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Detecting multiple-equilibria and chaos in oil prices and global commodity markets

Ata Ozkaya ORCID ↗

International Journal of Research in Business and Social Science · 2022 · Vol. 11 / Issue 6 · 350-361

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Overview

Abstract

In the past 20 years, commodity markets have been examined under the hypothesis of whether the prices exhibit recurrent patterns or follow the stochastic processes. In this study, we analyze both global energy markets and food markets to detect the presence of multiple equilibria, which may lead to higher spikes in prices and to the occurrence of intermittency. This study focuses on daily prices in Brent petrol and Natural gas markets from 23 May 2017 to 23 May 2022. This time interval covers the period where extraordinary economic and financial policies have been preferred in countries worldwide amid the Covid-19 pandemic crisis. On the other hand, the study investigates global Food index monthly data from 2007M11 to 2022M4. Similarly, the time interval under examination points out the effects of the 2008 global crisis where expansionary monetary policies have been implemented both by the Federal Reserve of the U.S and the European Central Bank. We employed the phase-space reconstruction method for the Crude oil Brent Europe and spot Natural gas prices series, and global Food index data respectively. The main findings of the study demonstrate that commodity markets do not converge to a unique equilibrium level, instead multiple equilibria persist and chaotic behavior occurs. The presence of multiple equilibria leads to an increase in complexity and recurrently causes volatility in commodity markets, which may have spillover effects on other financial markets. Our results suggest that these effects simultaneously increase global inflationary pressures. From the perspective of policy making, it is crucial to establish a strategy to eliminate multiple equilibria and prevent high price spikes. Our findings have important implications for Central bank policies in emerging markets and portfolio and risk management.

Keywords: {'name': 'multiple equilibria'}, {'name': 'intermittency'}, {'name': 'oil prices'}, {'name': 'food index'}, {'name': 'natural gas prices'}, {'name': 'chaos'}, {'name': 'market efficiency'}

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Ata Ozkaya
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DOI: 10.1007/978-1-4612-0763-4

DOI: 10.1016/S0140-9883(00)00079-7

DOI: 10.1002/fut.21600

DOI: 10.1016/j.eneco.2011.10.004

DOI: 10.1016/j.jebo.2003.05.001

DOI: 10.2307/2534702

DOI: 10.1016/S0893-6080(02)00096-5

DOI: 10.1109/TNNLS.2016.2630802

DOI: 10.1016/j.resourpol.2021.102386

Brock, W.A., & Malliaris A.G. (1989). Differential Equations, Stability and Chaos in Dynamic Economics. North Holland, Amsterdam.

DOI: 10.1111/j.1540-6261.1992.tb04681.x

DOI: 10.4324/9780203855058

DOI: 10.1016/j.apenergy.2010.02.020

DOI: 10.1080/13504850500425436

DOI: 10.5547/ISSN0195-6574-EJ-Vol19-No2-10

DOI: 10.1209/0295-5075/4/9/004

Elder, J., & Serletis, A. (2008). “Oil Price Uncertainty.” Mimeo. Department of Economics, University of Calgary.

DOI: 10.1111/j.1540-6261.1970.tb00518.x

DOI: 10.1016/0167-2789(92)90210-E

DOI: 10.1016/S0927-5398(97)00022-4

DOI: 10.1016/S0304-4076(02)00207-5

DOI: 10.3386/w14492

DOI: 10.1063/1.166424

Hendricks D., Kambhu, J. & Mosser, P. (2007). New Directions For Understanding Systemic Risk. Federal Reserve Economic Policy Review, 13, 2.

DOI: 10.1016/j.asieco.2016.08.005

DOI: 10.1016/0375-9601(94)90991-1

DOI: 10.1017/CBO9780511755798

DOI: 10.1103/PhysRevA.45.3403

DOI: 10.1016/j.jmacro.2005.10.011

DOI: 10.1007/3-540-28556-3_11

DOI: 10.1016/j.eneco.2008.12.009

DOI: 10.1016/j.eneco.2018.07.009

DOI: 10.5547/ISSN0195-6574-EJ-Vol16-No4-2

DOI: 10.1257/089533003321164958

Mandelbrot, B.B., & Hudson R.L. (2004). The (Mis)Behavior of Markets: a Fractal View of Risk, Ruin & Reward. Basic Books, New York.

DOI: 10.1016/j.physrep.2006.11.001

DOI: 10.1016/j.eneco.2018.04.024

DOI: 10.1016/j.eneco.2020.105036

DOI: 10.5547/ISSN0195-6574-EJ-Vol28-No3-2

DOI: 10.5547/ISSN0195-6574-EJ-Vol27-No4-4

DOI: 10.1016/S0960-0779(03)00327-8

DOI: 10.1515/9781400831722

DOI: 10.1016/j.eneco.2004.04.009

DOI: 10.1016/j.eneco.2007.09.002

DOI: 10.5547/ISSN0195-6574-EJ-Vol20-No1-5

DOI: 10.3390/e16126415

DOI: 10.1007/BFb0091924

DOI: 10.1016/0167-2789(85)90011-9