• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar
  • Skip to footer
Finance Train

Finance Train

High Quality tutorials for finance, risk, data science

  • Home
  • Data Science
  • CFA® Exam
  • PRM Exam
  • Tutorials
  • Careers
  • Products
  • Login

Bond Features Affecting Interest Rate Risk

CFA® Exam Level 1, Fixed Income Securities

This lesson is part 3 of 17 in the course Risks of Investing in Bonds

We know that a bond’s price is inversely related to the yield. How sensitive a bond price is to yield depends on the various features of the bond such as its maturity, coupon rate, and any embedded options in the bond. Let’s look at how these factors influence the impact of interest rate changes on a bond’s price.

Maturity

In general, the longer the maturity, the higher the interest rate sensitivity. This means that for a given change in interest rates, everything else remaining the same, the price of a bond with higher maturity will change more compared to another similar bond with lower maturity. This happens because a higher number of cash flows need to be discounted.

Coupon Rate

All other factors remaining the same, the lower the coupon, the higher is the interest rate sensitivity. This happens because when the bond has lower coupon, its value is more dependent on the par amount to be received at maturity. In other words, it takes longer for a bondholder to get back its capital when the interest rates are low. On the other hand, a bond with high coupon rate has higher cash flows in the beginning which reduces its dependency on the maturity value. In this sense, zero-coupon bonds have highest interest rate sensitivity compared to a similar coupon paying bond.

Embedded Bonds

Some bonds can have embedded options such as a call option attached to it. For a callable bond, the bond can be called back by the issuer. Such an option also affects the interest rate sensitivity of the bond. All other factors remaining the same, a bond with embedded call option will be less sensitive to interest rate changes. This happens because the price of a callable bond is lower than a similar non-callable bond by an amount equal to the value of the option.

Price of Callable Bond = Price of Non-callable Bond – Price of Embedded Option

The price is reduced because the call option is a benefit for the issuer. The opposite will be true for a puttable bond which provides the right to the investor to return the bond to the issuer.

When interest rates rise, the price of the embedded call option declines. Therefore, the overall effect on the decline in the price of the bond is less.

Previous Lesson

‹ Understanding Inverse Price/Yield Relationship in Bonds

Next Lesson

Impact of Yield Level on Bond’s Price Sensitivity ›

Join Our Facebook Group - Finance, Risk and Data Science

Posts You May Like

How to Improve your Financial Health

CFA® Exam Overview and Guidelines (Updated for 2021)

Changing Themes (Look and Feel) in ggplot2 in R

Coordinates in ggplot2 in R

Facets for ggplot2 Charts in R (Faceting Layer)

Reader Interactions

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Primary Sidebar

In this Course

  • Key Risks Associated with Investing in Bonds
  • Understanding Inverse Price/Yield Relationship in Bonds
  • Bond Features Affecting Interest Rate Risk
  • Impact of Yield Level on Bond’s Price Sensitivity
  • Price of a Callable Bond
  • Interest Rate Risk of Floating-rate Bonds
  • Bond Duration and Convexity Simplified – Part 1 of 2
  • Bond Duration and Convexity Simplified – Part 2 of 2
  • Yield Curve Risk
  • Call and Prepayment Risk
  • Reinvestment Risk in Bonds
  • Credit Risk in Bonds
  • Liquidity Risk in Bonds
  • Exchange Rate Risk in Bonds
  • Inflation Risk in Bonds
  • Volatility Risk in Bonds with Embedded Options
  • Event Risk and Sovereign Risk in Bonds

Latest Tutorials

    • Data Visualization with R
    • Derivatives with R
    • Machine Learning in Finance Using Python
    • Credit Risk Modelling in R
    • Quantitative Trading Strategies in R
    • Financial Time Series Analysis in R
    • VaR Mapping
    • Option Valuation
    • Financial Reporting Standards
    • Fraud
Facebook Group

Membership

Unlock full access to Finance Train and see the entire library of member-only content and resources.

Subscribe

Footer

Recent Posts

  • How to Improve your Financial Health
  • CFA® Exam Overview and Guidelines (Updated for 2021)
  • Changing Themes (Look and Feel) in ggplot2 in R
  • Coordinates in ggplot2 in R
  • Facets for ggplot2 Charts in R (Faceting Layer)

Products

  • Level I Authority for CFA® Exam
  • CFA Level I Practice Questions
  • CFA Level I Mock Exam
  • Level II Question Bank for CFA® Exam
  • PRM Exam 1 Practice Question Bank
  • All Products

Quick Links

  • Privacy Policy
  • Contact Us

CFA Institute does not endorse, promote or warrant the accuracy or quality of Finance Train. CFA® and Chartered Financial Analyst® are registered trademarks owned by CFA Institute.

Copyright © 2021 Finance Train. All rights reserved.

  • About Us
  • Privacy Policy
  • Contact Us