Bond Equivalent Yield Convention

In the bond market the convention is to annualize the semi-annual yield by simply doubling it. So, if the semi-annual yield is 3%, the annual yield is calculated simply as 3% x 2 = 6%. The annual yield so calculated is called the bond-equivalent yield (BEY).

This convention doesn’t follow the time value of money rules where you would compound the semi-annual yield to calculate the effective annual yield. Instead the doubling convention is followed across the market.

A common question asked by students is ‘Why have such a convention and why not instead use effective annual yield?’ The answer to this question is that since it’s a convention everybody uses it and therefore yields are comparable. It doesn’t really affect performance or comparison between bonds because everyone would have used the convention to quote the yield. Conventions are usually made to make things simpler. In this case if someone tells you that the bond-equivalent yield is 6%, you instantly know that semi-annual yield is 3%, which you can use to perform any calculations or to calculate the effective annual yield if you require it.

If the convention was to use effective annual yield, it may have been better, but does it really matter? In fact there are many other limitations of YTM that far outweigh the problem of BEY convention. So, my suggestion to you would be to just follow the convention and don’t fret over it. It is important however, that you use the convention correctly.

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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.