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Probability of information-based trading and the January effect

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  • Kang, Moonsoo

Abstract

We investigate the seasonality in the probability of information-based trading (PIN)-return relationship, the 'January PIN effect'. We find that on average stock returns decrease with PIN in January, in contrast to other calendar months. This pattern is more apparent for small stocks. We argue that this seasonality is related to the January effect. According to the analysis, the December selling pressure associated with the January effect decreases in PIN, especially for small stocks. This suggests that when the price bounces back in January, low-PIN stocks will exhibit a larger return within a small stock group, leading to the negative PIN-return pattern. Furthermore, this seasonality is not the same as other January anomalies associated with momentum and idiosyncratic risk.

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  • Kang, Moonsoo, 2010. "Probability of information-based trading and the January effect," Journal of Banking & Finance, Elsevier, vol. 34(12), pages 2985-2994, December.
    • Handle: RePEc:eee:jbfina:v:34:y:2010:i:12:p:2985-2994
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    Cited by:

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    5. Yan, Yuxing & Zhang, Shaojun, 2014. "Quality of PIN estimates and the PIN-return relationship," Journal of Banking & Finance, Elsevier, vol. 43(C), pages 137-149.
    6. Xuejun Jin & Hongze Li & Bin Yu, 2023. "The day‐of‐the‐month effect and the performance of the dollar cost averaging strategy: Evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(S1), pages 797-815, April.
    7. Lee, Dong Wook & Liu, Mark H., 2011. "Does more information in stock price lead to greater or smaller idiosyncratic return volatility?," Journal of Banking & Finance, Elsevier, vol. 35(6), pages 1563-1580, June.
    8. Diego Alonso Agudelo Rueda & Edwin Villarraga & Santiago Giraldo, 2012. "Asimetría en la información y su efecto en los rendimientos en los mercados accionarios latinoamericanos," Documentos de Trabajo de Valor Público 10669, Universidad EAFIT.
    9. Chen, Yifan & Zhao, Huainan, 2012. "Informed trading, information uncertainty, and price momentum," Journal of Banking & Finance, Elsevier, vol. 36(7), pages 2095-2109.
    10. Lynch, Andrew & Puckett, Andy & Yan, Xuemin (Sterling), 2014. "Institutions and the turn-of-the-year effect: Evidence from actual institutional trades," Journal of Banking & Finance, Elsevier, vol. 49(C), pages 56-68.
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    12. Lof, Matthijs & Bommel, Jos van, 2018. "Asymmetric information and the distribution of trading volume," Research Discussion Papers 1/2018, Bank of Finland.
    13. Schreder, Max, 2018. "Idiosyncratic information and the cost of equity capital: A meta-analytic review of the literature," Journal of Accounting Literature, Elsevier, vol. 41(C), pages 142-172.
    14. Coakley, Jerry & Kuo, Jing-Ming & Wood, Andrew, 2012. "The School’s Out effect: A new seasonal anomaly!," The British Accounting Review, Elsevier, vol. 44(3), pages 133-143.
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    16. Shiu, Yih-Wen & Lee, Chun I. & Gleason, Kimberly C., 2014. "Institutional shareholdings and the January effects in Taiwan," Journal of Multinational Financial Management, Elsevier, vol. 27(C), pages 49-66.
    17. Quan Gan & Wang Chun Wei & David Johnstone, 2015. "A faster estimation method for the probability of informed trading using hierarchical agglomerative clustering," Quantitative Finance, Taylor & Francis Journals, vol. 15(11), pages 1805-1821, November.
    18. Deb, Saikat Sovan & Kalev, Petko S. & Marisetty, Vijaya B., 2013. "Flexible price limits: The case of Tokyo Stock Exchange," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 24(C), pages 66-84.
    19. Cosmin Octavian Cepoi & Victor Dragotă & Ruxandra Trifan & Andreea Iordache, 2023. "Probability of informed trading during the COVID-19 pandemic: the case of the Romanian stock market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-27, December.

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