Currency Swaps

  • Currency swaps have some key differences from interest rate swaps:

  • There are two notional principal amounts;

  • Each notional is in a different currency;

  • The notionals are exchanged at the beginning of the swap and then again at the end of the swap.

  • Periodic cash flow payments are made in different currencies.

  • Currency Swap Steps:

  1. Initial exchange of notionals.
  2. Periodic exchange of coupon payments; given the different currencies, netting may not be feasible in currency swaps like it is for plain vanilla interest rate swaps.
  3. Return of notional principals at swap expiration.
  • Motivation: Because a company may have a borrowing advantage in one currency but wishes to have the debt exposure in another currency, the company may wish to enter a currency swap.

  • Example: a U.S. company with high quality credit can borrow cheaply within the U.S. The company wishes to build a factory in Colombia, but does not have the credit history to borrow at comparable rates. The company may opt to finance the project with U.S. denominated debt and enter into a currency swap to receive U.S. and pay Colombian pesos.

  • Common users of currency swaps are borrowers who wish to convert their debt into a different currency.

Swaps are can be referred to as an "exchange of borrowings" because the parties have independently borrowed financial capital and through the use of a swap have agreed to exchange the proceeds.

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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.