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A High-Frequency Analysis of Price Resolution and Pricing Barriers in Equities on the Adoption of a New Currency

Author

Listed:
  • Christos Alexakis

    (ESC [Rennes] - ESC Rennes School of Business)

  • Mark Cummins

    (DCU - Dublin City University [Dublin])

  • Michael Dowling

    (ESC [Rennes] - ESC Rennes School of Business)

  • Vasileios Pappas

    (University of Bath [Bath])

Abstract

We use ultra high frequency (trade by trade) data to demonstrate that equity price clustering and pricing predictability around psychologically important prices in Greece switches away from drachma-focused with the introduction of the euro, but does not immediately switch to euro-clustering. The change in trader price focus around the euro introduction addresses an open debate in the clustering literature on whether the presence of clustering is a bias related to current prices or anchoring to past prices. Our findings of a decline in drachma clustering, but lack of switch to euro effects supports the case for clustering being a trading feature that is slow to transfer to new pricing regimes. A key advantage of the ultra high frequency dataset is we are also able to demonstrate the presence of psychological pricing barriers related to each currency that are not detectable in daily data.

Suggested Citation

  • 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.
    • Handle: RePEc:hal:journl:hal-01994666
    DOI: 10.1080/00036846.2018.1430347
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    References listed on IDEAS

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    1. Victor Niederhoffer, 1965. "A New Look at Clustering of Stock Prices," The Journal of Business, University of Chicago Press, vol. 39, pages 309-309.
    2. 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.
    3. Raj Aggarwal & Brian M. Lucey, 2007. "Psychological barriers in gold prices?," Review of Financial Economics, John Wiley & Sons, vol. 16(2), pages 217-230.
    4. 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.
    5. Palao, Fernando & Pardo, Angel, 2012. "Assessing price clustering in European Carbon Markets," Applied Energy, Elsevier, vol. 92(C), pages 51-56.
    6. Bill Hu & Christine Jiang & Thomas McInish & Haigang Zhou, 2017. "Price clustering on the Shanghai Stock Exchange," Applied Economics, Taylor & Francis Journals, vol. 49(28), pages 2766-2778, June.
    7. Clifford A. Ball & Walter N. Torous & Adrian E. Tschoegl, 1985. "The degree of price resolution: The case of the gold market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 5(1), pages 29-43, March.
    8. 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.
    9. 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.
    10. Cummins, Mark & Dowling, Michael & Lucey, Brian M., 2015. "Behavioral influences in non-ferrous metals prices," Resources Policy, Elsevier, vol. 45(C), pages 9-22.
    11. 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.
    12. Aragon, George O. & Dieckmann, Stephan, 2011. "Stock market trading activity and returns around milestones," Journal of Empirical Finance, Elsevier, vol. 18(4), pages 570-584, September.
    13. Oded Palmon & Barton A. Smith & Ben J. Sopranzetti, 2004. "Clustering in Real Estate Prices: Determinants and Consequences," Journal of Real Estate Research, American Real Estate Society, vol. 26(2), pages 115-136.
    14. Meng, Lei & Verousis, Thanos & ap Gwilym, Owain, 2013. "A substitution effect between price clustering and size clustering in credit default swaps," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 139-152.
    15. 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.
    16. 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.
    17. Ohta, Wataru, 2006. "An analysis of intraday patterns in price clustering on the Tokyo Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 30(3), pages 1023-1039, March.
    18. 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.
    19. Comerton-Forde, Carole & Putnins, Talis J., 2011. "Measuring closing price manipulation," Journal of Financial Intermediation, Elsevier, vol. 20(2), pages 135-158, April.
    20. 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.
    21. Dowling, Michael & Cummins, Mark & Lucey, Brian M., 2016. "Psychological barriers in oil futures markets," Energy Economics, Elsevier, vol. 53(C), pages 293-304.
    22. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
    23. Victor Niederhoffer, 1965. "Clustering of Stock Prices," Operations Research, INFORMS, vol. 13(2), pages 258-265, April.
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