A Multifactorial Analysis of Herding Behavior in the Stock Market: A Theory-Driven Survey in the Tehran Stock Exchange | ||
| International Journal of New Political Economy | ||
| مقاله 9، دوره 6، شماره 2، 2025، صفحه 203-240 اصل مقاله (986.68 K) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.48308/jep.2025.240334.1227 | ||
| نویسندگان | ||
| Mohamad Ahadzadeh* 1؛ Vahid Shabani Heydarabadi2؛ Ali Eshaghzadeh3؛ Ruhollah Moradi4 | ||
| 1islamic azad university science and research branch | ||
| 2Master's Degree in Business Administration, field of study: international commercial law, Shahid Beheshti University, Tehran, Iran. | ||
| 3Ph.D. of Finance, Faculty of Management, imam Sadiq University, Tehran, Iran. | ||
| 4Associate Professor, Department of Management and economics, Science and Research Branch, Islamic Azad University, Tehran, Iran. | ||
| چکیده | ||
| Herding behavior in the stock market disrupts market efficiency as investors imitate others instead of relying on independent analysis. This study examines the impact of Trust in Economic News (TEN), Social Media Influence (SMI), Market Volatility (MV), Behavioral Triggers (BT), and External Economic Factors (EEF) on herding behavior, particularly among Millennials and Gen-Z investors. A survey of 350 retail and institutional investors was conducted in 2025, and data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with Smart PLS 3.2.9. The results show that MV is the strongest driver of herding behavior (β = 0.470, p = 0.000), while SMI (β = 0.368, p = 0.000) and TEN (β = 0.287, p = 0.000) amplify the influence of economic news and social media. Additionally, BT (β = 0.393, p = 0.000) and EEF (β = 0.236, p = 0.000) significantly contribute to herding through emotional and systemic mechanisms. The novelty of this study lies in its comprehensive analysis of the combined influence of cognitive, social, and macroeconomic factors on herding behavior in the stock market, offering both theoretical and practical insights for understanding investor behavior. This research highlights the crucial role of psychological, social, and economic factors in shaping herding behavior. | ||
| کلیدواژهها | ||
| Herding Behavior؛ Trust in Economic News؛ Social Media Influence؛ Market Volatility؛ Behavioral Triggers and External Economic Factors | ||
| مراجع | ||
|
Ab Hamid, M. R., Sami, W., & Sidek, M. M. (2017). Discriminant validity assessment: Use of Fornell & Larcker criterion versus HTMT criterion. In Journal of physics: Conference series (Vol. 890, No. 1, p. 012163). IOP Publishing. doi: 10.1088/1742-6596/890/1/012163. Akerlof, G. A., & Shiller, R. J. (2010). Animal spirits: How human psychology drives the economy, and why it matters for global capitalism. Princeton university press. doi: https://doi.org/10.2307/j.ctv36mk90z.
Allcott, H., & Gentzkow, M. (2017). Social media and fake news in the 2016 election. Journal of economic perspectives, 31(2), 211-236. doi: 10.1257/jep.31.2.211.
Antweiler, W., & Frank, M. Z. (2004). Is all that talk just noise? The information content of internet stock message boards. The Journal of finance, 59(3), 1259-1294. doi: https://doi.org/10.1111/j.1540-6261.2004.00662.x.
Baker, M., & Wurgler, J. (2006). Investor sentiment and the cross‐section of stock returns. The journal of Finance, 61(4), 1645-1680. doi: https://doi.org/10.1111/j.1540-6261.2006.00885.x.
Baker, H. K., & Nofsinger, J. R. (Eds.). (2010). Behavioral finance: investors, corporations, and markets (Vol. 6). John Wiley & Sons. doi:10.1002/9781118258415.
Barberis, N., Shleifer, A., & Vishny, R. (1998). A model of investor sentiment. Journal of financial economics, 49(3), 307-343. doi: https://doi.org/10.1016/S0304-405X(98)00027-0.
Banerjee, A. V. (1992). A simple model of herd behavior. The quarterly journal of economics, 107(3), 797-817. doi: https://doi.org/10.2307/2118364. Barberis, N., Thaler, R. (2003). A Survey of Behavioral Finance. Handbook of the Economics of Finance, 1. doi: https://doi.org/10.1016/S1574-0102(03)01027-6. Bernile, G., Bonaparte, Y., & Delikouras, S. (2025). Stock market experience and investor overconfidence: Do investors learn to be overconfident?. Journal of Banking & Finance, 174, 107431. doi: https://doi.org/10.1016/j.jbankfin.2025.107431.
Bikhchandani, S., Hirshleifer, D., & Welch, I. (1992). A theory of fads, fashion, custom, and cultural change as informational cascades. Journal of political Economy, 100(5), 992-1026. doi: https://doi.org/10.1086/261849.
Bloom, N., Bond, S., & Van Reenen, J. (2007). Uncertainty and investment dynamics. The review of economic studies, 74(2), 391-415. doi: https://doi.org/10.1111/j.1467-937X.2007.00426.x.
Black, F. (1976). Studies of stock market volatility changes. Proceedings of the American Statistical Association, Business & Economic Statistics Section, 1976.
Blasco, N., Corredor, P., & Ferreruela, S. (2012). Does herding affect volatility? Implications for the Spanish stock market. Quantitative Finance, 12(2), 311-327. doi: https://doi.org/10.1080/14697688.2010.516766.
Bollen, J., Mao, H., & Zeng, X. (2011). Twitter mood predicts the stock market. Journal of computational science, 2(1), 1-8. doi: https://doi.org/10.1016/j.jocs.2010.12.007. Camerer, C. F. (2011). Behavioral game theory: Experiments in strategic interaction. Princeton university press.
Chen, H., De, P., Hu, Y., & Hwang, B. H. (2014). Wisdom of crowds: The value of stock opinions transmitted through social media. The review of financial studies, 27(5), 1367-1403. doi: https://doi.org/10.1093/rfs/hhu001.
Chiou, W. J. P., Knewtson, H. S., & Nofsinger, J. R. (2019). Paying attention to social media stocks. International Review of Economics & Finance, 59, 106-119. doi: https://doi.org/10.1016/j.iref.2018.08.009.
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. doi: https://doi.org/10.2469/faj.v51.n4.1918.
Cialdini, R. B. (2007). Influence: The psychology of persuasion (Vol. 55, p. 339). New York: Collins.
Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. Journal of business, 383-403. doi: 10.1086/296344. 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. Doi: https://doi.org/10.2469/faj.v51.n4.1918.
Chin, W. W. (1998). The partial least squares approach to structural equation modeling. Modern methods for business research/Lawrence Erlbaum Associates.
Chen, H., De, P., Hu, Y., & Hwang, B. H. (2014). Wisdom of crowds: The value of stock opinions transmitted through social media. The review of financial studies, 27(5), 1367-1403. Doi: https://doi.org/10.1093/rfs/hhu001.
Cronbach, L. J. (1951). Coefficient alpha and the internal structure of tests. Psychometrika, 16(3), 297-334. doi: https://doi.org/10.1007/BF02310555. Daniel, K., Hirshleifer, D., & Subrahmanyam, A. (1998). Investor psychology and security market under‐and overreactions. The Journal of Finance, 53(6), 1839-1885. Doi: https://doi.org/10.1111/0022-1082.00077.
Di Guilmi, C., He, X. Z., & Li, K. (2014). Herding, trend chasing and market volatility. Journal of Economic Dynamics and Control, 48, 349-373. Doi: https://doi.org/10.1016/j.jedc.2014.07.008.
Fama, E. F. (1981). Stock Returns, Real Activity, Inflation, and Money. The American Economic Review, 71(4), 545–565. doi: http://www.jstor.org/stable/1806180. Froot, K. A., Scharfstein, D. S., & Stein, J. C. (1992). Herd on the street: Informational inefficiencies in a market with short‐term speculation. The Journal of finance, 47(4), 1461-1484. Doi: https://doi.org/10.2307/2328947.
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of marketing research, 18(1), 39-50. Doi: https://doi.org/10.2307/3151312.
Fei, T., & Liu, X. (2021). Herding and market volatility. International Review of Financial Analysis, 78, 101880. doi: https://doi.org/10.1016/j.irfa.2021.101880. Han, X., & Li, Y. (2017). Can investor sentiment be a momentum time-series predictor? Evidence from China. Journal of Empirical Finance, 42, 212-239. Doi: https://doi.org/10.1016/j.jempfin.2017.04.001.
Kacperczyk, M., & Schnabl, P. (2010). When safe proved risky: commercial paper during the financial crisis of 2007–2009. Journal of economic perspectives, 24(1), 29-50. Doi: 10.1257/jep.24.1.29.
Karimi, M., & Ahadzadeh, M. (2024). Macro Herding Behavior and Its Implications in Tehran Stock Exchange: An Analysis of Extreme Market Conditions. Iranian Journal of Finance, 8(3), 98-117. Doi: 10.30699/ijf.2024.462197.1475.
Li, T., Chen, H., Liu, W., Yu, G., & Yu, Y. (2023). Understanding the role of social media sentiment in identifying irrational herding behavior in the stock market. International Review of Economics & Finance, 87, 163-179. doi: https://doi.org/10.1016/j.iref.2023.04.016. Nofsinger, J. R. (2017). The psychology of investing. Routledge. Doi: https://doi.org/10.4324/9781315230856.
Shleifer, A., & Summers, L. H. (1990). The noise trader approach to finance. Journal of Economic perspectives, 4(2), 19-33. doi: 10.1257/jep.4.2.19. Schwert, G. W. (1989). Why does stock market volatility change over time?. The journal of finance, 44(5), 1115-1153. doi: https://doi.org/10.1111/j.1540-6261.1989.tb02647.x. Signorelli, P. F. C. L., Camilo-da-Silva, E., & Barbedo, C. H. D. S. (2021). An Examination of Herding Behavior in the Brazilian Equity Market. BBR. Brazilian Business Review, 18(3), 236-254. Doi: http://dx.doi.org/10.15728/bbr.2021.18.3.1.
Sarstedt, M., Ringle, C. M., & Hair, J. F. (2021). Partial least squares structural equation modeling. In Handbook of market research (pp. 587-632). Cham: Springer International Publishing. Doi: https://doi.org/10.1007/978-3-319-57413-4_15.
Tetlock, P. C. (2011). All the news that's fit to reprint: Do investors react to stale information?. The Review of Financial Studies, 24(5), 1481-1512. Doi: https://doi.org/10.1093/rfs/hhq141.
Tetlock, P. C. (2015). The role of media in finance. Handbook of media Economics, 1, 701-721. Doi: https://doi.org/10.1016/B978-0-444-63685-0.00018-8.
Thaler, R. (1980). Toward a positive theory of consumer choice. Journal of economic behavior & organization, 1(1), 39-60. doi: https://doi.org/10.1016/0167-2681(80)90051-7. Van Dolder, D., & Vandenbroucke, J. (2024). Behavioral risk profiling: Measuring loss aversion of individual investors. Journal of banking & finance, 168, 107293. doi: https://doi.org/10.1016/j.jbankfin.2024.107293.
Welch, I. (2000). Herding among security analysts. Journal of Financial economics, 58(3), 369-396. doi: https://doi.org/10.1016/S0304-405X(00)00076-3. You, T. (2025). Confirmation bias and herding behavior across the housing markets. Humanities and Social Sciences Communications, 12(1), 1-14. doi: https://doi.org/10.1057/s41599-025-05021-5. | ||
|
آمار تعداد مشاهده مقاله: 3,052 تعداد دریافت فایل اصل مقاله: 3,373 |
||