Proposing a model for assessing Herding behavior in the Iranian capital market using meta-heuristic algorithms

Document Type : Original Article

Authors

1 Ph.D. Student of Accounting, South Tehran Branch, Islamic Azad University, Tehran, Iran

2 Associate Professor, Department of Accounting, South Tehran Branch, Islamic Azad University, Tehran, Iran

3 Assistant Professor, Department of Accounting, South Tehran Branch, Islamic Azad University, Tehran, Iran.

Abstract

The main purpose of this article is to provide a model for assessing the Herding behavior of investors in the Iranian capital market based on fundamental and non-fundamental factors using meta-heuristic algorithms, based on DNA and racial complement calculations. The statistical population of the present study includes all companies that have been active in the Tehran Stock Exchange during the period of 2009 to 2019, and 129 companies were selected as a statistical sample. Fundamental and non-fundamental factors were identified as factors affecting the mass behavior of investors and after collecting data, meta-heuristic algorithms were used to predict the dependent variable. Comparison of the results of meta-heuristic algorithms also shows that the prediction error according to MSE and MAPE criteria in the shrimp batch algorithm is less than that in the three humpback whale algorithms, the improved genetic algorithm and the simple genetic algorithm; The prediction error rate according to the RMSE criterion in the humpback whale algorithm is less than that in three shrimp batch movement algorithms, improved genetics and simple genetics. On the other hand, the execution time of a simple genetic algorithm is less than the other three algorithms. In general, it can be said that the shrimp batch movement algorithm and the humpback whale algorithm are better than the simple and improved genetic algorithm in predicting the mass behavior of investors in the Iranian capital market and have higher accuracy.

Keywords

References

  • Adam Zaremba, Adam  Szyszka,  Andreas Karathanasopoulos, Mateusz  Mikutowski(2020) Herding for profits: Market breadth and the cross-section of global equity returns. Economic Modelling Available online 16 April 2020.
  • Amihud, Y. (2002). Illiquidity and stock returns: cross-section and time-series effects. Journal of Financial Markets, 5(1), 31-56. An Experimental Analysis. The Journal of Finance, 60(1). An Experimental Analysis. The Journal of Finance, 60(1).
  • Axel Buchner, Abdulkadir  Mohamed, Armin  Schwienbacher (2020) Herd behaviour in buyout investments . Journal of Corporate Finance, Volume 60, February 2020, 101503
  • Balcilar, M., Demirer , R., & Hammoudeh , S. (2014). What Drives Herding in Oil-Rich, Developing Stock Markets? Relative Roles of Own Volatility and Global Factors.
  • Banerjee, A., (1992), “A Simple Model of Herd Behavior” Quarterly Journal of Economics.No.3, Vol.107
  • Bashir et. Al. (2013).» Impact of Behavioral Biases On Investor Decision Making: Male Vs Female«. IOSR Journal of Business and Management, 10 (3), 60-68.
  • Belgacem, A., & Lahiani, A. (2013). Herding Behaviour Around US Herding Behaviour Around US. The Journal of Applied Business Research , 29(5), 1401-1410.
  • Belgacem, A., & Lahiani, A. (2013). Herding Behaviour Around US Herding Behaviour Around US. The Journal of Applied Business Research , 29(5), 1401-1410.
  • Bikchandani, S., & Sharma, S. (2001). Herd Behaviour in Financial Markets. IMF Staff Papers, 47(3), 279-310.
  • Blasco, N., P. Corredor, and S. Ferreruela. (2012). " Market Sentiment: A Key Factor of Investors’ Imitative Behavior", Accounting and Finance, 52, pp 663–689.
  • Bohl, M., Siklos, P. (2008). Empirical Evidence on Feedback Trading in Mature and Emerging Stock Markets . Applied Financial Economics, 18, 1379-1389.
  • Cakan, E., & Balagyozyan, A. (2016). Sectoral Herding: Evidence from an Emerging Market.
  • Chang, E. C., Korana, A., & Cheng, J. W. (2000). An Examination of Herd Behaviour in Equity Markets: An International Perspective. Journal of Banking and Finance, 24, 1651-1679.
  • Chiang, T. C., & Zheng, D. (2010). An empirical analysis of herd behaviour in global stock markets. Journal of Banking & Finance, 34 (8), 1911-1921.
  • Choi, S. (2016). Herding among local individual investors: Evidence from online and offline trading. Economic Letters, 144.
  • Chong, T. T.-L., Liu , X., & Zhu, C. (2016). What Explains Herd Behaviour in the Chinese Stock Market? MPRA(Paper No. 72100), (pp. 1-25). Retrieved November 11, 2016, from https://mpra.ub.uni-de/72100/1/MPRA_paper_72100.pdf
  • Christie, W. G., & Huang, R. D. (1995). Following the Pied Piper: Do Individual Returns Herd Around the Market. Financial Analysts Journal, 51(4), 31-37.
  • Corcoran, J. (2013). Russia Corporate Scandals ‘Striking,’ Prosperity CEO Says. Retrieved
  • Dang, H. V., & Lin, M. (2016). Herd mentality in the stock market: On the role of idiosyncratic participants with heterogeneous information. 48(c), 247-260.
  • Daniel, K., Hirshleifer, D., & Subrahmanyam, A. (1998). Investor Psychology and Security Market Under- and Overreactions. The Journal of Finance, 53(6), 1839-1885.
  • De Long, B., Shleifer, A., Summers, L., & Waldman, R. (1990). Positive Feedback Investment Strategies and Destabilizing Rational Speculation. The Journal of Finance, 45(2), 379395.
  • Demir, N., & Solakoglu, M. N. (2016). Herding in Middle Eastern Frontier Markets -Are local and Global Factors Important. Handbook of Frontier Markets - Evidance from Middle East, North Africa and International Comperatve Studies,2, Section A, 3-15. Economics and Finance Review, 4(5), 14-30.
  • Fadeeva, A. (2015). Российские нефтяные компании оказались самыми эффективными и доходными в мире [Russian Oil Companies appeared to be most efficient and profitable in the world]. Retrieved February 17, 2017, from Vedomosti:
  • Fama, E. F. (1970). Efficient Capital Markets: A Review of Theory and Empirical Work. The Journal of Finance, 25(2), 383-417.
  • Fama, E. F., & French, K. R. (1995). Size and Book-to-Market Factors in Earnings and Returns. The Journal of Finance, 50, 131-155.
  • Filip, A., Pochea, M., & Pece, A. (2015). The Herding Behaviour of Investors in the CEE Stocks Markets. Procedia Economics and Finance, 32, 307-315.
  • Froot, A, Scharfestein, S., and Stein, J. (1992) “Herd on the Street: Informational Inefficiencies in a Market with Short-Term Speculation,” Journal of finance, No.4.
  • Galariotis, E. C., Rong, W., & Spyrou, S. I. (2015). Herding on fundamental information: A comparative study. Journal of Banking & Finance, 50, 589-598.
  • Garg, A., & Jindhal, K. (2014). Herding Behaviour in an Emerging Stock Market. The IUP Journal of Applied Finance, 20(2), 18-36.
  • Gümbel, A. (2005). Herding in delegated portfolio management: When is comparative performance information desirable? European Economic Review, 49(3), 599-626.
  • Güvercin, A. (2016). Sentimental Herding: The Role of Regional and Global Shocks in Egyptian and Saudi Stock Markets. Sosyoekonomi, 24(27), 25-32.
  • Haigh, M. S., & List, J. A. (2005). Do Professional Traders Exhibit Myopic Loss Aversion?
  • Hedesström, M., Gärling, T., Andersson, M., & Biel, A. (2015). Effects of bonuses on diversification in delegated stock portfolio management. Journal of Behavioural and Experimental Finance, 7, 60-70.
  • Iwasaki, I. (2014). Global financial crisis, corporate governance, and firm survival:The Russian experience. Journal of Comparative Economics, 42(1), 178-211. January 7, 2017, from Bloomberg: https://www.bloomberg.com/news/articles/2013-
  • Jensen, M. C. (1967). The Performance of Mutual Funds in the Period 1945-1964 . Journal of Finance, 23(2), 389-416. Journal of Accounting and Finance, 16(4), 87-98.
  • Keim, D. B. (1983). Size-related anomalies and stock return seasonality: Further empirical evidence. Journal of Financial Economics, 12(1), 13-32.
  • Keynes, M. J. (1936). General Theory Of Employment , Interest And Money. Norwalk, Connecticut: The Easton Press, 1-263. Retrieved December 16, 2016 from http://cas2.umkc.edu/economics/people/facultypages/kregel/courses/econ645/winter2 011/generaltheory.pdf
  • Khan, H., Hassairi, S. A., & Viviani, J.-L. (2011). Herd Behaviour and Market Stress: The Case of Four European Countries. International Business Research, 4(3), 53-67.

39)    Kim, K. A., and Nofsinger, J. R, (2008). »Behavioral finance in Asia«. Pacific-Basin Finance Journal, l6(4), 1-7.

  • LeRoy, S. F., & Porter, R. D. (1981). The Present-Value Relation: Tests Based on Implied Variance Bounds. Econometrica, 49(3), 555-574.
  • Mauck, N., & Salzsieder, L. (2015). Diversification Bias and the Law of One Price: An Experiment on Index Mutual Funds. Journal of Behavioural Finance, 18(1), 45-53.
  • Jegadeesh, W. Kim, Do analysts herd? An analysis of recommendations and market reactions, Rev. Financ. Stud. 23 (2010) 901–937. R. Olsen, Implications of herding behavior for earnings estimation, risk assessment, and stock returns, Financ. Anal. J. 2 (1996) 37–41.
  • Namatalla, A. A., & Gokoluk, S. (2016). Top 2017 Emerging EMEA Picks Are All Things Russia; Avoid Turkey. Retrieved January 15, 2017 from Bloomberg Markets: https://www.bloomberg.com/news/articles/2016-12-27/top-2017-emerging-emeapicks-are-all-things-russia-avoid-turkey
  • Nietzsche , F. W. (1886). Beyond good and evil. First World Library - Literary Society, 107-184. Retrieved December 17, 2016, from https://books.google.lv/books/about/Beyond_Good_and_Evil.html?id=Dg6SArOSCm QC&printsec=frontcover&source=kp_read_button&redir_esc=y#v=onepage&q&f=fa lseNorth American Journal of Economics and Finance, 29, 418-440. North American Journal of Economics and Finance, 29, 418-440.
  • Özsu, H. H. (2015). Empirical Analysis of Herding Behaviour in Borsa Istanbul. International Journal of Economic Sciences, 4(4), 27-52.
  • Poshakwale, S., & Mandal, A. (2014). Investor Behaviour and Herding: Evidence from the National Stock Exchange in India. Journal of Emerging Market Finance, 13(2), 197216.
  • Rozeff, M. S., & Kinney, W. R. (1976). Capital market seasonality: The case of stock returns. Journal of Financial Economics, 3(4), 379-402.
  • Rozeff, M. S., & Kinney, W. R. (1976). Capital market seasonality: The case of stock returns. Journal of Financial Economics, 3(4), 379-402.
  • Sharpe, W. F. (1964). A theory of Market Equilibrium under Conditions of Risk. The Journal of Finance, 19(3), 425-442.
  • Shiller, R. J. (2003). From Effecient Markets theory to Behavioural Finance. Journal of Economic Perspectives, 17(1), 83-104.
  • Shleifer, A., & Summers, L. H. (1990). The Noise Trader Approach to Finance. Journal of Economic Perspectives, 4(2), 19-33.
  • Shyu, J., & Sun, H.-M. (2010). Do Institutional Investors Herd in Emerging Markets? Evidence from the Taiwan Stock Market. Asian Journal of Finance & Accounting, 2(2).
  • Styliani-Iris Krokida& Panagiota Makrychoriti& Spyros Spyrou(2020) Monetary policy and herd behavior: International evidence Journal of Economic Behavior & Organization
  • Tan, L., Chiang, T. C., Mason, J. R., & Nelling, E. (2008). Herding behaviour in Chinese stock markets: An examination of A and B shares. Pacific-Basin Finance Journal, 16(1-2), 61-77.
  • Thirikwa, G. M. (2015). Determinants of Herding in the Nairobi Securities Exchange.
  • Veblen, Thorstein. (1899) Theory of the Leisure Class: An Economic Study in the Evolution of Institutions. New York: Macmillan-Volume 170, February 2020, Pages 386-417
  • Wang, Guocheng & Wang, Yanyi, 2018. "Herding, social network and volatility," Economic Modelling, Elsevier, vol. 68(C), pages 74-81.
  • Wang, Y., A. Keswani, and S. Taylor. (2006), “The Relationships Between Sentiment, Rturns and Volatility”, International Journal of Forecasting, 22, pp 109–123.
  • Wanga, Guocheng &Wang, Yanyi. (2019). Herding, Social Network and Volatility.Economic Modelling, 68: 74-81.
  • Warner, G. M., & Dyer, M. G. (1994). Evolution of herding behavior in artificial animals. Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior, 393-399.
  • Yang, W.-R., & Chen, Y.-L. (2015). The Response of Dynamic Herd Behaviour to Domestic and U.S. Market Factors: Evidence from the Greater China Stock Markets. Emerging Markets Finance & Trade, 51, 18-41.
  • Zheng, D., Lia, H., & Zhu, X. (2015). Herding behaviour in institutional investors: Evidence from China’s stock market. Journal of Multinational Financial Management,33-33, 59-76.
  • Zhou, R. T., & Lai, R. N. (2009). Herding and information based trading. Journal of Empirical Finance, 16(3), 388-393.

 

Files

Share

How to cite

Statistics