US Treasury STRIPS: Pricing and Risks

The prices of STRIPS are quoted on a discount basis, as a percentage of par. Eligible securities can be stripped at any time. For a book-entry security to be separated into its component parts, the par value must be an amount which, based on the stated interest rate, will produce a semiannual interest payment of $1,000 or a multiple of $1,000. Quotes for STRIPS are quoted in yields to maturity.

Hedging

Zeros are typically hedged in the futures or options markets, or by taking a contra position in another Treasury security. The effectiveness of any hedge depends on yield-curve and basis risk. Also, if a position in zeros is hedged with an OTC option, the relative illiquidity of the derivative Treasury security and the option may diminish the effectiveness of the hedge.

Risks

The two key risks are interest rate risk and liquidity risk. There is no credit risk because STRIPS are considered to be free from default.

Interest-Rate Risk

Increases in the level of interest rates increase the advantages of stripping. This is because the constant-yield method applied to premium bonds results in a lower price than linear amortization does. Zeros have higher sensitivity to changes in interest rates than bonds with the same maturity. Because they are zero-coupon bonds, their duration equals their maturity. The higher the duration, the higher the potential volatility.

Liquidity Risk

The STRIPS market is significantly less liquid than the U.S. Treasury bond market. Investors encounter wider bid/ask spreads and are subject to higher commissions. In addition, liquidity may fluctuate significantly in times of market instability. However, since a dealer can strip or reconstitute bonds in a fairly flexible manner, if zero-coupon prices diverge too far from their equilibrium levels, a new supply can be created or reduced through the stripping and reconstitution process.

Reference: Federal Reserve Board

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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.