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Clustering and psychological barriers: the importance of numbers

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  • Robert I. Webb
  • Jason Mitchell

Abstract

The contemporary press frequently makes mention of, and identifies significance with, specific numerical values in financial markets. This focus has been suggested to result in clustering. Furthermore, these symbolic numbers are often referred to as psychological barriers. These effects are identified as a widespread phenomenon permeating into the economic decision making and financial market environments. This article outlines various arguments and rationale from the cultural, economic, and behavioral literature why clustering and other effects such as psychological barriers may be expected in financial markets. Evidence across a variety of literatures suggests that financial market clustering derives from a variety of sources. There is evidence from a cultural and conventional basis to suggest that number preference exists and that there is a natural tendency to round that derives from the development of the modern decimal system. The literature also provides valid behavioral and economic reasons as to why these effects may occur. However, no evidence is found to support the notion that clustering or barriers in financial markets would occur as a result of a natural order or as a product of the number progression or simply from the numbers themselves. © 2001 John Wiley & Sons, Inc. Jrl Fut Mark 21:395–428, 2001

Suggested Citation

  • 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.
  • Handle: RePEc:wly:jfutmk:v:21:y:2001:i:5:p:395-428
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    Cited by:

    1. Ross C Phillips & Denise Gorse, 2018. "Cryptocurrency price drivers: Wavelet coherence analysis revisited," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-21, April.
    2. Li, Xin & Li, Shenghong & Xu, Chong, 2020. "Price clustering in Bitcoin market—An extension," Finance Research Letters, Elsevier, vol. 32(C).
    3. Owain ap Gwilym & Evamena Alibo, 2003. "Decreased price clustering in FTSE100 futures contracts following a transfer from floor to electronic trading," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 23(7), pages 647-659, July.
    4. Ocean Fan Lu & David Giles, 2010. "Benford's Law and psychological barriers in certain eBay auctions," Applied Economics Letters, Taylor & Francis Journals, vol. 17(10), pages 1005-1008.
    5. Dowling, Michael & Cummins, Mark & Lucey, Brian M., 2016. "Psychological barriers in oil futures markets," Energy Economics, Elsevier, vol. 53(C), pages 293-304.
    6. Gunther Capelle-Blancard & Mo Chaudhury, 2007. "Price clustering in the CAC 40 index options market," Applied Financial Economics, Taylor & Francis Journals, vol. 17(15), pages 1201-1210.
    7. Florian El Mouaaouy, 2018. "Financial crime ‘hot spots’ – empirical evidence from the foreign exchange market," The European Journal of Finance, Taylor & Francis Journals, vol. 24(7-8), pages 565-583, May.
    8. Ashton, John K. & Hudson, Robert S., 2008. "Interest rate clustering in UK financial services markets," Journal of Banking & Finance, Elsevier, vol. 32(7), pages 1393-1403, July.
    9. Bill M. Cai & Charlie X. Cai & Kevin Keasey, 2007. "Influence of cultural factors on price clustering and price resistance in China's stock markets," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 47(4), pages 623-641, December.
    10. Robert Brooks & Edwyna Harris & Yovina Joymungul, 2013. "Price clustering in Australian water markets," Applied Economics, Taylor & Francis Journals, vol. 45(6), pages 677-685, February.
    11. Cummins, Mark & Dowling, Michael & Lucey, Brian M., 2015. "Behavioral influences in non-ferrous metals prices," Resources Policy, Elsevier, vol. 45(C), pages 9-22.
    12. Lucey, Michael E. & O'Connor, Fergal A., 2016. "Mind the gap: Psychological barriers in gold and silver prices," Finance Research Letters, Elsevier, vol. 17(C), pages 135-140.
    13. Urquhart, Andrew, 2017. "Price clustering in Bitcoin," Economics Letters, Elsevier, vol. 159(C), pages 145-148.
    14. Carol L. Osler, 2003. "Currency Orders and Exchange Rate Dynamics: An Explanation for the Predictive Success of Technical Analysis," Journal of Finance, American Finance Association, vol. 58(5), pages 1791-1820, October.
    15. Kunter Gunasti & Timucin Ozcan, 2016. "Consumer reactions to round numbers in brand names," Marketing Letters, Springer, vol. 27(2), pages 309-322, June.
    16. 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.
    17. Palao, Fernando & Pardo, Angel, 2012. "Assessing price clustering in European Carbon Markets," Applied Energy, Elsevier, vol. 92(C), pages 51-56.
    18. Brown, Philip & Mitchell, Jason, 2008. "Culture and stock price clustering: Evidence from The Peoples' Republic of China," Pacific-Basin Finance Journal, Elsevier, vol. 16(1-2), pages 95-120, January.
    19. Quinn Keefer & Galib Rustamov, 2018. "Limited attention in residential energy markets: a regression discontinuity approach," Empirical Economics, Springer, vol. 55(3), pages 993-1017, November.
    20. Kwong Wing Chau & Danika Wright & Ervi Liusman, 2018. "The cost of a lucky price," ERES eres2018_240, European Real Estate Society (ERES).
    21. Woodhouse, Sam Alan & Singh, Harminder & Bhattacharya, Sukanto & Kumar, Kuldeep, 2016. "Invisible walls: Do psychological barriers really exist in stock index levels?," The North American Journal of Economics and Finance, Elsevier, vol. 36(C), pages 267-278.

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