IDEAS home Printed from https://ideas.repec.org/a/eee/jrpoli/v38y2013i4p621-627.html
   My bibliography  Save this article

Iron ore spot price volatility and change in forward pricing mechanism

Author

Listed:
  • Ma, Yiqun

Abstract

To examine the impact of the change in forward pricing mechanism on the volatility of iron ore spot prices, we model the iron ore daily price of Platts IODEX from October 7, 2008 to September 21, 2012. The identified iron ore spot price tends to be less volatile after the introduction of quarterly pricing mechanism. Our main approaches are as follows: (i) to decompose the spot price of Platts IODEX into two subsamples and relate the result of the structural break to the date of the switch in the iron ore forward pricing mechanism; (ii) to apply the EGARCH (1, 1) model to simultaneously capture the long memory and the asymmetric effect on the volatility of the iron ore spot price; and (iii) to delineate the news impact curve to further interpret the asymmetric effect.

Suggested Citation

  • Ma, Yiqun, 2013. "Iron ore spot price volatility and change in forward pricing mechanism," Resources Policy, Elsevier, vol. 38(4), pages 621-627.
    • Handle: RePEc:eee:jrpoli:v:38:y:2013:i:4:p:621-627
    DOI: 10.1016/j.resourpol.2013.10.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0301420713000834
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.resourpol.2013.10.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Salisu, Afees A. & Fasanya, Ismail O., 2013. "Modelling oil price volatility with structural breaks," Energy Policy, Elsevier, vol. 52(C), pages 554-562.
    2. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-370, March.
    3. Arouri, Mohamed El Hédi & Lahiani, Amine & Lévy, Aldo & Nguyen, Duc Khuong, 2012. "Forecasting the conditional volatility of oil spot and futures prices with structural breaks and long memory models," Energy Economics, Elsevier, vol. 34(1), pages 283-293.
    4. Som Sekhar Bhattacharyya & Pradeep Kumar Deepak, 2012. "Comprehending the changing global iron ore trade service system and the dynamics of pricing," International Journal of Business and Globalisation, Inderscience Enterprises Ltd, vol. 9(1), pages 70-89.
    5. Paresh Kumar Narayan & Stephan Popp, 2010. "A new unit root test with two structural breaks in level and slope at unknown time," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(9), pages 1425-1438.
    6. Caporale, Tony & McKiernan, Barbara, 1997. "High and variable inflation: Further evidence on the Friedman hypothesis," Economics Letters, Elsevier, vol. 54(1), pages 65-68, January.
    7. Wilson, Jeffrey D., 2012. "Chinese resource security policies and the restructuring of the Asia-Pacific iron ore market," Resources Policy, Elsevier, vol. 37(3), pages 331-339.
    8. Engle, Robert F & Ng, Victor K, 1993. "Measuring and Testing the Impact of News on Volatility," Journal of Finance, American Finance Association, vol. 48(5), pages 1749-1778, December.
    9. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    10. Narayan, Paresh Kumar & Narayan, Seema, 2007. "Modelling oil price volatility," Energy Policy, Elsevier, vol. 35(12), pages 6549-6553, December.
    11. Engle, Robert F, 1983. "Estimates of the Variance of U.S. Inflation Based upon the ARCH Model," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 15(3), pages 286-301, August.
    12. Hammoudeh, Shawkat & Yuan, Yuan, 2008. "Metal volatility in presence of oil and interest rate shocks," Energy Economics, Elsevier, vol. 30(2), pages 606-620, March.
    13. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Su, Chi-Wei & Wang, Kai-Hua & Chang, Hsu-Ling & Dumitrescu–Peculea, Adelina, 2017. "Do iron ore price bubbles occur?," Resources Policy, Elsevier, vol. 53(C), pages 340-346.
    2. Liu, Yanxin & Li, Huajiao & Guan, Jianhe & Liu, Xueyong & Guan, Qing & Sun, Qingru, 2019. "Influence of different factors on prices of upstream, middle and downstream products in China's whole steel industry chain: Based on Adaptive Neural Fuzzy Inference System," Resources Policy, Elsevier, vol. 60(C), pages 134-142.
    3. Adewuyi, Adeolu O. & Wahab, Bashir A. & Adeboye, Olusegun S., 2020. "Stationarity of prices of precious and industrial metals using recent unit root methods: Implications for markets’ efficiency," Resources Policy, Elsevier, vol. 65(C).
    4. Ahmed, Walid M.A., 2019. "Islamic and conventional equity markets: Two sides of the same coin, or not?," The Quarterly Review of Economics and Finance, Elsevier, vol. 72(C), pages 191-205.
    5. Ma, Yiqun, 2021. "Do iron ore, scrap steel, carbon emission allowance, and seaborne transportation prices drive steel price fluctuations?," Resources Policy, Elsevier, vol. 72(C).
    6. Yufeng CHEN & Shuo YANG, 2022. "How Does the Reform in Pricing Mechanism Affect the World’s Iron Ore Price: A Time-Varying Parameter SVAR Model," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 83-103, April.
    7. Salisu, Afees A. & Fasanya, Ismail O., 2013. "Modelling oil price volatility with structural breaks," Energy Policy, Elsevier, vol. 52(C), pages 554-562.
    8. Nam T. Hoang & Bao H. Nguyen, 2018. "Oil and Iron Ore Price Shocks: What Are the Different Economic Effects in Australia?," The Economic Record, The Economic Society of Australia, vol. 94(305), pages 186-203, June.
    9. Ma, Yiqun & Wang, Junhao, 2019. "Co-movement between oil, gas, coal, and iron ore prices, the Australian dollar, and the Chinese RMB exchange rates: A copula approach," Resources Policy, Elsevier, vol. 63(C), pages 1-1.
    10. Zhu, Xuehong & Zheng, Weihang & Zhang, Hongwei & Guo, Yaoqi, 2019. "Time-varying international market power for the Chinese iron ore markets," Resources Policy, Elsevier, vol. 64(C).
    11. Ma, Yiqun, 2021. "Dynamic spillovers and dependencies between iron ore prices, industry bond yields, and steel prices," Resources Policy, Elsevier, vol. 74(C).
    12. Yiqun Ma & Wei Zhen, 2020. "Market Fundamentals and Iron Ore Spot Prices," The Economic Record, The Economic Society of Australia, vol. 96(315), pages 470-489, December.
    13. Adibi, Nabiollah & Ataee-pour, Majid, 2015. "Decreasing minerals׳ revenue risk by diversification of mineral production in mineral rich countries," Resources Policy, Elsevier, vol. 45(C), pages 121-129.
    14. Ahmed, Walid M.A., 2017. "On the dynamic interactions between energy and stock markets under structural shifts: Evidence from Egypt," Research in International Business and Finance, Elsevier, vol. 42(C), pages 61-74.
    15. Wu, Jinxi & Yang, Jie & Ma, Linwei & Li, Zheng & Shen, Xuesi, 2016. "A system analysis of the development strategy of iron ore in China," Resources Policy, Elsevier, vol. 48(C), pages 32-40.
    16. Wei, Jiangqiao & Ma, Zhe & Wang, Anjian & Li, Pengyuan & Sun, Xiaoyan & Yuan, Xiaojing & Hao, Hongchang & Jia, Hongxiang, 2022. "Multiscale nonlinear Granger causality and time-varying effect analysis of the relationship between iron ore futures and spot prices," Resources Policy, Elsevier, vol. 77(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Halkos, George E. & Tsirivis, Apostolos S., 2019. "Effective energy commodity risk management: Econometric modeling of price volatility," Economic Analysis and Policy, Elsevier, vol. 63(C), pages 234-250.
    2. Halkos, George & Tzirivis, Apostolos, 2018. "Effective energy commodities’ risk management: Econometric modeling of price volatility," MPRA Paper 90781, University Library of Munich, Germany.
    3. Nonejad, Nima, 2017. "Parameter instability, stochastic volatility and estimation based on simulated likelihood: Evidence from the crude oil market," Economic Modelling, Elsevier, vol. 61(C), pages 388-408.
    4. Auer, Benjamin R., 2016. "How does Germany's green energy policy affect electricity market volatility? An application of conditional autoregressive range models," Energy Policy, Elsevier, vol. 98(C), pages 621-628.
    5. Issler, João Victor, 1999. "Estimating and forecasting the volatility of Brazilian finance series using arch models (Preliminary Version)," FGV EPGE Economics Working Papers (Ensaios Economicos da EPGE) 347, EPGE Brazilian School of Economics and Finance - FGV EPGE (Brazil).
    6. Apergis, Nicholas & Payne, James E., 2017. "Volatility Modeling of U.S. Metropolitan Retail Gasoline Prices: An Empirical Note," Journal of Regional Analysis and Policy, Mid-Continent Regional Science Association, vol. 48(2), September.
    7. Chkili, Walid & Hammoudeh, Shawkat & Nguyen, Duc Khuong, 2014. "Volatility forecasting and risk management for commodity markets in the presence of asymmetry and long memory," Energy Economics, Elsevier, vol. 41(C), pages 1-18.
    8. Jean Pierre Fernández Prada Saucedo & Gabriel Rodríguez, 2020. "Modeling the Volatility of Returns on Commodities: An Application and Empirical Comparison of GARCH and SV Models," Documentos de Trabajo / Working Papers 2020-484, Departamento de Economía - Pontificia Universidad Católica del Perú.
    9. Wang, Yudong & Liu, Li & Ma, Feng & Wu, Chongfeng, 2016. "What the investors need to know about forecasting oil futures return volatility," Energy Economics, Elsevier, vol. 57(C), pages 128-139.
    10. Tarek Bouazizi & Mongi Lassoued & Zouhaier Hadhek, 2021. "Oil Price Volatility Models during Coronavirus Crisis: Testing with Appropriate Models Using Further Univariate GARCH and Monte Carlo Simulation Models," International Journal of Energy Economics and Policy, Econjournals, vol. 11(1), pages 281-292.
    11. Charles, Amélie & Darné, Olivier, 2017. "Forecasting crude-oil market volatility: Further evidence with jumps," Energy Economics, Elsevier, vol. 67(C), pages 508-519.
    12. Franses,Philip Hans & Dijk,Dick van & Opschoor,Anne, 2014. "Time Series Models for Business and Economic Forecasting," Cambridge Books, Cambridge University Press, number 9780521520911.
    13. Raúl De Jesús Gutiérrez & Reyna Vergara González & Miguel A. Díaz Carreño, 2015. "Predicción de la volatilidad en el mercado del petróleo mexicano ante la presencia de efectos asimétricos," Revista Cuadernos de Economia, Universidad Nacional de Colombia, FCE, CID, March.
    14. Chevallier, Julien & Ielpo, Florian, 2017. "Investigating the leverage effect in commodity markets with a recursive estimation approach," Research in International Business and Finance, Elsevier, vol. 39(PB), pages 763-778.
    15. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654.
    16. Allan Crawford & Marcel Kasumovich, 1996. "Does Inflation Uncertainty Vary with the Level of Inflation?," Staff Working Papers 96-09, Bank of Canada.
    17. Su, EnDer, 2014. "Measuring Contagion Risk in High Volatility State between Major Banks in Taiwan by Threshold Copula GARCH Model," MPRA Paper 58161, University Library of Munich, Germany.
    18. Ewing, Bradley T. & Malik, Farooq, 2017. "Modelling asymmetric volatility in oil prices under structural breaks," Energy Economics, Elsevier, vol. 63(C), pages 227-233.
    19. Lin, Yu & Xiao, Yang & Li, Fuxing, 2020. "Forecasting crude oil price volatility via a HM-EGARCH model," Energy Economics, Elsevier, vol. 87(C).
    20. Afees A. Salisu & Ismail O. Fasanya, 2012. "Comparative Performance of Volatility Models for Oil Price," International Journal of Energy Economics and Policy, Econjournals, vol. 2(3), pages 167-183.

    More about this item

    Keywords

    Iron ore price; Structural break; Volatility modelling;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • Q30 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - General

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jrpoli:v:38:y:2013:i:4:p:621-627. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/30467 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.