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Influence of cultural factors on price clustering and price resistance in China's stock markets

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  • Bill M. Cai
  • Charlie X. Cai
  • Kevin Keasey

Abstract

This paper builds on prior research by analysing the impact of cultural factors on both price clustering and price resistance in China's stock markets. The results support the presence of cultural factors impacting on price clustering with the digit 8 showing a higher propensity for clustering and the digits 4 and 7 showing a lower propensity in the A‐share market, where stock is denominated in renminbi and traded by mainland Chinese. These results are further supported by an analysis of the B‐share market, where cultural factors have no (or less) impact on the price of Chinese stocks traded by foreign investors in US dollars (or in Hong Kong dollars). A range of measures for price resistance show the digits 0 and 5 to be significant resistance points in the A‐share market. Although digit 8 cannot be considered as a resistance point, its resistance level is highest among the remaining numbers. In conclusion, cultural factors help to explain not only price clustering in the Chinese stock markets but price resistance levels as well, albeit at a weak level.

Suggested Citation

  • 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.
    • Handle: RePEc:bla:acctfi:v:47:y:2007:i:4:p:623-641
    DOI: 10.1111/j.1467-629X.2007.00221.x
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    References listed on IDEAS

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    Cited by:

    1. Michael O'Neill & Kent Wang & Zhangxin (Frank) Liu & Tom Smith, 2016. "A State-Price Volatility Index for China's Stock Market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 56(3), pages 607-626, September.
    2. Owyong, David & Wong, Wing-Keung & Horowitz, Ira, 2015. "Cointegration and causality among the onshore and offshore markets for China's currency," Journal of Asian Economics, Elsevier, vol. 41(C), pages 20-38.
    3. Vladim'ir Hol'y & Petra Tomanov'a, 2021. "Modeling Price Clustering in High-Frequency Prices," Papers 2102.12112, arXiv.org, revised Mar 2021.
    4. Narayan, Paresh Kumar & Smyth, Russell, 2013. "Has political instability contributed to price clustering on Fiji's stock market?," Journal of Asian Economics, Elsevier, vol. 28(C), pages 125-130.
    5. Li, Xin & Li, Shenghong & Xu, Chong, 2020. "Price clustering in Bitcoin market—An extension," Finance Research Letters, Elsevier, vol. 32(C).
    6. J˙lio Lob„o & Margarida Couto, 2019. "Are there Psychological Barriers in Asian Stock Markets?," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 15(1), pages 83-106.
    7. Tong V. Wang & Rogier J. D. Potter van Loon & Martijn J. van den Assem & Dennie van Dolder, 2016. "Number preferences in lotteries," Judgment and Decision Making, Society for Judgment and Decision Making, vol. 11(3), pages 243-259, May.
    8. Júlio Lobão & Natércia Fortuna & Franklin Silva, 2020. "Do psychological barriers exist in Latin American stock markets?," Revista de Analisis Economico – Economic Analysis Review, Universidad Alberto Hurtado/School of Economics and Business, vol. 35(2), pages 29-56, October.
    9. repec:cup:judgdm:v:11:y:2016:i:3:p:243-259 is not listed on IDEAS

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