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A method to test weak-form market efficiency from sectoral indices of the WAEMU stock exchange: A wavelet analysis.

ABSTRACT: This study assesses the efficiency of the West African Economic and Monetary Union (WAEMU) regional stock exchange using daily data on its seven (7) sectoral indices from December 31, 2013, to January 4, 2019. To this end, we analyze the market structure and calculate the generalized Hurst index by using the discrete wavelet transformation (DWT) and wavelet leader transformation (WLT) approaches. Our conclusions can be summarized as follows: first, this study highlights the multifractal nature of the WAEMU stock market. Second, the Hurst generalized index reveals a persistent or nonpersistent process depending on the sector, according to the q chosen or the method used (DWT or WLT). The dynamics of the indices reveal the characteristics of short memory or, in some cases, long memory, and the efficient market hypothesis is rejected.

SUBMITTER: Diallo OK

PROVIDER: S-EPMC7855331 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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A method to test weak-form market efficiency from sectoral indices of the WAEMU stock exchange: A wavelet analysis.

Diallo Oumou Kalsoum OK Mendy Pierre P Burlea-Schiopoiu Adriana A

Heliyon 20210118 1

This study assesses the efficiency of the West African Economic and Monetary Union (WAEMU) regional stock exchange using daily data on its seven (7) sectoral indices from December 31, 2013, to January 4, 2019. To this end, we analyze the market structure and calculate the generalized Hurst index by using the discrete wavelet transformation (DWT) and wavelet leader transformation (WLT) approaches. Our conclusions can be summarized as follows: first, this study highlights the multifractal nature o ...[more]

PMID: 33553713

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Dataset Information

A method to test weak-form market efficiency from sectoral indices of the WAEMU stock exchange: A wavelet analysis.

Publications

A method to test weak-form market efficiency from sectoral indices of the WAEMU stock exchange: A wavelet analysis.

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