Tukey's g- and h- transformations

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Tukey's g- and h- transformations

In this courselet, we use the Tukey's gh transformation to model non-normality by modifying random variables.

  • 4.8 Rating
  • 4 Reviews
  • 14 Students Enrolled
  • Free
transforming distribution

Courselet Content

3 components


  • Basic knowledge of statistics

General Overview


In theory, it is often assumed that random variables follow a normal distribution. However, in practice, this is often not the case. ETH returns during the time period from 2015 to the beginning of 2022 are bullish and follow a skewed distribution with heavy tails. The Tukey's g- and h- transformation provides a way to model this non-normality via the modification of standard normal random variables.

In this courselet, we will cover the theoretical background on the Tukey gh transformations, show examples and illustrate limitations. Furthermore, we estimate the parameters g and h based on return data.

As a result, the participants will get a deeper understanding of non-normality and the modification possibilities of already existing distributions. In addition, people will learn about skewness and heavy tails which can come in handy when dealing with financial return data.


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Meet the instructors !

About the Instructor

Graduate Student of Economics and Management Science at Humboldt University of Berlin

Research Interests:

Sentiment Analysis


Quantitative Finance

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