Nonlinear analysis of Casablanca Stock Exchange, Dow Jones and S&P500 industrial sectors with a comparison

Salim Lahmiri and Stelios Bekiros

Physica A: Statistical Mechanics and its Applications, 2020, vol. 539, issue C

Abstract: Long memory, information content, information generation, and randomness are evaluated in various industrial sectors from Casablanca Stock Exchange (CSE), Dow Jones, and S&P500. Then, three formal statistical tests are performed to check presence of differences. It is found that Dow Jones and S&P500 industrial sectors which are developed markets are characterized by richer information content and circulation compared to industrial sectors in CSE which is a developing stock market. In addition, the obtained empirical results show that the amount of information content and generation increases with stock market size. Finally, prices are potentially predictable in all industrial sectors across all three markets.

Keywords: Hurst exponent; Kolmogorov complexity; Lempel–Ziv complexity; Shannon entropy; Casablanca Stock Exchange; Dow Jones; S&P500; Industrial sectors (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:539:y:2020:i:c:s0378437119316577

DOI: 10.1016/j.physa.2019.122923

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