Abstract
The purpose of the present work is to study the fractal properties of the London Metal Exchange (LME) returns time series. Special emphasis is given to the fundamental issue of detection, identification, and measurement of scaling behaviour of LME returns time series. A fractal approach through ARFIMA models is used to analyze the LME time series. The stable distribution has also been used in order to test the Fractal Market Hypothesis (FMH) in the case of LME market. It is demonstrated that LME returns data possess to some extent fractal properties. The findings are in line with the FMH.
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