidence suggests that base correlations provide better sensitivities than compound correlations. From standard index tranches we can bootstrap base correlations 12
Agenda Synthetic CDO mechanics Base correlations under Gaussian copula model Stress tests Mapping bespoke tranches to standard index tranches Interpolation / extrapolation of base correlations 13
- Page 2 and 3: Managing synthetic CDO tranches usi
- Page 4 and 5: Synthetic CDO mechanics losses Pro
- Page 6 and 7: Protection buyer can hedge by selli
- Page 8 and 9: Agenda Synthetic CDO mechanics Ba
- Page 10 and 11: Gaussian Copula Model (con’t) S
- Page 14 and 15: Stress tests Base correlations c
- Page 16 and 17: Subprime crisis has spread to … L
- Page 18 and 19: Stress Test Example for CDX.NA.IG S
- Page 20 and 21: So which stress test makes sense I
- Page 22 and 23: Agenda Synthetic CDO mechanics Ba
- Page 24 and 25: Mapping base correlations between b
- Page 26 and 27: Base correlation mapping methods Fi
- Page 28 and 29: Method 4: Expected Tranche Loss Pro
- Page 30 and 31: Comparison of mappings for iTraxx S
- Page 32 and 33: Heterogeneous portfolios Can we fin
- Page 34 and 35: Consider linear interpolation iTrax
- Page 36: Summary Base correlation are usef
Agenda<br />
<br />
<strong>Synthetic</strong> <strong>CDO</strong> mechanics<br />
<br />
<strong>Base</strong> correlations under Gaussian copula model<br />
<br />
Stress tests<br />
<br />
Mapping bespoke tranches to standard index tranches<br />
<br />
Interpolation / extrapolation of base correlations<br />
13
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