OPEN ACCESS OJS A Wavelet-Based Method to Measure Stock Market Development

Copyright © 2014 Adel Al Sharkasi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In accor-dance of the Creative Commons Attribution License all Copyrights © 2014 are reserved for SCIRP and the owner of the intellectual property Adel Al Sharkasi et al. All Copyright © 2014 are guarded by law and by SCIRP as a guardian. In this paper, we introduce a novel algorithm, based on the wavelet transform, to measure stock market devel-opment. This algorithm is applied to the return series of fourteen worldwide market indices from 1996 to 2005. We find that a comparison of the return series in terms of the quantity of fractional Gaussian noise (fGn), for different values of Hurst exponent (H), facilitates the classification of stock markets according to their degree of development. We also observe that the simple classification of stock markets into “emerging ” or “developing” and “mature ” or “developed ” is no longer sufficient. However, stock markets can be grouped into three catego-ries that we named emerging, intermediate and mature