Relationship between the oil price volatility and sectoral stock markets in oil-exporting economies: Evidence from wavelet nonlinear denoised based quantile and Granger-causality analysis |
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| Affiliation: | 1. Faculty of Economics and Management, University of Sfax, Tunisia;2. Taibah University, Al Madinah, Saudi Arabia;3. Montpellier Business School, France;1. School of Finance, Yunnan University of Finance and Economics, Kunming, China;2. School of Economics & Management, Southwest Jiaotong University, Chengdu, China;3. School of Finance, Chongqing Technology and Business University, Chongqing, China;4. School of Business, Sichuan Normal University, Chengdu, China;1. IMM, Campus de Luminy, Case 907, 13288 Marseille cedex 09, France;2. IPAG LAB-IPAG Business School, 184, Boulevard Saint-Germain, 75006 Paris, France;1. College of Business Administration, Hunan University, Changsha, Hunan Province, China;2. School of Economics and Management, Fuzhou University, Fuzhou, Fujian Province, China;1. Rajagiri Centre for Business Studies, Rajagiri Valley Campus, Kochi, India;2. Montpellier Business School, Montpellier, France;3. Department of Finance and Accounting, IBS, IFHE University, Hyderabad, India;4. Department of Economics, Pusan National University, 2, Busandaehak-ro 63beon-gil, Geumjeong-gu, Busan 46241, Republic of Korea;1. Department of Applied Economics, Universitat de les Illes Balears, Ctra. Valldemossa, km 7.5, Building: Gaspar Melchor Jovellanos, 07122 Palma de Mallorca, Spain;2. Montpellier Business School, 2300 Avenue des Moulins, 34080 Montpellier, France;3. Division of Economics, Department of Management and Engineering, Linköping University, 581 83 Linköping, Sweden |
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| Abstract: | This paper examines the extent of volatility between oil price and sectoral indices in the Gulf Cooperation Council (GCC) countries by using quantile regression analysis (QRA) for the return's series and denoised series over the period 2006–2017. Four sectors are found to offer diversification opportunities during a high market (i.e., 90th quantile). All the sectors are found interdependent of oil price volatility; however, the bank and insurance sectors are insusceptible to oil price volatility during the 10th, 25th and 75th quantiles. In addition, QRA results for wavelet nonlinear denoising with a soft-thresholding series indicate that all the sectors are interdependent of oil price volatility but that the aggregate market index, transport and telecommunication sectors are insensitive to oil price volatility during the 75th and 90th quantiles. This highlights the usefulness of denoising the financial returns series when applying regression tools. Moreover, the contagion and interdependence between the oil price and stock returns sectors are estimated by frequency domain causality. |
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