Incorporating Deviations from Normality: Lower Partial Moments

Bernd Scherer

This chapter deals with non-normality, a prominent shortcoming of traditional portfolio analysis. We first review key issues that arise when we are faced with non-normality in data series. The main focus of the chapter, however, is the application of lower partial moments as one way of dealing with asymmetric return distributions. A second, more general method will be presented in Chapter 8.


6.1.1 Single-period returns: visualising and testing for non-normality

This and the next two sections will deal with non-normality (which was identified in Chapter 1 as a potential shortcoming of the traditional Markowitz framework) and its impact on portfolio choice. We will not attempt to arrive at some definitive “cookbook recipe” for constructing a portfolio but, rather, attempt to establish the following key issues to keep in mind when doing so.

  • Are returns normal?

  • Are deviations from normality statistically significant?

  • Are these deviations stable, ie, forecastable?

  • Will non-normality vanish over time?

  • Can we model a simple non-normal alternative?

Most of these questions are covered in this section, though the last two are

To continue reading...

You need to sign in to use this feature. If you don’t have a account, please register for a trial.

Sign in
You are currently on corporate access.

To use this feature you will need an individual account. If you have one already please sign in.

Sign in.

Alternatively you can request an individual account here: