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Comparison of the Stock Price Clustering of stocks which are traded in the US and Germany—Is XETRA more efficient than the NYSE?

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Author Info
Kirsten Rüchardt () (Faculty of Economics and Management, Otto-von-Guericke University Magdeburg)
Bodo Vogt () (Faculty of Economics and Management, Otto-von-Guericke University Magdeburg)
Abstract

We analyze intraday trades of German stocks (Daimler Chrysler and SAP) that are traded simultaneously at the German stock market XETRA and the New York Stock Exchange (NYSE). At first glance, the stock price clustering seems to be less pronounced at the NYSE. But after converting Euro-prices into Dollar-prices, we obtain the result that the clustering is stronger at the NYSE indicating that XETRA is more efficient with respect to this measure. This difference in the clustering at the different stock markets should not be observable if the no-arbitrage condition would hold. We also discuss several explanations, like ease of negotiation, convenience and rounding, attraction, odd pricing, and aspiration level for stock price clustering. As a result we see that no model is able to capture all of our empirical observations.

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Publisher Info
Paper provided by Otto-von-Guericke University Magdeburg, Faculty of Economics and Management in its series FEMM Working Papers with number 09016.

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Length: 21 pages
Date of creation: May 2009
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Handle: RePEc:mag:wpaper:09016

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Related research
Keywords: behavioral finance; market microstructure; stock price clustering;

Find related papers by JEL classification:
C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
D40 - Microeconomics - - Market Structure and Pricing - - - General
G12 - Financial Economics - - General Financial Markets - - - Asset Pricing

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References listed on IDEAS
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  1. Christie, William G & Harris, Jeffrey H & Schultz, Paul H, 1994. " Why Did NASDAQ Market Makers Stop Avoiding Odd-Eighth Quotes?," Journal of Finance, American Finance Association, vol. 49(5), pages 1841-60, December. [Downloadable!] (restricted)
  2. Aitken, Michael & Brown, Philip & Buckland, Christine & Izan, H. Y. & Walter, Terry, 1996. "Price clustering on the Australian Stock Exchange," Pacific-Basin Finance Journal, Elsevier, vol. 4(2-3), pages 297-314, July. [Downloadable!] (restricted)
  3. 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. [Downloadable!]
  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. [Downloadable!] (restricted)
  5. Grossman, Sanford J, et al, 1997. "Clustering and Competition in Asset Markets," Journal of Law & Economics, University of Chicago Press, vol. 40(1), pages 23-60, April.
  6. Aslı Aşçıoğlu & Carole Comerton-Forde & Thomas H. McInish, 2007. "Price Clustering on the Tokyo Stock Exchange," The Financial Review, Eastern Finance Association, vol. 42(2), pages 289-301, 05. [Downloadable!] (restricted)
  7. Huang, Roger D. & Stoll, Hans R., 2001. "Tick Size, Bid-Ask Spreads, and Market Structure," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 36(04), pages 503-522, December. [Downloadable!]
  8. Harris, Lawrence, 1991. "Stock Price Clustering and Discreteness," Review of Financial Studies, Oxford University Press for Society for Financial Studies, vol. 4(3), pages 389-415. [Downloadable!] (restricted)
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