Fisher Effect

Fisher effect is an important exchange rate model developed by Irving Fisher in 1930.

The Fisher effect provides the relationship between the nominal interest rates, inflation and real interest rates. According to Fisher effect, the nominal interest rate is the sum of real interest rate and expected inflation. It can be expressed as below:

RNom=RReal+E[I]R_{Nom}=R_{Real}+E[I]

Where,

RNom is the nominal interest rate

RReal is the real interest rate

E[I] is the expected inflation

It is important to understand the difference between the nominal and real interest rates. Nominal interest rates are what people see everyday as published by banks and other institutes. For example, when a bank says that you will earn 6% on savings deposits, they are talking about the nominal interest rate. On the other hand, real interest rates take purchasing power parity into consideration. That’s the rate, which tells how much more you will be able to buy with your grown investment after one year.

Assume a bank is offering you an interest rate of 5% on your deposits and the expected inflation is 3%, then the real interest rate you earn is just 2% keeping the inflation in mind. In terms of real value of money, your investment will grow only by 2%. If you deposit $100 at the beginning of the year, your deposit will grow to $105 by the end of the year. However your $105 will not buy you 5% more stuff. It will buy you only 2% more stuff. This is because due to inflation, all the stuff has become expensive by 3%.

The idea here is that the real interest rates are fairly stable and the changes in interest rates are influenced by changes in inflation.

Note that we are referring to expected inflation. The investors also face the risk that the actual inflation will be different from the expected inflation, and they demand an additional premium for this risk.

RNom=RReal+E[I]+RPR_{Nom}=R_{Real}+E[I] +RP

Where RP is the risk premium for uncertainty in inflation rate

An important point to note is that Fisher effect is a long-term phenomenon and may not be present in the short run.

Related Downloads

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 includes PDFs, explanations, instructions, data files, and R code for all examples.

Get the Bundle for $39 (Regular $57)
JOIN 30,000 DATA PROFESSIONALS

Free Guides - Getting Started with R and Python

Enter your name and email address below and we will email you the guides for R programming and Python.

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.