Feedback and winning-losing probability effects on economic behavior in risky choices decision-making

Myopic Loss Aversion (MLA) is one of the study objects of behavioral economics. It corresponds to the fact that participants, when facing choice situations, cannot rationally evaluate the risks and profits of available options, leading them to choose investments more likely to occur but less profitable. This behavior shows that they cannot evaluate the options satisfactorily, so they have sub-optimal decisions. There may be conditions for MLA more favorable for it to occur, as the frequency one shows the participant the outcomes of their choices (feedback) and the probability of winning or losing. In this way, this study aims to evaluate how feedback influences participants' choices and the influence and interaction of the winning and losing probability. This study had the participation of 80 people, ages 18 to 30 years, all university students, 29 women and 51 men, without either relation to business degree courses or familiarity with the research area on economic behavior. The experiment consisted in making nine repeated choices in a lottery game. Participants started the experiment with R$1000 (a thousand) fictitious reais (Brazilian currency); each lottery game had a cost of 150 reais, and the profits returned this invested value with an addition of more 150 reais. The results indicate that the presence of feedback induces participants to bet more. However, the winning and losing probability do not influence the invested amount, and there was no interaction between these two factors.

https://doi.org/10.55223/bej.2

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References

Anand P. (1995). Foundations of Rational Choice under Risk. Oxford: Oxford University Press.

Bellemare, C., Krause, M., Kröger, S., & Zhang, C. (2005). Myopic loss aversion: Information feedback vs. investment flexibility. Economics Letters, 87(3), 319–

https://doi.org/10.1016/j.econlet.2004.12.011

Benartzi, S., & Thaler, R. H. (1999). Risk Aversion or Myopia? Choices in Repeated Gambles and Retirement Investments. Management Science, 45(3), 364–381. https://doi.org/10.1287/mnsc.45.3.364

Benartzi, S., & Thaler, R. H. R. (1995). Myopic loss aversion and the equity premium puzzle. The Quarterly Journal of Economics, 110(1), 73–92. https://doi.org/10.2307/2118511

Bickel, W. K., Marsch, L., Smith, C. L., Hantula, D. A., Weatherly, J. N., Derenne, A.,… Ainslie, G. (2002). Within-subject comparison of real and hypothetical money rewards in delay discounting. Journal of the Experimental Analysis of Behavior, 77(4), 129–146. https://doi.org/10.1901/jeab.2002.77-129

Day, R. H. (1971). Rational Choice and Economic Behavior. Theory and Decisions, 1, 229–251.

Fellner, G., & Sutter, M. (2009). Causes, consequences, and cures of myopic loss aversion - An experimental investigation. Economic Journal, 119(537), 900–916. https://doi.org/10.1111/j.1468-0297.2009.02251.x

Fishburn, P. C. (1970). Utility Theory for Decision Making. New York: Wiley.

Gneezy, U., Kapteyn, A., & Potters, J. (2003). Evaluation Periods and Asset Prices in a Market Experiment. Journal of Finance, 58(2), 821–837. https://doi.org/10.1111/1540-6261.00547

Gneezy, U., & Potters, J. (1997). An Experiment on Risk Taking and Evaluation Periods. The Quarterly Journal of Economics, 112(2), 631–645. https://doi.org/10.1162/003355397555217

Haffke, P., & Hübner, R. (2015). Effects of different feedback types on information integration in repeated monetary gambles. Frontiers in Psychology, 6(JAN), 1–13. https://doi.org/10.3389/fpsyg.2015.00597

Haigh, M. S., & List, J. A. (2005). Do professional traders exhibit myopic loss aversion? An experimental analysis. The Journal of Finance, 60(1), 523-534. DOI: 10.1111/j.1540-6261.2005.00737.x

Haisley, E., Mostafa, R., & Loewenstein, G. (2008). Myopic risk-seeking: The impact of narrow decision bracketing on lottery play. Journal of Risk and Uncertainty, 37(1), 57–75. https://doi.org/10.1007/s11166-008-9041-1

Hopfensitz, A., & Wranik, T. (2008). Psychological and environmental determinants of myopic loss aversion. MPRA Paper, (9305). Retrieved from http://mpra.ub.uni- muenchen.de/9305/%5Cnhttp://mpra.ub.uni- muenchen.de/9305/%5Cnhttp://mpra.ub.uni- muenchen.de/9305/1/MPRA_paper_9305.pdf

Iturbe-Ormaetxe, I., Ponti, G., & Tomás, J. (2016). Myopic loss aversion under ambiguity and gender effects. PLoS ONE, 11(12). https://doi.org/10.1371/journal.pone.0161477

Jessup, R. K., Bishara, A. J., & Busemeyer, J. R. (2008). Feedback produces divergence from prospect theory in descriptive choice. Psychological Science, 19(10), 1015– 1022. https://doi.org/10.1111/j.1467-9280.2008.02193.x

Kahneman, D., & Tversky, A. (2013). Choices, values, and frames. In Handbook of the fundamentals of financial decision making: Part I (pp. 269-278).

Kahneman, D., & Lovallo, D. (1993). Timid Choices and Bold Forecasts: A Cognitive Perspective on Risk Taking. Management Science, 39(1), 17–31. https://doi.org/10.1287/mnsc.39.1.17

Kahneman, D., & Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk. Econometrica, 47(2), 263–292. https://doi.org/10.2307/1914185

Kahneman, D., & Tversky, A. (1984). Choices, values and Frames. American Psychologist, 39(4), 341. https://doi.org/10.1037/0003-066X.39.4.341

Keren, G., & Wagenaar, W. A. (1987). Violation of utility theory in unique and repeated gambles. Journal of Experimental Psychology: Learning, Memory, and Cognition, 13(3), 387. DOI: 10.1016/j.jebo.2003.01.005

Langer, T., & Weber, M. (2005). Myopic prospect theory vs. myopic loss aversion: how general is the phenomenon?. Journal of Economic Behavior & Organization, 56(1), 25-38.

Langer, T., & Weber, M. (2008). Does commitment or feedback influence myopic loss aversion?. An experimental analysis. Journal of Economic Behavior and Organization, 67(3–4), 810–819. https://doi.org/10.1016/j.jebo.2006.05.019

Lejarraga, T. (2010). When experience is better than description: Time delays and complexity. Journal of Behavioral Decision Making, 23(1), 100–116. https://doi.org/10.1002/bdm.666

Lejarraga, T., & Gonzalez, C. (2011). Effects of feedback and complexity on repeated decisions from description. Organizational Behavior and Human Decision Processes, 116(2), 286–295. https://doi.org/10.1016/j.obhdp.2011.05.001

Leon, O. G., & Lopes, L. L. (1988). Risk preference and feedback. Bulletin of the Psychonomic Society, 26(4), 343–346. https://doi.org/10.3758/BF03337676

Lopes, L. L. (1981). Decision making in the short run. Journal of Experimental Psychology: Human Learning and Memory, 7(5), 377.

Odean, T. (1998). Are investors reluctant to realize their losses? Journal of Finance, 53(5), 1775–1798. https://doi.org/10.1111/0022-1082.00072

Peirce, J. W. (2007). PsychoPy-Psychophysics software in Python. Journal of Neuroscience Methods, 162(1–2), 8–13. https://doi.org/10.1016/j.jneumeth.2006.11.017

R Development Core Team, R. (2011). R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing (Vol. 1). https://doi.org/10.1007/978-3-540-74686-7

Shefrin, H., & Statman, M. (1985). The Disposition to Sell Winners Too Early and Ride Losers Too Long: Theory and Evidence. The Journal of Finance, 40(3), 777–790. https://doi.org/10.1111/j.1540-6261.1985.tb05002.x

Staw, B. M. (1997). The escalation of commitment: An update and appraisal. In Z. Shapira (Ed.), Cambridge series on judgment and decision making. Organizational decision making (p. 191–215). Cambridge University Press.

Thaler, R. H. (1985). Mental accounting and consumer choice. Marketing Science1, 4(1), 199–214. https://doi.org/10.1287/mksc.1070.0330

Thaler, R. H., & Johnson, E. J. (1990). Gambling with the house money and trying to break even: The effects of prior outcomes on risky choice. Management science, 36(6), 643-660. DOI: 10.1287/mnsc.36.6.643

Thaler, R., Tversky, a., Kahneman, D., & Schwartz, a. (1997). The effect of myopia and loss aversion on risk taking: An experimental test. The Quarterly Journal of Economics, 112(2), 647–661. https://doi.org/10.1162/003355397555226

Tversky, A., & Kahneman, D. (1992). Advances in prospect theory: Cumulative representation of uncertainty. Journal of Risk and Uncertainty, 5(4), 297–323. https://doi.org/10.1007/BF00122574

Wang, M.-L., Huang, H.-H., & Hsu, S.-C. (2013). The Effect of Information Feedback Frequency and Investment Flexibility on Myopic Loss Aversion. Asian Economic and Financial Review, 3(9), 1232–1248. Retrieved from http://search.proquest.com/docview/1504127829?accountid=17215%5Cnhttp://sfx. libis.be/kuleuven?url_ver=Z39.88- 2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&genre=article&sid=ProQ:ProQ:e conlitshell&atitle=The+Effect+of+Information+Feedback+Frequency+and+Inv

Weber, M., & Camerer, C. F. (1998). The Disposition Effect in Securities Trading: An Experimental Analysis. Journal of Economic Behavior & Organization, 33(2), 167–184. https://doi.org/10.1016/S0167-2681(97)00089-9

Weber, M., & Zuchel, H. (2005). How do prior outcomes affect risk attitude? Comparing escalation of commitment and the house-money effect. Decision Analysis, 2(1), 30-43. DOI: 10.1287/deca.1050.0034

Zeisberger, S., Vrecko, D., & Langer, T. (2012). Measuring the time stability of prospect theory preferences. Theory and Decision, 72(3), 359-386. DOI: 10.1007/s11238-010-9234-3