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Credit default swap Quote by Michael Lewis

“A credit default swap was confusing mainly because it wasn’t really a swap at all. It was an insurance policy, typically on a corporate bond, with semiannual premium payments and a fixed term. For instance, you might pay $200,000 a year to buy a ten-year credit default swap on $100 million in…” quote by Michael Lewis
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““A credit default swap was confusing mainly because it wasn’t really a swap at all. It was an insurance policy, typically on a corporate bond, with semiannual premium payments and a fixed term. For instance, you might pay $200,000 a year to buy a ten-year credit default swap on $100 million in General Electric bonds. The most you could lose was $2 million: $200,000 a year for ten years. The most you could make was $100 million, if General Electric defaulted on its debt any time in the next ten years and bondholders recovered nothing. It was a zero-sum bet: If you made $100 million, the guy who had sold you the credit default swap lost $100 million. It was also an asymmetric bet, like laying down money on a number in roulette. The most you could lose were the chips you put on the table; but if your number came up you made thirty, forty, even fifty times your money.””

Michael Lewis

About This Quote

Source Book: Liar's Poker by Michael Lewis, 1989

A credit default swap functions like insurance on a bond, with limited loss but potentially huge gain, making it a zero‑sum, asymmetric bet.

In simple terms: CDS are like insurance on bonds with big upside, limited downside.

Key Takeaway

Understand risk/reward asymmetry before trading.

Themes

finance risk derivatives asymmetry zero‑sum

Mood

cautious analytical

Type

educational technical

When to use this quote

  • investment banking
  • risk management
  • trading strategies
  • portfolio construction

Key Concepts

insurance leveraging betting financial engineering

Questions to Reflect On

  • How does asymmetry affect decision‑making?
  • What safeguards mitigate hidden risks?
A Different Perspective

Complexity can obscure true risk; model assumptions may fail.

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