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Behavioral Influences in Non-Ferrous Metals Prices

Author

Listed:
  • Mark Cummins

    (Dublin City University Business School)

  • Brian M. Lucey

    (Institute for International Integration Studies, Trinity College Dublin)

  • Michael M. Dowling

    (Dublin City University Business School)

Abstract

Recent research has identified the presence of behavioral influences on traders in predominantly professionally traded markets such as oil, gold, and foreign exchange. Previous research had largely confined behavioral-based investigations to equity markets due to an assumption that noise traders would drive any influence and these traders were mainly absent from the professionally traded markets. This paper extends this research to the non-ferrous metals markets and demonstrates similar influences on prices. It is shown that psychological price barriers, where there is predictable trading patterns around psychologically important price points, are important. Specifically, lead, zinc, and aluminium alloy, show anomalous price reactions in the days particularly following a breach of a $1,000 price point. There is also evidence presented of negative price clustering before key price barriers. Subperiod tests further indicate that the relevant psychological price point is dependent on average prices. Recognizing the multiple hypothesis testing nature of the study, generalized Bonferroni corrections are implemented to provide a robust control for the possibility of data mining. This represents a first investigation of behavioral influences in non-ferrous metals prices, and suggests these markets are not immune to trader biases influencing the setting of prices.

Suggested Citation

  • Mark Cummins & Brian M. Lucey & Michael M. Dowling, 2014. "Behavioral Influences in Non-Ferrous Metals Prices," The Institute for International Integration Studies Discussion Paper Series iiisdp459, IIIS.
  • Handle: RePEc:iis:dispap:iiisdp459
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    References listed on IDEAS

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    1. Todorova, Neda & Worthington, Andrew & Souček, Michael, 2014. "Realized volatility spillovers in the non-ferrous metal futures market," Resources Policy, Elsevier, vol. 39(C), pages 21-31.
    2. Victor Niederhoffer, 1965. "A New Look at Clustering of Stock Prices," The Journal of Business, University of Chicago Press, vol. 39, pages 309-309.
    3. Fama, Eugene F., 1998. "Market efficiency, long-term returns, and behavioral finance," Journal of Financial Economics, Elsevier, vol. 49(3), pages 283-306, September.
    4. Sullivan, Ryan & Timmermann, Allan & White, Halbert, 2001. "Dangers of data mining: The case of calendar effects in stock returns," Journal of Econometrics, Elsevier, vol. 105(1), pages 249-286, November.
    5. Raj Aggarwal & Brian M. Lucey, 2007. "Psychological barriers in gold prices?," Review of Financial Economics, John Wiley & Sons, vol. 16(2), pages 217-230.
    6. Robert I. Webb & Jason Mitchell, 2001. "Clustering and psychological barriers: the importance of numbers," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 21(5), pages 395-428, May.
    7. Joshua D. Coval & Tyler Shumway, 2005. "Do Behavioral Biases Affect Prices?," Journal of Finance, American Finance Association, vol. 60(1), pages 1-34, February.
    8. Tokic, Damir, 2011. "Rational destabilizing speculation, positive feedback trading, and the oil bubble of 2008," Energy Policy, Elsevier, vol. 39(4), pages 2051-2061, April.
    9. Sonnemans, Joep, 2006. "Price clustering and natural resistance points in the Dutch stock market: A natural experiment," European Economic Review, Elsevier, vol. 50(8), pages 1937-1950, November.
    10. Clinton Watkins & Michael McAleer, 2003. "Pricing of Non-ferrous Metals Futures on the London Metal Exchange," CIRJE F-Series CIRJE-F-213, CIRJE, Faculty of Economics, University of Tokyo.
    11. Clinton Watkins & Michael McAleer, 2004. "Econometric modelling of non‐ferrous metal prices," Journal of Economic Surveys, Wiley Blackwell, vol. 18(5), pages 651-701, December.
    12. Buncic, Daniel & Moretto, Carlo, 2015. "Forecasting copper prices with dynamic averaging and selection models," The North American Journal of Economics and Finance, Elsevier, vol. 33(C), pages 1-38.
    13. Cochran, Steven J. & Mansur, Iqbal & Odusami, Babatunde, 2012. "Volatility persistence in metal returns: A FIGARCH approach," Journal of Economics and Business, Elsevier, vol. 64(4), pages 287-305.
    14. David Hirshleife, 2015. "Behavioral Finance," Annual Review of Financial Economics, Annual Reviews, vol. 7(1), pages 133-159, December.
    15. Joseph P. Romano & Azeem M. Shaikh & Michael Wolf, 2010. "Hypothesis Testing in Econometrics," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 75-104, September.
    16. David Hirshleifer, 2001. "Investor Psychology and Asset Pricing," Journal of Finance, American Finance Association, vol. 56(4), pages 1533-1597, August.
    17. David L. Ikenberry & James P. Weston, 2008. "Clustering in US Stock Prices after Decimalisation," European Financial Management, European Financial Management Association, vol. 14(1), pages 30-54, January.
    18. O’Connell, Paul G. J. & Teo, Melvyn, 2009. "Institutional Investors, Past Performance, and Dynamic Loss Aversion," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 44(1), pages 155-188, February.
    19. Batten, Jonathan A. & Ciner, Cetin & Lucey, Brian M., 2010. "The macroeconomic determinants of volatility in precious metals markets," Resources Policy, Elsevier, vol. 35(2), pages 65-71, June.
    20. M. F. M. Osborne, 1962. "Periodic Structure in the Brownian Motion of Stock Prices," Operations Research, INFORMS, vol. 10(3), pages 345-379, June.
    21. Utpal Bhattacharya & Craig W. Holden & Stacey Jacobsen, 2012. "Penny Wise, Dollar Foolish: Buy-Sell Imbalances On and Around Round Numbers," Management Science, INFORMS, vol. 58(2), pages 413-431, February.
    22. Jerry Coakley & Jian Dollery & Neil Kellard, 2011. "Long memory and structural breaks in commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 31(11), pages 1076-1113, November.
    23. Dorfleitner, Gregor & Klein, Christian, 2009. "Psychological barriers in European stock markets: Where are they?," Global Finance Journal, Elsevier, vol. 19(3), pages 268-285.
    24. Donaldson, R. Glen & Kim, Harold Y., 1993. "Price Barriers in the Dow Jones Industrial Average," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 28(3), pages 313-330, September.
    25. Cummins, Mark, 2013. "EU ETS market interactions: The case for multiple hypothesis testing approaches," Applied Energy, Elsevier, vol. 111(C), pages 701-709.
    26. Narayan, Paresh Kumar & Narayan, Seema & Popp, Stephan, 2011. "Investigating price clustering in the oil futures market," Applied Energy, Elsevier, vol. 88(1), pages 397-402, January.
    27. Pierdzioch, Christian & Rülke, Jan-Christoph & Stadtmann, Georg, 2013. "Forecasting metal prices: Do forecasters herd?," Journal of Banking & Finance, Elsevier, vol. 37(1), pages 150-158.
    28. Richard Heaney, 2006. "An empirical analysis of commodity pricing," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 26(4), pages 391-415, April.
    29. Bharati, Rakesh & Crain, Susan J. & Kaminski, Vincent, 2012. "Clustering in crude oil prices and the target pricing zone hypothesis," Energy Economics, Elsevier, vol. 34(4), pages 1115-1123.
    30. Victor Niederhoffer, 1965. "Clustering of Stock Prices," Operations Research, INFORMS, vol. 13(2), pages 258-265, April.
    31. Mitchell, Jason & Izan, H.Y., 2006. "Clustering and psychological barriers in exchange rates," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 16(4), pages 318-344, October.
    32. Campbell R. Harvey & Yan Liu & Heqing Zhu, 2014. ". . . and the Cross-Section of Expected Returns," NBER Working Papers 20592, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Wang, Xiao-Qing & Wu, Tong & Zhong, Huaming & Su, Chi-Wei, 2023. "Bubble behaviors in nickel price: What roles do geopolitical risk and speculation play?," Resources Policy, Elsevier, vol. 83(C).
    2. Holmes, Mark J. & Otero, Jesús, 2023. "Psychological price barriers, El Niño, La Niña: New insights for the case of coffee," Journal of Commodity Markets, Elsevier, vol. 31(C).
    3. Berk, Ales S. & Cummins, Mark & Dowling, Michael & Lucey, Brian M., 2017. "Psychological price barriers in frontier equities," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 49(C), pages 1-14.
    4. Christos Alexakis & Mark Cummins & Michael Dowling & Vasileios Pappas, 2018. "A high-frequency analysis of price resolution and pricing barriers in equities on the adoption of a new currency," Applied Economics, Taylor & Francis Journals, vol. 50(36), pages 3949-3965, August.
    5. Qu, Qiushi & Wang, Limao & Cao, Zhi & Zhong, Shuai & Mou, Chufu & Sun, Yanzhi & Xiong, Chenran, 2019. "Unfolding the price effects of non-ferrous industry chain on economic development: A case study of Yunnan province," Resources Policy, Elsevier, vol. 61(C), pages 1-20.
    6. Christos Alexakis & Mark Cummins & Michael Dowling & Vasileios Pappas, 2018. "A High-Frequency Analysis of Price Resolution and Pricing Barriers in Equities on the Adoption of a New Currency," Post-Print hal-01994666, HAL.
    7. Ciner, Cetin & Lucey, Brian & Yarovaya, Larisa, 2020. "Spillovers, integration and causality in LME non-ferrous metal markets," Journal of Commodity Markets, Elsevier, vol. 17(C).
    8. Narayan, Paresh Kumar, 2022. "Evidence of oil market price clustering during the COVID-19 pandemic," International Review of Financial Analysis, Elsevier, vol. 80(C).

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    More about this item

    Keywords

    psychological barriers; clustering; non-ferrous metals;
    All these keywords.

    JEL classification:

    • G13 - Financial Economics - - General Financial Markets - - - Contingent Pricing; Futures Pricing
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • L61 - Industrial Organization - - Industry Studies: Manufacturing - - - Metals and Metal Products; Cement; Glass; Ceramics

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