Benchmark Yield Spreads

  • Whereas stocks have their ratio comparables with similar companies and certain indexes, bonds have yield spreads.
  • A bond may be considered under-valued or over-priced based on its yield spread above a relevant benchmark yield.
  • Nominal Spread: This is the difference in yield between the yield to maturity of a bond and the yield to maturity of a comparable benchmark.

Example, a fixed income analyst might compare the yield to maturity of a 10 year bond for a U.S. company with a high credit rating to the yield to maturity of 10 year U.S. Treasury bonds.

If the spread has widened in recent months, this could indicate that the company is showing signs of weakness, that the economy is showing signs of weakness, or that the bond is now under-valued by the market and a buying opportunity is at hand.

Nominal spread is best applied to traditional bullet bonds (i.e., bonds that pay a periodic fixed coupon payment and return the loaned principal at maturity).

For corporate bonds, the nominal spread reflects: credit risk, liquidity risk, and option risk.

When both bonds compared in the nominal spread are option free, there is no option risk reflected in the nominal spread.

  • Z-Spread: This is the zero volatility or static spread.

The Z-Spread reflects credit, option, and liquidity risk.

  • Option Adjusted Spread (OAS): This spread removes the effect of embedded options on future returns, to reflect non-option risks when comparing a bond to a benchmark.

  • OAS reflects only credit and liquidity risk.

  • The OAS is based on the Treasury spot curve and is considered the best tool for comparing the yields of bonds with embedded options to Treasury yields.

  • When the OAS for a bond is higher than the OAS of comparable bonds relative to the same benchmark, the bond is considered undervalued.

  • Alternatively, when the OAS for a bond is lower than the OAS of comparable bonds against their relevant benchmark, the bond is considered overvalued.

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Data Science in Finance: 9-Book Bundle

Data Science in Finance Book Bundle

Master R and Python for financial data science with our comprehensive bundle of 9 ebooks.

What's Included:

  • Getting Started with R
  • R Programming for Data Science
  • Data Visualization with R
  • Financial Time Series Analysis with R
  • Quantitative Trading Strategies with R
  • Derivatives with R
  • Credit Risk Modelling With R
  • Python for Data Science
  • Machine Learning in Finance using Python

Each book comes with PDFs, detailed explanations, step-by-step instructions, data files, and complete downloadable R code for all examples.