MODELING INVESTOR BEHAVIOR: INTEGRATING RISK AND RETURN IN A SYSTEM DYNAMICS FRAMEWORK

Jones Parlindungan Nadapdap; Rissa Ayustia; Perminas Pangeran; Eligia Monixa Salfarini; Firdaus Nur

Authors

Jones Parlindungan Nadapdap Institut of Shanti Bhuana
Rissa Ayustia Institut of Shanti Bhuana
Perminas Pangeran Duta Wacana Christian University
Eligia Monixa Salfarini Institut of Shanti Bhuana
Firdaus Nur University of Dharmas Indonesia

Keywords:

Investor behavior, Causal Loop Diagrams (CLDs), risk and return, market sentiment, risk perception

Abstract

This research explores the dynamics of investor behavior within the framework of risk and return by proposing Causal Loop Diagrams (CLDs) as a modeling tool. The study delves into the intricate relationships between market sentiment, risk perception, stock prices, and investment decisions. The reinforcing and balancing loops identified in the CLDs highlight the complex interplay of factors that shape investor behavior and market dynamics. The reinforcing loop between positive market sentiment and buying decisions illustrates the strong influence of sentiment on investor actions, potentially leading to prolonged bullish trends. Conversely, the reinforcing loop linking high risk perception to selling decisions depicts a negative cycle, with declining stock prices reinforcing risk perception, triggering further divestment. These loops showcase how market participants respond to changing conditions, stabilizing the market during downturns. Implications of the CLDs include the ability to identify market trends, potential risks, and the influence of investor decisions on market dynamics. Recommendations for market participants, analysts, and policymakers emphasize the importance of understanding market sentiment, implementing prudent risk management, and adapting strategies to changing market conditions. In conclusion, the proposed CLDs offer a valuable tool for comprehending the complexities of investor behavior, contributing to improved investment strategies, enhanced risk management practices, and a deeper understanding of financial market dynamics. This research contributes significantly to advancing our understanding of the intricate factors that shape investor decisions and influence the direction of financial markets.

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References

E. F. Fama, “Efficient Capital Markets: A Review of Theory and Empirical Work,” J. Finance, vol. 25, no. 2, pp. 383–417, 1970, [Online]. Available: http://www.jstor.org/stable/2325486.

H. Markowitz, “Portfolio Selecion,” J. Finance, vol. 7, no. 1, pp. 77–91, 1952, [Online]. Available: http://www.jstor.org/stable/2975974.

D. Kahneman and A. Tversky, “Prospect Theory: An Analysis of Decision under Risk,” Econom. Soc., vol. 47, no. Mar, pp. 263–292, 1979, [Online]. Available: http://www.jstor.org/stable/1914185 .

D. H. Meadows, Thinking in Systems. Earthscan, 2009.

J. W. Forrester, Principle of Systems. Cambridge, MA: MIT Press, 1968.

J. W. Forrester, Jay W. Forrester - World Dynamics -Pegasus Communications (1971).pdf. 1971.

E. F. Fama, “The Behavior of Stock-Market Prices,” J. Bus., vol. 38, no. 1, pp. 34–105, 1965, [Online]. Available: http://www.jstor.org/stable/2350752.

Robert J. Shiller, Exuberance Irrational. Princeton University Press, 2000.

N. Barberis and R. Thaler, “Working Paper Series a Survey of Behavioral Finance,” 2002. [Online]. Available: http://www.nber.org/papers/w9222.

S. Steiger and M. Pelster, “Social interactions and asset pricing bubbles,” J. Econ. Behav. Organ., vol. 179, pp. 503–522, 2020, doi: 10.1016/j.jebo.2020.09.020.

B. M. Barber and T. Odean, “Boys will be boys: Gender, overconfidence, and common stock investment,” Q. J. Econ., vol. 116, no. 1, pp. 261–292, 2001, doi: 10.1162/003355301556400.

K. Daniel and D. Hirshleifer, “Overconfident investors, predictable returns, and excessive trading,” J. Econ. Perspect., vol. 29, no. 4, pp. 61–88, 2015, doi: 10.1257/jep.29.4.61.

E. F. Fama, “Market efficiency, long-term returns, and behavioral finance,” J. financ. econ., vol. 49, no. 3, pp. 283–306, 1998, doi: 10.1016/s0304-405x(98)00026-9.

B. K. Bala, F. M. Arshad, and K. M. Noh, System Dynamics Modelling and Simulation, no. 67. Springer, 2017.

M. A. W. Sinaga, N. F. Nuzula, and C. R. Damayanti, “The Psychology of Risk Influence and Investor Sentiment on Investment Decision Making in the Indonesian Stock Market,” J. Ilm. Akunt. dan Bisnis, vol. 18, no. 2, pp. 197–215, 2023, doi: 10.24843/JIAB.2023.v18.i02.p01.

P. Koratamaddi, K. Wadhwani, M. Gupta, and S. G. Sanjeevi, “Market sentiment-aware deep reinforcement learning approach for stock portfolio allocation,” Eng. Sci. Technol. an Int. J., vol. 24, no. 4, pp. 848–859, 2021, doi: 10.1016/j.jestch.2021.01.007.

N. Barberis and R. Thaler, “Chapter 18 A survey of behavioral finance,” Handb. Econ. Financ., vol. 1, no. SUPPL. PART B, pp. 1053–1128, 2003, doi: 10.1016/S1574-0102(03)01027-6.

B. G. Malkiel, “The Efficient Market Hypothesis and Its Critics,” J. Econ. Perspect., vol. 17, no. 1, pp. 59–82, 2003, doi: 10.1257/089533003321164958.

C. Mbanga, A. F. Darrat, and J. C. Park, “Investor sentiment and aggregate stock returns: the role of investor attention,” Rev. Quant. Financ. Account., vol. 53, no. 2, pp. 397–428, 2019, doi: 10.1007/s11156-018-0753-2.