Wavelet-based systematic risk estimation: application on GCC stock markets: the Saudi Arabia case

Anouar Ben Mabrouk; Anouar Ben Mabrouk

doi:10.3934/QFE.2020026

Quantitative Finance and Economics

2020, Volume 4, Issue 4: 542-595. doi: 10.3934/QFE.2020026

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Research article

Wavelet-based systematic risk estimation: application on GCC stock markets: the Saudi Arabia case

Anouar Ben Mabrouk ^{1,2,3
,
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1.
Department of Mathematics, Faculty of Science, University of Tabuk, Saudi Arabia
2.
Department of Mathematics, Higher Institute of Applied Mathematics and Computer Science, University of Kairouan, Tunisia
3.
Laboratory of Algebra, Number Theory and Nonlinear Analysis, Department of Mathematics, Faculty of Sciences, University of Monastir, Tunisia
Correction on: Quantitative Finance and Economics 7: 117-118.

Received: 02 June 2020 Accepted: 01 September 2020 Published: 07 September 2020
JEL Codes: G11, C02, C22

Systematic risk estimation is widely applied by investors and managers in order to predict risks in the market. One of the most applied measures of risk is the so-called Capital Asset Pricing Model, shortly CAPM. It has been studied empirically focusing on the impact of return interval on the betas. This paper lies in this topic and attempts to estimate the CAPM at different time scales for GCC markets by adapting a wavelet method to examine the relationship between the return of the stock and its systematic risk at different time scales. The main novelty is by applying non-uniform intervals of time. Differently from existing literature, we use random ones. The proposed procedure is acted empirically on a sample corresponding to Saudi Tadawul market as the most important GCC representative market actively traded over the period January 01, 2013 to September 20, 2018, which is characterized by many political, economic and financial movements such as Qatar embargo, Yemen war, NEOM project, 2030 KSA vision and the Arab spring effects. The findings in the present work may be good basis for understanding current and future GCC markets situation and may be thus a basis for investors' decisions in such markets.
- wavelets CAPM,
- systematic (market) risk,
- scaling,
- GCC stock markets,
- Tadawul
Citation: Anouar Ben Mabrouk. Wavelet-based systematic risk estimation: application on GCC stock markets: the Saudi Arabia case[J]. Quantitative Finance and Economics, 2020, 4(4): 542-595. doi: 10.3934/QFE.2020026

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Abstract

Systematic risk estimation is widely applied by investors and managers in order to predict risks in the market. One of the most applied measures of risk is the so-called Capital Asset Pricing Model, shortly CAPM. It has been studied empirically focusing on the impact of return interval on the betas. This paper lies in this topic and attempts to estimate the CAPM at different time scales for GCC markets by adapting a wavelet method to examine the relationship between the return of the stock and its systematic risk at different time scales. The main novelty is by applying non-uniform intervals of time. Differently from existing literature, we use random ones. The proposed procedure is acted empirically on a sample corresponding to Saudi Tadawul market as the most important GCC representative market actively traded over the period January 01, 2013 to September 20, 2018, which is characterized by many political, economic and financial movements such as Qatar embargo, Yemen war, NEOM project, 2030 KSA vision and the Arab spring effects. The findings in the present work may be good basis for understanding current and future GCC markets situation and may be thus a basis for investors' decisions in such markets.

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