CiteNScope — Scholarly Index & Analytics
Discover / IJFBSPUBLICATION RECORD

Commodity Pricing through Crises

Giulio Cifarelli

International Journal of Finance & Banking Studies · 2025 · Vol. 14 / Issue 3 · 31-43

Research reach

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.

CROSSREF CITATIONS0

Observed 21 Oct 2026, 00:21 UTC

OpenAlex · Citations0Cached provider observation

Observed 21 Oct 2026 00:22 UTC

Mendeley · Readers—No verified count available

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.

OpenAlex / Citation year

Annual citations to this article

View provider totals ↑

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

OpenAlex

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.

Overview

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