Testing mean-reversion in agricultural commodity prices: Evidence from wavelet analysis

Lawal, A. I. and Omoju, Oluwasola Emmanuel and Babajide, Abiola Ayopo and Asaleye, Abiola John (2019) Testing mean-reversion in agricultural commodity prices: Evidence from wavelet analysis. Journal of International Studies, 12 (4). pp. 100-114. ISSN 2071-8330

[img] Text
7_686_Lawal et al(1).pdf - Published Version

Download (663kB)
Official URL: http://dx.doi.org/10.14254/2071-8330.2019/12-4/7


This study examines the validity of the random walk hypothesis for some selected soft agricultural commodity prices within the context of heterogeneous market hypothesis and mean reversion hypothesis. The study employs a battery of traditional unit root tests, GARCH-based models and a novel frequency-based wavelet analysis to analyze daily data sourced from 6th of Jan 1986 to 29th Dec 2018. Contrary to other existing studies that employed only traditional time domain unit root tests, our results reveal that soft commodity prices are mean reverting, suggesting the existence of potential excess returns for investors. Overall, our results show that the selected soft commodity series are inefficient when we factored in heteroscedascity and frequency domain into our model. Our study is an improvement on the existing studies as we analyze our data using both time and frequency domain estimates. Besides, unlike other studies that did not offer structural breaks, the current study provides structural break dates with major events in the global socioeconomic space, which are key to identifying the date of bubbles and potential signs of commodity price bubbles. Our findings have some critical implications for investors, policy makers

Item Type: Article
Subjects: H Social Sciences > HG Finance
Depositing User: ADEDOYIN LAWAL
Date Deposited: 29 Jun 2021 10:47
Last Modified: 29 Jun 2021 10:47
URI: https://eprints.lmu.edu.ng/id/eprint/3052

Actions (login required)

View Item View Item