Study of the CoAnomaly in Tehran Stock Exchange

Document Type : Original Article


1 Ph.D Student in Finance, Yazd Branch, Islamic Azad University, Yazd, Iran

2 Assistant Professor, Department of Finance, Faculty of Management, Economics and Accounting, Yazd Branch, Islamic Azad University, Yazd, Iran



Anomaly correlation is among the essential topics that must be paid attention to in investment. Given the investment portfolio, the return is considered to be more than the expected return, and the premium risk of portfolio components, and portfolio components, and the correlation between portfolio components are investigated so that one can eventually achieve the optimal portfolio. The present study investigates the CoAnomaly in Tehran Stock Exchange. For this purpose, a simple measure of time series risk was presented as CoAnomaly (anomaly correlation) for stock market trade anomalies. This measure is the mean time-varying made up of 12 anomalies. Since the correlation between the underlying assets determines the portfolio variance, CoAnomaly is an important state variable for arbitrators that have a diverse anomaly portfolio to enhance performance. The information and data required in this study were obtained from the information on the firms listed in Tehran Stock Exchange over 2011-2020. Empirically, We show that, CoAnomaly is persistent and forecasts long-run aggregate volatility of the diversified anomaly portfolio. CoAnomaly positively predicts future average anomaly returns in the time series. On the other hand, results revealed that an increase in the CoAnomaly increases anomaly variance over the short term and long term.


  • Badri, Ahmad and Fouad Fath Elahi (2014), "Momentum Returns: Evidence from Tehran Stock Exchange", Investment Knowledge Research Quarterly, No. 9, pp. 1-20.
  • Izadinia, Nasser and Amin Hajiannejad, (2009), "Study and investigation of heredity Behavior in Selected Industries of Tehran Stock Exchange", Quarterly Journal of Stock Exchange, No. 7, p. 105-132.
  • Jahangiri Rad, Mostafa, Mohammad Marfou, and Mohammad Javad Salimi, (2014), "Study of investors’ group behavior in the Tehran Stock Exchange", Quarterly Journal of Experimental Studies in Financial Accounting, No. 42, pp. 141-158.
  • Haidarpour, Farzaneh, Yadaleh Tari Verdi, and Maryam Mehrabi (2013), "The Influence of Investors' Sentimental Tendencies on Stock Returns", Quarterly Journal of Securities Analysis, No. 17, pp. 1-13.
  • Sarlak, Kobra, Zahra Alipour Darvish, and Hamidreza Vakilifard (2012), "The Impact of Investors' Sentimental Decision Making and Fundamental Technique Variables on Stock Returns in Tehran Stock Exchange", Financial Knowledge of Securities Analysis, No. 16, pp. 1-12
  • Saeedi, Ali and Seyed Mohammad Javad Farhanian (2011), "investors’ heredity Behavior in Tehran Stock Exchange", Quarterly Journal of the Stock Exchange, No. 01, pp. 175-198.
  • Eslami Bidgoli, Gholamreza and Sara Shahriari (2007), "Study and Investigation of Investors’ Heredity Behavior Using Stock Return Deviations from Total Market Returns in Tehran Stock Exchange over 2001-2005" Accounting and Auditing Reviews, No. 49, Pp. 25-44.
  • Matin Fard, Mehran and Sohbat Salahvarzi. (2018), the impact of stock price synchronicity on stock price risk. Quarterly Journal of Financial Knowledge Securities Analysis.
  • Shams, Shahabuddin, and Amir Teymour Esfandiari Moghaddam. (2017), the impact of mass behavior on the performance of investment firms based on modern and postmodern portfolio theories. Financial Research 19 (1): 97-118
  • Zanjirdar, Majid and Sadaf Khojasteh. (2016), the impact of mass behavior of institutional investors on stock returns. Fiscal and Economic Policy Quarterly 4 (15): 119-115.
  • Nikbakht, Mohammad Reza;Amir Hossein Hosseinpour and Hossein Eslami Mofidabadi.(2016), Investigating the impact of investors' sentimental behavior and accounting information on stock prices.Empirical Accounting Research 6 (22): 245-219
  • Naderi Bani, Rahmatollah Arabsalehi, Mehdi, Kazemi, Iraj.(2009).investigating accounting anomalies of the Fama and French three-factor model at the firm level using the hierarchical Bayesian approach and Markov chain Monte Carlo simulation.Financial Accounting Research, 11 (3), 97-116.
  • James Tengyu Guo. (2019). "Anomaly Investing Out-of-Sample Performance and Intertemporal Considerations" SSRN ELSEVIER.
  • James Tengyu Guo. (2019). "Decomposing Momentum Spread" SSRN ELSEVIER.
  • James Tengyu Guo. (2019). "CoAnomaly Correlation Risk in Stock Market Anomalies" SSRN ELSEVIER.
  • Yao, J., CH. Ma., and W. Peng He. (2014). "Investor Herding Behavior of Chinese sStock Market". International Review of Economics and Finance, 29, pp 12-29.
  • M, and A. Bensaida (2014)."Herding Behavior and Trading Volume: Evidence from The American Indexes". International review of management and business research, 3 (2). pp 705 – 722.
  • McQueen, G., Pinegar, M. A., & Thorley, S. (1996). “Delayed Reaction to Good News and the Cross-Autocorrelation of Portfolio Returns”, Journal of Finance, 51, pp 889–919.
  • Blasco, N., P. Corredor, and S. Ferreruela. (2012). " Market Sentiment: A Key Factor of Investors’ Imitative Behavior", Accounting and Finance, 52, pp 663–689.
  • Al-Shboul, M. (2012). " Asymmetric Effects and The Herd Behavior in the Australian Equity Market", International Journal of Business and Management, 7 (7), pp 121- 140.
  • E. and M. Pereira. (2014). "Herding Behaviour and Sentiment: Evidence in a Small European Market", Spanish Accounting Review, 18 (1), pp 78–86.
  • Chih-Hsiang Chang، Shih-Jia Lin (2015).The effects of national culture and behavioral pitfalls on investors’ decision-making: Herding behavior in international stock markets Herding behavior in international stock markets, InternationalReview of Economics 00and Finance 37،380–392.
  • Rasheed, M. S., H. Bint Saeed, T. Yousaf, and F. Javed. (2018). Stock Price Synchronicity and Voluntary Disclosure in Perspective of Pakistan. European Online Journal of Natural and Social Sciences 7(2): 265
  • Gassen, J., H. Skaife, and D. Veenman. (2017). Illiquidity and the measurement of stock price synchronicity.
  • Galariotis, E.C., S. Krokida, and S.I. Spyrou. (2016). Herd behavior and equity market liquidity: Evidence from major markets, International Review of Financial Analysis.