| dc.contributor.author | LAHMIRI, Salim | |
| dc.contributor.author | BEKIROS, Stelios D. | |
| dc.date.accessioned | 2021-02-22T15:49:33Z | |
| dc.date.available | 2021-02-22T15:49:33Z | |
| dc.date.issued | 2020 | |
| dc.identifier.citation | Physica, 2020, Vol. 539, Art. 122923, OnlineOnly | en |
| dc.identifier.issn | 0378-4371 | |
| dc.identifier.issn | 1873-2119 | |
| dc.identifier.uri | https://hdl.handle.net/1814/70155 | |
| dc.description | First published online: 01 February 2020 | en |
| dc.description.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. (C) 2019 Elsevier B.V. All rights reserved. | en |
| dc.language.iso | en | |
| dc.publisher | Elsevier | en |
| dc.relation.ispartof | Physica | en |
| dc.title | Nonlinear analysis of Casablanca stock exchange, Dow Jones and S&P500 industrial sectors with a comparison | en |
| dc.type | Article | |
| dc.identifier.doi | 10.1016/j.physa.2019.122923 | |
| dc.identifier.volume | 539 | |
| eui.subscribe.skip | true | |