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Quant Systems Lab · Control Systems for Quantitative Finance

Credit Intensity Models and Default Correlation

Intensity models treat default as a random time with a hazard rate, which can be linked across names via factors.

Explanation

In reduced-form models, default time is generated from an intensity (hazard rate) process, not a structural threshold.

Common factors in intensities generate dependent default times and cluster risk in portfolios.

Default correlation matters for CDO tranches, tail risk, and systemic stress testing.


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Interactive visualisation

Intensity models treat default as a random time driven by a hazard rate. When a common factor drives part of that intensity, different names share stress periods and default times become clustered rather than independent.

Intensity decomposition λ = λᵢ + λ_f: calm vs stress scenario over horizon TCalmλ_calm ≈ 4.4%Stressλ_stress ≈ 6.6%λᵢ idiosyncraticλ_f common factor
By horizon T: single-name default, joint default, and at-least-one default probabilitiesconstP(default A)21.4%P(both defaults)4.7%P(at least one)38.1%
Numbers
λ base ≈ 5.0% per year
λᵢ idiosyncratic ≈ 3.0% per year
λ_f base factor ≈ 2.0% per year
λ_calm ≈ 4.4% per year
λ_stress ≈ 6.6% per year
P(default A by T) ≈ 21.4%
P(both defaults) ≈ 4.7%
P(at least one default) ≈ 38.1%
Pairwise default correlation ≈ 0.01
Interpretation

Increasing ρ moves more of λ into the common factor: the purple segments grow relative to the grey ones, especially in the stress scenario. Single-name default probabilities change only moderately, but the joint default and “at least one default” bars grow faster.

The correlation number summarises clustering: with ρ near zero, defaults are almost independent; with large ρ, stress periods dominate and defaults become much more likely to occur together. This is exactly the effect that matters for portfolio credit, tranches, and systemic stress testing.