Commodity Pricing through Crises
Giulio Cifarelli
International Journal of Finance & Banking Studies · 2025 · Vol. 14 / Issue 3 · 31-43
Publication metrics
External links open provider records or DOI searches. Provider counts are not combined. Mendeley readership measures saves, not citations.
Dimensions
Live provider badge. If unavailable, use the Dimensions link above.
Observed 21 Oct 2026, 00:21 UTC
Observed 21 Oct 2026 00:22 UTC
OpenAlex and Mendeley observations refresh on article visits, at most once per 24 hours. Unavailable data is not zero. Google Scholar opens a DOI search.
Citations received by this article, grouped by the year of the citing work. Crossref and OpenAlex lifetime totals remain separate in Publication metrics.
2017–2026 Annual history last updated:
Citations received
OpenAlex · year of the citing work
Hover over a year or focus the chart and use arrow keys to inspect values.
2017–2026 annual-history window. 2026 is year to date. Unknown years have gaps.
View data & coverage
2026 is incomplete. Within a successfully fetched ten-year window, omitted years mean zero. Years beyond a saved observation’s window remain unknown (—). Older citations are excluded, so this chart’s sum may differ from the OpenAlex lifetime total. The date above belongs to this annual history; an unsuccessful refresh keeps the previous observation.
Abstract
The pricing of six highly liquid futures commodity contracts is investigated using a Markov switching procedure. The data set spans an exceptionally turbulent period, characterized by a complex interplay of economic/financial and political shocks. Markov switching analysis exploits time series nonlinearity to identify the nature and the timing of the implicit changes of regime. Building on a HAM framework, we use the time varying parameterization of the transition probability estimates to link these shifts to exogenous variables. We provide in this way additional information on the co-movement of the time series and on their regime shifts, eventually conducive to herding pricing behaviour. The WTI oil futures price and DJIA stock index are used as proxies for global shocks as they turn out to be the main common drivers of the changes in regime of most futures commodity prices.
Keywords: {'name': 'HAM Commodity pricing'}, {'name': 'Markov Switching'}, {'name': 'Time-Varying Transition Probabilities Synchronization'}
Authors & affiliations
Giulio Cifarelli
Affiliation not supplied
Deposited references
Supplied references, not a list of publications citing this article.
DOI: 10.1111/j.1746-1049.2006.00004.x
DOI: 10.1016/j.najef.2014.06.009
DOI: 10.1080/1540496X.2015.1011520
Baker, R., Bloom, N., Davis, S, J., (2025), Global Economic Policy Uncertainty Index: Current Price Adjusted GDP [GEPUCURRENT], retrieved from FRED, Federal Reserve Bank of St. Louis; https://fred.stlouisfed.org/series/GEPUCURRENT.
DOI: 10.1111/jtsa.12211
DOI: 10.1111/j.1540-6261.1995.tb04790.x
Brock W.A., Dechert, W.D., Scheinkman, J.A., (1987), A Test for Independence Based on the Correlation Dimension, Department of Economics, University of Wisconsin-Madison, SSRI Working Paper n. 8702.
DOI: 10.2307/2171879
DOI: 10.1016/S0165-1889(98)00011-6
DOI: 10.1016/j.ememar.2008.02.005
DOI: 10.2139/ssrn.4122049
DOI: 10.1007/978-3-319-07470-2_12
DOI: 10.1093/oso/9780198773917.003.0010
DOI: 10.1002/(SICI)1099-1158(199601)1:1<55::AID-IJFE5>3.0.CO;2-C
DOI: 10.1002/for.2753
DOI: 10.1080/07350015.1994.10524545
DOI: 10.1016/S0304-4076(97)00096-1
Frankel, J.A., Froot, K.A., (1986) Understanding the US Dollar in the Eighties: The Expectations of Chartists and Fundamentalists, Economic Record, 62, p. 24-38.
Kao, C.-W., Kleykamp, D., Wan J.-Y., (2016), Nonlinear Oil Price Dynamics and the Impact of Heterogeneous Agents, available at DOI: 10.3966/054696002015060097003
DOI: 10.2307/1912559
DOI: 10.1016/j.jeconom.2005.01.023
DOI: 10.2139/ssrn.742384
DOI: 10.1002/fut.21897
DOI: 10.1016/j.jempfin.2012.04.011
DOI: 10.2139/ssrn.1857398
DOI: 10.1016/j.eneco.2016.02.015
Psaradakis, Z., Sola, M., (2017), Markov-Switching Models with State-Dependent Time-Varying Transition Probabilities, BWPEF 1702, Birbeck College, London.
DOI: 10.1007/s00181-006-0100-7
Santabárbara, D., (2017), The Oil Market: Recent Developments and Outlook. Banco de España, Analytical Articles Economic Bulletin 3/2017.
DOI: 10.1111/j.1540-6261.1997.tb03807.x
DOI: 10.1016/S0378-4371(04)00848-9
DOI: 10.1016/j.physa.2004.11.015