International Journal of Nonlinear Analysis and Applications
Risk psychology and decision-making behavior of traders (Prospect Theory test)
Document Type : Research Paper
Authors
Department of Accounting, Bonab Branch, Islamic Azad University, Bonab, Iran
Abstract
Prospect Theory basically describes how people evaluate profits and losses. This theory indicates that a person makes a certain choice, but does not expect a definite result. The present study predicts the causal relationships between the constructs of prospect theory including risk attitude, subjective accounting and overconfidence, and decision-making behaviour of traders resulting from mass behaviour, cognitive, and emotional bias. The statistical population is active traders in the capital market within the country and a standard questionnaire was used to collect data. The relevant analyzes were performed based on the Lineal Structural Relations approach after performing the reliability and validity tests of the sample data. The test results of the hypotheses showed that the structures of prospect theory have a significant effect on the decision-making behaviour of traders.
Keywords
[1] J. Aduda, The behaviour and financial performance of individual investors in the trading shares of companies listed at the Nairobi stock exchange, Kenya J. Financ. Invest. Anal. 1 (2012), no. 3, 33–60.
[2] A. Anderson, J. Henker and S. Owen, Limit order trading behavior and individual investor performance, J. Behav. Financ. 6 (2005), no. 2, 71–89.
[3] A. Atefifar and A. Soleimani Bashli, Financial behavior, Aylar Publications, 2019.
[4] B. Aziz and M. Abdolah Khan, Behavioral factors influencing individual investor’s investment decision and performance, evidence from Pakistan stock exchange, Int. J. Res. Financ. Market. 6 (2016), 74–86.
[5] A. Bandopadhyaya and A.L. Jones, Measuring investor sentiment in equity markets, J. Asset Manag. 7 (2006), no. 3, 208–215.
[6] A. Ben Sa¨ıda, Herding effect on idiosyncratic volatility in US industries, Financ. Res. Lett. 23 (2017), 121–132.
[7] S. Bikhchandani and S. Sharma, Herd behavior in financial markets: a review, Working paper, IMF Institute, 2000.
[8] P. Centobelli, R. Cerchione and M. Ertz, Managing supply chain resilience to pursue business and environmental strategies, Bus. Strategy Envir. 29 (2020), no. 3, 1215–1246.
[9] E.C. Chang, J.W. Cheng and A. Khorana, An examination of herd behavior in equity markets: an international perspective, J. Bank. Finance 24 (2000), no. 10, 1651–1679.
[10] A. Charles and R. Kasilingam, Impact of selected behavioural bias factors on investment decisions of equity investors, Ictact J. Manag. Stud. 2 (2016), no. 2, 297–311.
[11] Y. Chen, Z. Wang and Z. Zhang, Mark to market value at risk, J. Economet. 208 (2019), no. 1, 299–321.
[12] T.C. Chiang and D. Zheng, An empirical investigation of herd behavior: evidence from international perspective, Working Paper, Drexel University, 2008.
[13] O. Dadar and S.M. Jafari, The effect of investors sentiment and free float on stock return in TSE listed companies by using generalized method of moments (GMM), J. Invest. Knowledge 9 (2016), no. 34, 317–331.
[14] H. Danaei Fard, S.M. Alwani and A. Azar, Qualitative research methodology in management: a comprehensive approach, Saffar Pub, Tehran, 2011.
[15] R. Demirer and A.M. Kutan, Does herding behavior exist in Chinese stock market?, J. Int. Financ. Markets Inst. Money 16 (2006), 123–142.
[16] F. Dezoort and S.E. Salterio, The effects of corporate governance experience and financial-reporting and audit knowledge on audit committee members’ judgments, Audit.: J. Practice Theory 20 (2001), no. 2, 31–47.
[17] A. Ebrahimi Lifshagard, K. Pakizeh Kamran and K. Raisifar, Investigating the effect of investors’ personality traits on investment performance with the mediating role of revelation biases, Financ. Knowledge Secur. Anal. 12 (2019), no. 42, 107–128.
[18] A.S. Farley, The master swing trader toolkit: the market survival guide, McGraw Hill Professional, 2010.
[19] M. Grinblatt and B. Han, Prospect theory, mental accounting, and momentum, J. Financ. Econ. 11 (2005), no. 2, 119–133.
[20] J.F. Hair, W.C. Black, B.J. Babin and R.E. Anderson, Multivariate Data Analysis, Prentice Hall, 2010.
[21] S. Hwang and M. Salmon, Market stress and herding, J. Empir. Finance 11 (2004), no. 4, 585–616.
[22] L. Kengatharan and N. Kengatharan, The influence of behavioral factors in making investment decisions and performance, Asian J. Financ. Account. 6 (2014), no. 1.
[23] G. Khaki, Research method with an approach to dissertation writing, Eighth edition, Tehran, Bazetab Publications, 2011.
[24] K.H. Kim and P.M. Bentler, Data modeling: structural equation modeling, In J.L. Green, G. Camilli and P.B. Elmore (Eds.): Handbook of complementary methods in education research, Routledge, 2012.
[25] A. Lim and J. Sinnakkannu, Empirical analysis on the speed of stock price adjustment to firm specific and market wide announcements, Inti College Malaysia, 2003.
[26] A. Merilkas and D. Prasad, Factor influencing Greek investor behavior on the Athens stock exchange, J. Bus. 66 (2003), no. 1, 1–20.
[27] L.T.B. Ngoc, Behavior pattern of individual investors in stock market, Int. J. Bus. Manag. 9 (2013), no. 1.
[28] A. Panahi and A. Habibi Rad, Explaining the relationship between bitcoin price in business financial transactions and search volume in order to identify its behavioral pattern: a comparative study between countries, Strategic Budget Financ. Res. 10 (2021), no. 37, 141–169.
[29] P.C.B. Phillips, S.P. Shi and J. Yu, Specification sensitivity in right tailed unit root testing for explosive behaviour, Oxford Bull. Econ. Statist. 76 (2014), no. 3, 315–333.
[30] M. Pompian, Behavioral finance and wealth management: how to build optimal portfolios that account for investor biases, John Wiley and Sons, Inc. 2006.
[31] N. Rasool and S. Ullah, Financial literacy and behavioural biases of individual investors: empirical evidence of Pakistan stock exchange, J. Econ. Finance Admin. Sci. 25 (2021), no. 50, 261–278.
[32] A. Rezazadeh and A. Davari, Structural equation modeling with PLS software, Second Edition, Tehran, Jihad Daneshgahi Pub. 2014.
[33] I.G. Sarason and B.R. Sarason, Abnormal psychology: The problem of maladaptive behavior, New Jersey, Prentice Hall, 2005.
[34] R.J. Shiller, Human behavior and efficiency of the financial system, in: J.B. Taylor and M. Woodford (ed.), Handbook of macroeconomics, Elsevier, (1999).
[35] L. Tan, T.C. Chiang, J.R. Mason and E. Nelling, Herding behavior in Chinese stock markets: an examination of A and B shares, Pacific-Basin Finance J. 16 (2008), no. 1–2, 61–77.
[36] A. Tversky and D. Kahneman, Judgment under uncertainty: Heuristics and biases, Science ´u185 (1971), no. 4157, 1124–1131.
[37] A. Tversky and D. Khaneman, Rational choice and the framing of decisions, J. Bus. 59 (1986), no. 4, S251–S278.
[38] E.E. Umphress, J.B. Bingham and M.S. Mitchell, Unethical behavior in the name of the company: The moderating effect of organizational identification and positive reciprocity beliefs on unethical pro-organizational behavior, J. Appl. Psych. 95 (2010), 769–780.
[39] W. Van der Wielen and S. Barrios, Economic sentiment during the COVID pandemic: evidence from search behaviour in the EU, J. Econ. Bus. 115 (2021), 105970.
[40] N.M. Waweru, E. Munyoki and E. Uliana, The effects of behavioral factors in investment decision-making: a survey of institutional investors operating at the Nairobi Stock Exchange, Int. J. Bus. Emerg. Markets 1 (2008), no. 1, 24–41.
[41] Y.-F. Wen, Capital investment decision, corporate governance, and prospect theory, Proc. Soc. Behav. Sci. 5 (2010), 116–126.
[42] P. Xidonas, C. Hassapis, J. Soulis and A. Samitas, Robust minimum variance portfolio optimization modelling under scenario uncertainty, Econ. Model. 64 (2017), 60–68.
[43] W. Xuan, S. Jieqiong, S. Shan and Z. Yan, Urban ecological regulation based on information entropy at the town scale a case study on Tongzhou district, Beijing city, Proc. Environ. Sci. 13 (2012), 1155–1164.
[44] J. Yao, C. Ma and W.P. He, Investor herding behaviour of Chinese stock market, Int. Rev. Econ. Financ. 29 (2014), 12–29.
)
Volume 14, Issue 2
February 2023Pages 207-219
- Receive Date: 14 April 2022
- Revise Date: 16 June 2022
- Accept Date: 22 June 2022