Author(s)

P. JIZBA & J. KORBEL

Abstract

We show that a multifractal analysis offers a new and potentially promising avenue for quantifying the complexity of various time series. In particular, we compare the most common techniques used for multifractal scaling exponents estimation. This is done from both a theoretical and phenomenological point of view. In our discussion we specifically focus on methods based on estimation of Rényi entropy, which provide a powerful tool especially in the presence of heavy-tailed data. As a testbed for the applicability of above multifractal methods we use various real financial datasets, including both daily and high-frequency data.

Keywords

multifractal spectrum, Rényi entropy, time series