Main Article Content

Abstract

This research aims to investigate the influence of behavioral finance on stock investment decision-making in Indonesia, considering both rational and irrational behaviors. Key behavioral finance factors, including overconfidence, herding bias, mental accounting, and loss aversion, are examined to understand their impact on stock investment decisions, the financial literacy as moderating variables has been added to the model. A self-administered questionnaires were distributed to 391 active trading stock investor in Indonesia. Using Partial Least Squares method, the results shows that loss aversion and overconfidence negatively influence the investment decision. Further, the analysis confirmed the role of financial literacy as moderating variable for mental accounting and overconfidence. It is also consistent with the notion that financial literacy at least in terms of mental accounting biases under some conditions might actually reinforce certain specific cognitive shortcuts. This study’s results suggest policymakers and financial educators should work to increase investors’ literacy about finance, as well as their ability to identify biases they hold which could be used against them when making investment decisions.

Keywords

Herding bias Investment decision Loss aversion Mental accounting Overconfidence

Article Details

How to Cite
Budiman, J., Yodiputra, J., Candy, C., & Agustin, I. N. (2025). How overconfidence and mental accounting influence investments? The moderating role of financial literacy. Asian Management and Business Review, 5(1), 1–18. https://doi.org/10.20885/AMBR.vol5.iss1.art1

References

  1. Adil, M., Singh, Y., & Ansari, M. S. (2022). How financial literacy moderate the association between behavior biases and investment decision? Asian Journal of Accounting Research, 7(1), 17–30. https://doi.org/10.1108/AJAR-09-2020-0086
  2. Ahmad, M., & Shah, S. Z. A. (2022). Overconfidence heuristic-driven bias in investment decision-making and performance: mediating effects of risk perception and moderating effects of financial literacy. Journal of Economic and Administrative Sciences, 38(1), 60–90. https://doi.org/10.1108/JEAS-07-2020-0116
  3. Ahmed, R., Riaz, S., Aqdas, R., Ibn, S., & Hassan, U. L. (2021). The relationship among overconfidence, economic expectation, social factors and investment decision making behavior with the mediating and moderating effects. Journal of Contemporary Issues in Business and Government, 27(02), 1075-1088. https://doi.org/10.47750/cibg.2021.27.02.127
  4. Aigbovo, O., & Ilaboya, O. J. (2019). Does behavioral biases influences individual investment decisions. Management Science Review, 10(1), 68–89.
  5. Ajzen, I. (2020). The theory of planned behavior: frequently asked questions. Human Behavior and Emerging Technologies, 2(4), 314–324. https://doi.org/10.1002/hbe2.195
  6. Almeida, R., & Gonçalves, F. (2023). The impact of cognitive biases on stock market investments. Financial Research Letters, 47. https://doi.org/https://doi.org/10.1016/j.finre.2023.01.001
  7. Al-Tamimi, H., Hassan, A., & Obeidat, S. M. (2020). Factors influencing individual investor behavior: evidence from the UAE. International Journal of Islamic and Middle Eastern Finance and Management, 13(2), 299–318. https://doi.org/https://doi.org/10.1108/IMEFM-03-2020-0149
  8. Anagol, S., Balasubramaniam, V., & Ramadorai, T. (2021). Learning from noise: evidence from India’s IPO lotteries. Journal of Financial Economics, 140(3), 965–986. https://doi.org/10.1016/j.jfineco.2021.02.003
  9. Ani, N. C., & Özarı, Ç. (2020). Behavioral finance: investors psychology. IOSR Journal of Economics and Finance, 11(1), 46–50. https://doi.org/10.9790/5933-1101024650
  10. Arran, R. (2023). Behavioral finance: the psychology behind financial decision-making. Business Studies Journal, 15(5), 1–2.
  11. Banerjee, A. V. (2020). A simple model of herd behavior. The Quarterly Journal of Economics, 107(3), 797–817. https://doi.org/10.2307/2118364
  12. Barber, B. M., & Odean, T. (2019). Trading is hazardous to your wealth: the common stock investment performance of individual investors. The Journal of Finance, 55(2), 773–806. https://doi.org/10.1111/0022-1082.00226
  13. Barberis, N. (2019). Behavioral finance: an overview. Annual Review of Financial Economics, 11, 1–35. https://doi.org/https://doi.org/10.1016/j.jfineco.2019.03.006
  14. Barberis, N., Shleifer, A., & Vishny, R. (2019). A model of investor sentiment. Journal of Financial Economics, 49(3), 307–343. https://doi.org/https://doi.org/10.1016/S0304-405X(98)00027-
  15. Bouteska, A., & Regaieg, B. (2020). Loss aversion, overconfidence of investors and their impact on market performance: evidence from the US stock markets. Journal of Economics, Finance and Administrative Science, 25(50), 451–478. https://doi.org/10.1108/JEFAS-07-2017-0081
  16. Candy, C., & Novita, I. (2021). Herding behavior of indonesia investor: role of personality traits and motivation factors. International Journal of Economics, Business and Accounting Research (IJEBAR), 5(2), 296–303.
  17. Candy, C., & Vira, V. (2024). Financial behavior as key factors affecting Indonesian gen-Z entrepreneurial intention. International Journal of Applied Business Research, 6(02), 152-172. https://doi.org/10.35313/ijabr.v6i02.363
  18. Cao, C., Leggio, K., & Schniederjans, M. (2005). A comparison between Fama and French’s model and artificial neural networks in predicting the Chinese stock market. Computers & Operations Research, 58, 233–240. https://doi.org/https://doi.org/10.1016/j.cor.2021.02.013
  19. De Bondt, W. F., & Thaler, R. (1985). Does the stock market overreact?. The Journal of finance, 40(3), 793-805. https://doi.org/10.1111/j.1540-6261.1985.tb05004.x
  20. Etikan, I., Musa, S. A., & Alkassim, R. S. (2016). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1-4. https://doi.org/10.11648/j.ajtas.20160501.11
  21. Geloso, V., & Kufenko, V. (2019). Can markets foster rebellion? the case of the 1837–38 rebellions in Lower Canada. Journal of Economic Behavior & Organization, 166, 263–287. https://doi.org/10.1016/j.jebo.2019.06.005
  22. Gilenko, E., & Chernova, A. (2021). Saving behavior and financial literacy of Russian high school students: an application of a copula-based bivariate probit-regression approach. Children and Youth Services Review, 127. https://doi.org/10.1016/j.childyouth.2021.106122
  23. Hair, J. F., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2021). Partial Least Squares Structural Equation Modeling (PLS-SEM) Using R. Switzerland: Springer International Publishing. https://doi.org/10.1007/978-3-030-80519-7
  24. Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2020). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. https://doi.org/10.1108/EBR-11-2018-0203
  25. Hastings, J. S., Madrian, B. C., & Skimmyhorn, W. L. (2013). Financial literacy, financial education, and economic outcomes. Annual Review of Economics, 5(1), 347–373. https://doi.org/10.1146/annurev-economics-082312-125807
  26. Hinzen, F. J., John, K., & Saleh, F. (2022). Bitcoin’s limited adoption problem. Journal of Financial Economics, 144(2), 347–369. https://doi.org/10.1016/j.jfineco.2022.01.003
  27. Hirshleifer, D., & Hong Teoh, S. (2003). Herd behaviour and cascading in capital markets: a review and synthesis. European Financial Management, 9(1), 25–66. https://doi.org/10.1111/1468-036X.00207
  28. Indonesia Central Securities Depository (2023, October). Siaran Pers: Antusiasme Investor Muda Berinvestasi Terus Meningkat. Retrieved from https://www.ksei.co.id/files/uploads/press_releases/press_file/id-id/232_berita_pers_antusiasme_investor_muda_berinvestasi_terus_meningkat_20231031134735.pdf
  29. Islam Khan, M. T., Tan, S. H., & Chong, L. L. (2016). The effects of stated preferences for firm characteristics, optimism and overconfidence on trading activities. International Journal of Bank Marketing, 34(7), 1114-1130. https://doi.org/10.1108/IJBM-10-2015-0154
  30. Joshi, A., Kale, S., Chandel, S., & Pal, D. (2015). Likert scale: explored and explained. British Journal of Applied Science & Technology, 7(4), 396–403. https://doi.org/10.9734/BJAST/2015/14975
  31. Kahneman, D. (2011). Thinking, Fast, and Slow. New York: Farrar, Straus and Giroux.
  32. Kahneman, D., & Tversky, A. (2013). Prospect theory: an analysis of decision under risk. In MacLean, L. C., Ziemba, W. T. (Eds.), Handbook of the Fundamentals of Financial Decision Making: Part I (pp. 99-127). Singapore: World Scientific Publishing Company. https://doi.org/10.1142/9789814417358_0006
  33. Kartini, K., & Nahda, K. (2021). Behavioral biases on investment decision: a case study in Indonesia. Journal of Asian Finance, Economics and Business, 8(3), 1231–1240. https://doi.org/10.13106/jafeb.2021.vol8.no3.1231
  34. Khan, D. (2020). Cognitive driven biases, investment decision making: the moderating role of financial literacy. SSRN Electronic Journal, 1–25. https://dx.doi.org/10.2139/ssrn.3514086
  35. Khan, M. U. (2017). Impact of availability bias and loss aversion bias on investment decision making, moderating role of risk perception. Management & Administration (IMPACT: JMDGMA), 1(1), 17-28.
  36. Klapper, L., Lusardi, A., & Van Oudheusden, P. (2015). Financial literacy around the world: insights from the standard & poor’s ratings services global financial literacy survey. World Bank. Washington DC: World Bank, 2, 218-237.
  37. Kumar, S., & Goyal, N. (2015). Behavioral biases in investment decision making: a systematic review. Qualitative Research in Financial Markets, 11(3), 323–345. https://doi.org/https://doi.org/10.1108/QRFM-07-2018-0084
  38. Lusardi, A., & Mitchell, O. S. (2014). The economic importance of financial literacy: theory and evidence. Journal of Economic Literature, 56(1), 5–44. https://doi.org/https://doi.org/10.1257/jel.20161752
  39. Malik, M. S., Hanif, M. I., & Azhar, M. Z. (2019). The impact of overconfidence bias on investment decisions: mediating role of risk tolerance. International Journal of Research and Innovation in Social Science, 3(8), 154-160.
  40. Metawa, N., Hassan, M. K., Metawa, S., & Safa, M. F. (2019). Impact of behavioral factors on investors’ financial decisions: case of the Egyptian stock market. International Journal of Islamic and Middle Eastern Finance and Management, 12(1), 30–55. https://doi.org/10.1108/IMEFM-12-2017-0333
  41. Michailova, J., Mačiulis, A., & Tvaronavičienė, M. (2017). Overconfidence, risk aversion and individual financial decisions in experimental asset markets. Economic Research-Ekonomska Istrazivanja, 30(1), 1119–1131. https://doi.org/10.1080/1331677X.2017.1311234
  42. Mitchell, O. S., & Lusardi, A. (2015). Financial literacy and economic outcomes: evidence and policy implications. The Journal of Retirement, 3(1), 107. https://doi.org/10.3905/jor.2015.3.1.107
  43. Mnif, E., Mensi, W., & Yoon, S. M. (2022). How does financial literacy impact stock market participation? evidence from emerging markets. Research in International Business and Finance, 60. https://doi.org/https://doi.org/10.1016/j.ribaf.2022.101636
  44. Novandalina, A., Ernawati, F. Y., & Adriyanto, A. T. (2022). Risk attitudes, mental accounting and overconfidence in investment placement decision during and post Covid-19. International Journal of Economics, Business and Accounting Research (IJEBAR), 6(1), 498-506. http://dx.doi.org/10.29040/ijebar.v6i1.4453
  45. Odean, T. (1998). Are investors reluctant to realize their losses? The Journal of Finance, 53(5), 1775–1798. https://doi.org/10.1111/0022-1082.00072
  46. Özen, E., & Ersoy, G. (2019). The impact of financial literacy on cognitive biases of individual investors. Contemporary Issues in Behavioral Finance, 101, 77-95.
  47. Podsakoff, P. M., MacKenzie, S. B., & Podsakoff, N. P. (2016). Recommendations for creating better concept definitions in the organizational, behavioral, and social sciences. Organizational Research Methods, 22(4), 754–774. https://doi.org/https://doi.org/10.1177/1094428118764975
  48. Pokharel, P. R. (2020). Behavioral factors and investment decision: a case of Nepal. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3687104
  49. Ringle, C. M., Sarstedt, M., & Straub, D. W. (2012). Editor’s comments: a critical look at the use of PLS-SEM in MIS Quarterly. MIS Quarterly, 36(1), 3–14. https://doi.org/https://doi.org/10.25300/MISQ/2020/16214
  50. Seiler, M. J., Seiler, V. L., & Lane, M. A. (2012). Mental accounting and false reference points in real estate investment decision-making. Journal of Behavioral finance, 13(1), 17-26. https://doi.org/10.1080/15427560.2012.653293
  51. Shefrin, H., & Statman, M. (2000). Behavioral portfolio theory. Journal of Financial and Quantitative Analysis, 35(2), 127-151. https://doi.org/10.2307/2676187
  52. Sivaramakrishnan, S., Srivastava, M., & Rastogi, A. (2017). Attitudinal factors, financial literacy, and stock market participation. International Journal of Bank Marketing, 35(5), 818-841. https://doi.org/10.1108/IJBM-01-2016-0012
  53. Stolper, O. A., & Walter, A. (2017). Financial literacy, financial advice, and financial behavior. Journal of Business Economics, 87(5), 581–643. https://doi.org/10.1007/s11573-017-0853-9
  54. Thaler, R. H. (1999). Mental accounting matters. Journal of Behavioral Decision Making, 12(3), 183-206. https://doi.org/10.1002/(SICI)1099-0771(199909)12:3%3C183::AID-BDM318%3E3.0.CO;2-F
  55. Thaler, R. H. (2015). Misbehaving: The Making of Behavioral Economics. United Kingdom: Penguin Books Limited.
  56. Thomas, A., & Spataro, L. (2018). Financial literacy, human capital and stock market participation in Europe. Journal of Family and Economic Issues, 39(4), 532-550. https://doi.org/10.1007/s10834-018-9576-5
  57. Van Rooij, M. C., Lusardi, A., & Alessie, R. J. (2011a). Financial literacy and retirement planning in the Netherlands. Journal of Economic Psychology, 32(4), 593-608. https://doi.org/10.1016/j.joep.2011.02.004
  58. Van Rooij, M., Lusardi, A., & Alessie, R. (2011b). Financial literacy and stock market participation. Journal of Financial Economics, 101(2), 449-472. https://doi.org/10.1016/j.jfineco.2011.03.006
  59. Verkijika, S. F. (2020). An affective response model for understanding the acceptance of mobile payment systems. Electronic Commerce Research and Applications, 39, 100905. https://doi.org/10.1016/j.elerap.2019.100905