Herding Bias and Investment Performance in Kenya's Dynamic Real Estate Sector.

Allan Muchemi Kuria

doi:10.61108/ijsshr.v2i3.145

Herding Bias and Investment Performance in Kenya's Dynamic Real Estate Sector.

Authors

Dr. Allan Muchemi Kuria Scholar, Dedan Kimathi University of Technology, Private bag, Nyeri, Kenya

DOI:

https://doi.org/10.61108/ijsshr.v2i3.145

Keywords:

Herding Bias, Investment Performance, Behavioral Bias, Herding Theory

Abstract

One fundamental question remain unanswered, are investments free from behavioral biases? This study explores the impact of herding bias on investment performance, with a focus on real estate investors in Kenya. Behavioral finance highlights how psychological factors influence investment decisions, challenging the assumptions of rationality and market efficiency. Herding, characterized by individuals imitating the decisions of others, emerges as a key bias affecting financial markets. It creates inefficiencies by distorting prices and returns, driven by social influences and noise trading. This research employed both descriptive and inferential analyses to assess the relationship between herding behavior and investment outcomes. Respondents were evaluated on their reliance on personal judgment, external opinions, and group influence when making investment decisions. Findings indicate a statistically significant effect of herding bias on investment performance, with 26.1% of performance variation attributable to herding. Regression analysis demonstrated a moderate correlation (R = 0.511) between herding and performance, underscoring the influence of behavioral biases. The study aligns with previous findings that herding can diminish return dispersion and, under extreme conditions, lead to negative dispersion. Notably, investors' reliance on group trends and noise rather than fundamental data often results in suboptimal decisions, adversely affecting financial outcomes. The results emphasize the need for strategies to mitigate the negative impacts of behavioral biases. Investors should evaluate investments based on portfolio performance rather than isolated returns and risks. Furthermore, the establishment of regulatory frameworks could guide investors toward informed decision-making and market stability. This study contributes to the understanding of behavioral finance in emerging markets, providing insights into the interplay between herding bias and investment performance in Kenya's dynamic real estate sector

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References

. Barberis, N., Huang, M. & Santos, T. (2001). Prospect Theory and Asset Prices. Quarterly Journal of Economics, 116(1), 1-53.

. Barberis, N. & Thaler R. H., (2003). A Survey of Behavioral Finance, A Handbook of the Economics of Finance. Amsterdam: Elsevier Science.

. Barberis, N. & Xiong, W. (2009). What drives the disposition effect? An analysis of a long-standing preference-based explanation. Journal of Finance 64(2): 751–784.

. Barberis, N., Huang, M. & Thaler, R. (2006). Individual Preferences, Monetary Gambles & Stock Market Participation: A Case for Narrow Framing. The American Economic Review, 6: 1069-1090.

. Black, F. (1986). Noise. Journal of Finance. 41(3): 529-543.

. Daniel, K., Hirshleifer, D. & Teoh, S.H. (2002). Investor Psychology in Capital Markets: Evidence and Policy Implications. Journal of Monetary Economics, 49: 139-209.

. De Long, J. B., Shleifer, A., Summers, L. H. & Waldmann, R. J. (1990). Noise Trader Risk in Financial Markets, Journal of Political Economy, 98(4),703-738.

. Fan, J. & Xiao, J. (2003). A Cross-Cultural Study in Risk Tolerance: Comparing Chinese and Americans. Consumer Interest Annual 44(9): 1205-1217.

. Hirshleifer, D. (2001). Investor Psychology and Asset Pricing. Journal of Finance 1(4): 1533-1536.

. Hofstede, G. (2001). Culture's Consequences: Comparing Values, Behaviors, Institutions and Organizations Across Nations (2nd Edition). Thousand Oaks: Sage Publications.

. Hott, C. (2009). Explaining House Price Fluctuations. Working Papers 2009-05, Swiss Nationa l Bank.

. Kahneman, D. & Tversky A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrics, 47: 263-292.

. Kudryavtsev, A. Cohen, G. & Hon-Snir, S. (2013). Rational' or 'Intuitive': Are Behavioral Biases Correlated Across Stock Market Investors? Contemporary Economics, 7(2): 31-53.

. Kumar, A. & Lee, C. M. (2006) Retail investor sentiment and return movements. Journal of Finance, 61: 2451–2486.

. Lawlor Leroy, S. F. & Porter R. D. (1981). The Present Value Relation: Tests Based on Implied Variance Bounds. Econometrical, 49(3): 555-574.

. Li, W., Rhee G. & Wang, S. S., (2009). Differences in Herding: Individual vs. Institutional Investors in China. Asian Finance Association (Asiana) 2015 Conference Paper. Retrieved on 27th June, 2013 from http://dx.doi.org/10.2139/ssrn.1342209.

. Lu, L., (2010). Asset Pricing and Welfare Analysis with Bounded Rational Investors. The Financial Review Journal 45(2): 485-499.

. Nyamute, W., Lishenga, J. & Oloko, M. (2015). The Effect of Investment Style on Portfolio Performance: Evidence from the Nairobi Securities Exchange. International Journal of Multidisciplinary Research and Development 2(5): 552-554.

. Prosad, J. (2014). Impact of Investors’ Behavioral Biases on the Indian Equity Market and Implications on Stock Selection Decisions: An Empirical Analysis. PhD Synopsis, Jaypee Institute of Information Technology.

. Shiller, R. (2000). Irrational Exuberance. New Jersey: Princeton University Press.

. Shleifer, A. (2000). Inefficient Markets: An Introduction to Behavioral Finance. Oxford: Oxford University Press.

. Singh, A. (2012). Changing Contours of Global Crisis – Impact on Indian Economy. Retrieved on 12th April, 2012 from http://rbi.org.in/scripts/BS_SpeechesView.aspx?Id=678.

. Statman, M. (2010). The Cultures of Risk Tolerance. SSRN Paper No: 1647086.

. Subrahmanyam, A. (2008). Behavioral Finance: A Review and Synthesis. European Financial Management 14(1): 12-29.

. Vissing-Jorgensen, A. (2004). Perspectives on Behavioral Finance: Does "Irrationality" Disappear with Wealth? Evidence from Expectations and Actions. Perspectives of behavioral finance 1(1): 141-146.

. Welch, I., (2000). Herding among Security Analysts. Journal of Financial Economics, 38(3): 369-396.

Vol. 2 No. 3 (2024) of the International Journal of Social Science and Humanities Research (IJSSHR)

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Published

2024-12-15

How to Cite

Kuria, A. M. (2024). Herding Bias and Investment Performance in Kenya’s Dynamic Real Estate Sector. International Journal of Social Science and Humanities Research (IJSSHR) ISSN 2959-7056 (o); 2959-7048 (p), 2(3), 332–338. https://doi.org/10.61108/ijsshr.v2i3.145

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Vol. 2 No. 3 (2024): International Journal of Social Science and Humanities Research (IJSSHR) ISSN 2959-7056 (o); 2959-7048 (p)

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