قیمتهای خوشهای در بازار سرمایه ایران و علل موثر بر آن

نوع مقاله: مقاله پژوهشی

نویسندگان

1 عضو هیات علمی (استادیار) گروه مالی و بانکداری دانشگاه علامه طباطبائی (نویسنده مسئول)،

2 عضو هیات علمی (استادیار) گروه مالی و بانکداری دانشگاه علامه طباطبائی

چکیده

قیمت‌های خوشه‌ای به تمایل قیمت‌ها به اعداد گرد اشاره دارد. این موضوع در کشورهای مختلف و در خصوص متغیرهای مالی گوناگونی بررسی و نظریات متفاوتی برای توجیه آن ارائه شده است. در این پژوهش به بررسی وجود این رفتار در قیمت‌ها و عوامل موثر بر شدت آن در بازار سرمایه ایران پرداخته شده است. برای این منظور از داده‌های پربسامد بهره جسته و با تحلیل این داده‌ها با استفاده از آزمون‌ها و فنون آماری، شواهدی دال بر وجود این پدیده در بازار سرمایه ایران مشاهده شد. علاوه بر این از بین عوامل مختلف، متغیر اندازه و قیمت و همچنین متغیر مجازی تفکیک بورس و فرابورس بر شدت خوشه‌ای بودن قیمت‌ها موثر شناخته شد که از این بین، متغیر اندازه بر خلاف انتظار دارای ضریبی مثبت بود. نتایج تحلیل‌های انجام شده با فرضیات خرده قیمت‌گذاری، واکافت قیمت (صرفاً در مورد متغیر قیمت و نه اندازه شرکت) و مذاکره همخوانی دارد.
 

کلیدواژه‌ها


عنوان مقاله [English]

Stock Price Clustering and Factors Affecting on It in Iran Capital Market

نویسندگان [English]

  • Moslem Peymany Foroushany 1
  • Amir Hossein Erza 2
  • Mohammad Mahdi Bahrololoum 2
1 Assistant Professor of Finance, Allameh Tabataba'i University (Corresponding Author)
2 Assistant Professor of Finance, Allameh Tabataba'i University
چکیده [English]

Price clustering is the tendency of prices to be round numbers. This phenomenon is studied in different countries and in various financial variables and several hypotheses have been put forth to explain that. In this study, existence of this price clustering and factors affecting on it is tested in Iran capital market. To this, high frequency data is used and by means of statistical tests, the existence of price clustering is observed in Iran capital market. Furthermore, among all variables, only size, price and a dummy variable to distinguish between Tehran stock exchange and Iran Farabourse exchange, were effective on the intensity of price clustering and despite the expectations, size variable has a positive coefficient. Results are corresponded to odd-pricing, price resolution (just for price variable and not for size) and negotiation hypothesis.
 

کلیدواژه‌ها [English]

  • Price Clustering
  • Round Numbers
  • High Frequency Data

*       Aerts, W., G. Van Campenhout and T. Van Caneghem. (2008). Clustering in Dividends, Economic Psychology 29 (3): 276–284.

*       Aitken, M., Brown, P., Buckland, C., Izan, H., & Walter, T. (1996). Price clustering on the Australian Stock Exchange. Pacific-Basin Finance Journal (4), 297-314.

*       Aşçıoğlu, A., Comerton, C & McInish, T. H. (2007). Price Clustering on the Tokyo Stock Exchange. The Financial Review (42), 289‐301.

*       Ball, C. A., Torus, W. A & Tschoegl, A. E. (1985). The degree of price resolution: The case of the gold market. Future Markets (5), 29-43.

*       Brown, P., and J. Mitchell. (2008). Culture and Stock Price Clustering: Evidence from the Peoples’ Republic of China. Pacific-Basin Finance Journal 16 (1–2): 95–120

*       Brown, P., A. Chua, and J. Mitchell. (2002). The Influence of Cultural Factors on Price Clustering: Evidence from Asia-Pacific Stock Markets. Pacific-Basin Finance Journal 10 (3): 307–332.

*       Christie, W. G., & Schultz, P. H. (1994). Why do NASDAQ market makers avoid odd-eighth quotes? Journal of Finance (49), 1813-1840.

*       Ciccone, Stephen. J. Investor Optimism, False Hopes and the January Effect. Journal of Behavioral Finance 12, No. 3 (2011), pp. 158–168.

*       Davis, R. L., B. F. Van Ness, and R. A. Van Ness. (2014). Clustering of Trade Prices by High-Frequency and Non-High-Frequency Trading Firms. Financial Review 49 (2): 421–433.

*       Dechow, P. M., and H. You. (2012). Analysts’ Motives for Rounding EPS Forecasts. Accounting Review 87 (6): 1939–1966.

*       Easley, D., & O'Hara, M. (1987). Price, Trade Size, and Information in Securities Markets. Journal of Financial Economics, 19(1), 69 - 90.

*       Fama, Eugene. (1965). The Behavior of Stock Market Prices, Journal of Business, 38, pp. 34–105.

*       Fama, Eugene. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work, Journal of Finance, XXV, No. 2.

*       Fischer, A.M. (2004). Price Clustering in the FX Market: A Disaggregate Analysis using Central Bank Interventions. Working Paper, Study Center Gerzensee and CEPR.

*       Gibbons, Michael R., and Hess, Patrick J. (1981). Day of the Week Effects and Asset Returns, Journal of Business, 54, pp. 579-596.

*       Goodhart, C., & Curcio, R. (1991). The clustering of bid-ask prices and the spread in the foreign exchange market. London School of Economics (Discussion Paper 110).

*       Grossman, S. J., Miller, M. H., Cone, K. R., Fischel, D. R., & Ross, D. J. (1997). Clustering and competition in asset markets. Journal of Law and Economics (40), 23-60.

*       Gwilym, Owain AP, Clare, Andrew, Thomas, Stephen. (1998). Price clustering and bid-ask spreads in international bond futures.  International Financial Markets, Institutions and Money, 8 (3-4), pp. 377–391.

*       Hameed, A., & Terry, E. (1998). The effect of tick size on price clustering and trading volume. Business Finance and Accounting (25), 849-867.

*       Harris, L. (1991). Stock price clustering and discreteness. Review of Financial Studies (4), 389-415.

*       Harris, Lawrence. (1986). A Transaction Data Study of Weekly and Intra-Daily Patterns in Stock Returns. Financial Economics, 14, pp. 99–117.

*       He, Y., and C. Wu. (2006). Is Stock Price Rounded for Economic Reasons in The Chinese Markets? Global Finance Journal 17: 119–135.

*       Hewlett, Patrick. (2006). Clustering of order arrivals, price impact and trade path optimization. Deutsche Bank.

*       Hornik, J., Cherian, J., & Zakay, D. (1994). The influence of prototypic values on the validity of studies using time estimates. Journal of the Market Research Society, 36(2), 145-147.

*        Hu, Bill. Jiang, Christine. McInish Thomas  & Zhou Haigang. (2017). Price clustering on the Shanghai Stock Exchange. Applied Economics.
(49). pp. 2766-2778

*       Ikenberry, D. L., and J. P. Weston. (2008). Clustering in US Stock Prices after Decimalization. European Financial Management 14 (1): 30–54.

*       Kandel, S., O. Sarig, and A. Wohl. (2001). Do Investors Prefer Round Stock Prices? Evidence from IPO Auctions. Journal of Banking and Finance 25: 1543-1551.

*       Klumpp Joni M., Brorsen, B. Wade and Anderson, Kim B. (2005), The Preference for Round Number Prices, Southern Agricultural Economics Association annual meetings, Little Rock, Arkansas.

*       Lakonishok, Josef, and Smidt, Seymour. (1984). Volume and Turn-of-the-Year Behavior, Journal of Financial Economics, 13.

*       Mitchell, J. (2001). Clustering and Psychological Barriers: The Importance of Numbers. The Journal of Futures Markets (21), 395–428.

*       Niederhoffer, V. (1965). Clustering of stock prices. Operations Research (13), 258-265.

*       Niederhoffer, V. (1966). A new look at clustering of stock prices. Journal of Business (39), 309-313.

*       Osborne, M. F. (1962). Periodic structure in the Brownian motion of stock prices. Operations Research (10), 345-379.

*      Sonnemams, J. (2003). Price clustering and natural resistance points in the Dutch Stock Market: A natural experiment. Discussion Paper, University of Amsterdam