Hedging Using Interest Rate Swaps

In this lesson, we will look at a few examples of how corporations and financial institutions use interest rate swaps.

GAP Management

This example represents a financial institution, a bank, that is “lengthening the maturity,” “fixing” the interest rate, on its funding base in order to better match the funding costs with the fixed rate yield from its assets, say loans or investments.

In the example, the effective fixed rate debt cost is now 11 + 1/8%.

Liability Management

In this example, a synthetic floating rate note, i.e., floating rate debt, could be created by converting a long-term liability (for example, term deposits of a bank or fixed rate debt of a corporation or bank) to a floating rate.

The issuer in this example had borrowed term funds at a 13% fixed rate and transformed them to an effective floating rate cost of treasuries plus 1.

Asset Management - 1

Fixed rate assets (such as fixed income bonds, private placements, mortgage loans or mortgage backed securities) can be converted to floating rates using a swap.

In the example, a pool of mortgages with a weighted average coupon (WAC) of 10.5% has been converted to yield LIBOR + ¼ %.

Asset Management- 2

To fix the rate on variable rate assets, perhaps to match available long-term funding, floating rate assets (such as domestic or foreign floating rate notes, adjustable rate mortgages, floating rate preferred stock or CD’s) can be converted to fixed rate assets using swaps.

In the example, the investment in variable rate CD’s has been transformed into a 12% fixed rate investment.

As you can see, one of the advantages of swaps is that you can obtain the best available funding, whatever the maturity, when market conditions are favourable and the opportunity is right. These funds can then be swapped into the desired maturity or interest rate structure.

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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.