Michael Brenndoerfer | Data & AI, Private Equity, Technology

Michael Brenndoerfer

Structured Credit Products (CDOs and Securitizations) › Synthetic CDOs and Credit Indices

Michael BrenndoerferNovember 19, 20253 min read

Quantitative FinanceAll chapters

Part 4 of 15Swaps and Credit Derivatives

Chapter 23Structured Credit Products (CDOs and Securitizations) › Synthetic CDOs and Credit Indices

Reading section 7 of 12 · Synthetic CDOs and Credit Indices · 3 minSection 7 of 12 · 3 min

Section 7 of 12 · 3 min read

Structured Credit Products (CDOs and Securitizations) › Synthetic CDOs and Credit IndicesOne section · Sections in this chapter7 / 12 ↓

Sections in this chapter12

Reading tools Definitions & inline links

Choose your expertise level to adjust how many terms are explained. Beginners see more tooltips, experts see fewer to maintain reading flow. Hover over underlined terms for instant definitions.

Article links

Make inline references clickable

Synthetic CDOs, introduced after the credit default swap market matured, use CDS contracts instead of physical bonds to create credit exposure. They became the dominant CDO structure due to lower execution costs and greater flexibility.

CDX and iTraxx IndicesLink Copied

Standardized credit indices made synthetic CDO trading more liquid:

CDX (North America): 125 investment-grade names in CDX.IG, 100 high-yield names in CDX.HY
iTraxx (Europe and Asia): Similar structures for European and Asian credits

These indices and their tranches trade with standardized terms, enabling more transparent price discovery than bespoke CDO structures.

In[26]:

Code

# Standard CDX.IG tranche structure
cdx_tranches = {
    "Equity": {
        "attachment": 0.00,
        "detachment": 0.03,
        "spread_type": "upfront",
    },
    "Junior Mezz": {
        "attachment": 0.03,
        "detachment": 0.07,
        "spread_type": "running",
    },
    "Senior Mezz": {
        "attachment": 0.07,
        "detachment": 0.10,
        "spread_type": "running",
    },
    "Junior Senior": {
        "attachment": 0.10,
        "detachment": 0.15,
        "spread_type": "running",
    },
    "Senior": {
        "attachment": 0.15,
        "detachment": 0.30,
        "spread_type": "running",
    },
    "Super Senior": {
        "attachment": 0.30,
        "detachment": 1.00,
        "spread_type": "running",
    },
}

cdx_df = pd.DataFrame(
    [
        {
            "Tranche": name,
            "Attachment (%)": spec["attachment"] * 100,
            "Detachment (%)": spec["detachment"] * 100,
            "Spread Type": spec["spread_type"],
        }
        for name, spec in cdx_tranches.items()
    ]
)

Out[27]:

Console

Standard CDX.IG Tranche Structure:
------------------------------------------------------------
      Tranche  Attachment (%)  Detachment (%) Spread Type
       Equity             0.0             3.0     upfront
  Junior Mezz             3.0             7.0     running
  Senior Mezz             7.0            10.0     running
Junior Senior            10.0            15.0     running
       Senior            15.0            30.0     running
 Super Senior            30.0           100.0     running

Out[28]:

Visualization

Horizontal stacked bar showing CDX.IG tranche attachment and detachment points — Standard CDX.IG capital structure. The diagram illustrates the subordination hierarchy, from the first-loss Equity tranche (0-3%) to the Super Senior tranche (30-100%), which is protected by a 30% subordination buffer.

The equity tranche trades with an upfront payment plus a fixed 500 bps running spread, while other tranches trade on a running spread basis. This convention reflects the high expected losses in the equity tranche, making a pure running spread impractical.