摘要

本研究分別針對在倚賴情緒進行決策的作業中表現較差的受試者中，以及受試者為管理學院背景或非管理學院背景時，觀察性格與專業背景是否會影響受試者的投資績效表現。本研究以二階段實驗取得研究樣本接著進行實證分析，研究對象以國立成功大學九大學院之學生作為樣本，原始樣本為470筆，最後用於迴歸測試的總樣本數量為120筆。實證結果發現：

（1） 在不區分受試者學術背景的情況下，並未發現「IGT實驗中表現較差的受試者」與「虛擬交易平台的投資績效」存在顯著關聯性。
（2） 進一步區分受試者學術背景的情況下，實證發現「管理學院背景的受試者」與「非管理學院背景的受試者」在虛擬交易平台的投資績效並無顯著之差異。
（3） 在區分受試者學術背景的情況下，實證發現「會計學系背景的受試者」相較於「其他學院科系背景的受試者」在虛擬交易平台的績效表現存在顯著較佳報酬成果。
（4） 透過IGT實驗中辨識出較容易做出不利選擇的受試者後，接著再區分受試者不同的學術背景差異下，實證發現「管理學院背景的受試者」與「非管理學院背景的受試者」在虛擬交易平台的投資績效並無顯著之差異。
（5） 透過IGT實驗中辨識出較容易做出不利選擇的樣本後，接著再區分受試者學術背景的情況下，實證發現「會計學系背景的受試者」相較於「其他學院科系背景的受試者」在虛擬交易平台的投資績效並無顯著之差異。

綜觀本研究之實證結果顯示，在本研究樣本群體下，雖然個人天生性格差異對於投資績效沒有存在顯著關聯(H3a、H3-b皆不顯著)，但從專業領域背景而言，卻能發現科系背景的確會對投資績效造成影響。然而若僅以是否為管理學院背景之專業範疇對象進行區分所得之實證結果並不顯著，故本研究進而區分受試者為「會計學系背景的受試者」與「其他學院科系背景的受試者」後，發現「會計學系背景的受試者」相較於「其他學院科系背景的受試者」在虛擬交易平台的績效表現顯著為佳，亦即會計領域學術素養能夠幫助受試者在投資中取得較好的績效表現。

Summary

This study focuses on the students who perform poorly result in the condition that they rely on emotion to make decisions. I examine whether the student’s background may affect the students’ investment performance. There are two-stage experiments in this study in order to obtain effective samples and then conduct empirical analysis. Taking National Cheng Kung University’s students as samples. The empirical results of this research show that:

(1) Students who perform poorly in the IGT experiment are not also performed poorly in stock investment.
(2) Students who have a management academic background do not perform better in stock investment than those who have a non-management academic background.
(3) Students who have an academic background in accounting perform better in stock investment than those who have an academic background in other academic courses.
(4) After distinguishing students who are more likely to make unfavorable choices in the IGT experiment. Students who have a management academic background do not perform better in stock investment than those who have a non-management academic background.
(5) After distinguishing students who are more likely to make unfavorable choices in IGT. Students who have an academic background in accounting are not performed better in stock investment than those who have an academic background in other academic courses.

　The empirical results of this research show that there is no correlation between individual innate personality and investment performance in this sample group. However, I find out that students’ academic backgrounds have an impact on investment performance.

參考文獻

Ana P. G. Jelihovschi, Ricardo L. Cardoso and Alexandre Linhares., 2018. An Analysis of the Associations among Cognitive Impulsiveness, Reasoning Process, and Rational Decision Making. Frontiers in Psychology.

Bechara, A., Damasio, A. R., Damasio, H., and Anderson, S. W., 1994. Insensitivity to future consequences following damage to human prefrontal cortex. Cognition, 50(1–3).

Buffett, W. E., 2003. Preface to the Fourth Edition. In B. Graham, and J. Zweig (Ed.), The Intelligent Investor: A book of practical counsel (Revised Edition edp. viii). New York : Perfect Bound.

Bechara, A., Damasio, H., and Damasio, A. R., 2000. Emotion, decision making and the orbitofrontal cortex. Cerebral Cortex, 10(3), 295–307.

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

Blanton, H., Pelham, B. W., DeHart, T., and Carvallo, M., 2001. Overconfidence as Dissonance Reduction. Journal of Experimental Social Psychology, 37, 373-385.

Blair, R. J. R., Colledge, E., and Mitchell, D. G. V., 2001. Somatic markers and response reversal: Is there orbitofrontal cortex dysfunction in boys with psychopathic tendencies？ Journal of Abnormal Child Psychology, 29, 499–511.

Bechara, A., Damasio, H., Damasio, A. R.,&Lee, G. P., 1999. Different contributions of the human amygdala and ventromedial prefrontal cortex to decision-making. The Journal of Neuroscience,　19, 5473–5481.

Chen, G., Kim, K. A., Nofsinger, J. R., and Rui, O. M., 2007. Trading performance, disposition effect, overconfidence, representativeness bias, and experience of emerging market investors. Journal of Behavioral Decision Making, 20(4), 425-451.

Camerer, C. F., Loewenstein, G., and Rabin, M., 2004. Advances in behavioral economics, Princeton university press.

Caroselli, J. S., Hiscock, M., Scheibel, R. S., and Ingram, F., 2006. The simulated gambling paradigm applied to young adults: An examination of university students’ performance. Applied Neuropsychology, 13, 203–212.

Cavedini, P., Riboldi, G., Keller, R., D’Annucci, A., and Bellodi, L., 2002. Frontal lobe dysfunction in pathological gambling patients. Biological Psychiatry, 51, 334–341.

Chad E. Lakey., Adam S. Goodie., and W. Keith Campbell., 2007. Frequent Card Playing and Pathological Gambling: The Utility of the Georgia Gambling Task and Iowa Gambling Task for Predicting PathologyJournal of Gambling Studies.

De Bortoli, D., da Costa, N., Goulart, M., and Campara, J., 2009. Personality traits and investor profile analysis: A behavioral finance study. (S. C. Gherghina, Ed.)

Dougherty, D. M., Mathias, C. W., Marsh-Richard, D. M., Furr, R. M., Nouvion, S. O., and Dawes, M. A., 2009. Distinctions in behavioral impulsivity: implications for substance abuse research. Addict. Disord.

Fields, S., Sabet, M., and Reynolds, B., 2013. Dimensions of impulsive behavior in obese, overweight, and healthy-weight adolescents. Appetite 70, 60–66.

Fraas, J.W., 1980. The use of seven simulation games in a college economics course. Journal of Experimental Eduacation, 48, 264-280.

Gremmen, H. & J. Potters., 1997. Assessing the efficacy of gaming in economic education. The Journal of Economic Education, 28(4), 291-303.

Janna Cousijn Reinout W. Wiers K. Richard Ridderinkhof Wim van den Brink Dick J. Veltman Linda J. Porrino Anna E. Goudriaan., 2012. Individual differences in decision making and reward processing predict changes in cannabis use: a prospective functional magnetic resonance imaging study. HUMAN NEUROIMAGING STUDY. 18, 1013–1023

Kahneman, D., and Tversky, A., 1979. A Prospect theory: an analysis of decision under risk. Econometrica, 47(2), 263-291.

Kahneman, D., 2011. Thinking, Fast and Slow. New York: Farrar, Straus and Giroux.

L. Clark, A. Bechara, H. Damasio, M. R. F. Aitken, B. J. Sahakian, T. W. Robbins., 2008. Differential effects of insular and ventromedial prefrontal cortex lesions on risky decision-making. Brain, Issue 5, Volume 131, Pages 1311–1322.

Levkin, B. J., 2005. Some evidence regarding computer-based financial instrument trading simulations and their use as an assessment tool. Journal of Financial Education, 31(2), 23-33.

Matt Hayes., 2013. Risky Decision, Affect, and Cognitive Load: Does Multi-Tasking Reduce Affective Biases？ W.P. Carey School of Accountancy First Year Research Paper.

McGue, M., Iacono, W. G., Legrand, L. N., and Elkins, I., 2001. Origins and consequences of age at first drink. ii. familial risk and heritability. Alcohol. Clin. Exp. Res. 25, 1166–1173.

Nofsinger, J. R., 2018. The Psychology of Investing (6 ed.). New York: Routledge.

Prosad, J. M., Kapoor, S., and Sengupta, J., 2015. Theory of Behavioral Finance. In Z. Copur, Handbook　of Research on Behavioral Finance and Investment Strategies: Decision Making in the Financial Industry. Hacettepe University, Turkey: IGI Global.

Petry, N. M., Bickel, W. K., and Arnett, M., 1998. Shortened time horizons and insensitivity to future consequence in heroin addicts. Addiction, 93, 729–738.

Pru Marriott, Siew Min Tan and Neil Marriott., 2015. Experiential Learning – A Case Study of the Use of Computerised Stock Market Trading Simulation in Finance Education. JOURNAL OF Accounting Education.

Watkins, L. H. A., Rogers, R. D., Lawrence, A. D., Sahakian, B. J., Rosser, A. E., and Robbins, T.W., 2000. Impaired planning but intact decision making in early Huntington’s disease: Implications for specific fronto-striatal pathology. Neuropsychologia, 38, 1112–1125.

Seiver, D., 2013. Incorporating a real-time FX trading platform in an international business　finance class. Journal of Financial Education 39, 53-65.

Steven D. Dolvin, Butler University Mark K. Pyles., 2011. THE INFLUENCE OF SIMULATION PERFORMANCE ON STUDENT INTEREST. Journal of Economics and Economic Education Research, College of Charleston. Volume 12.

Thaler, R. H., 2008. Mental Accounting and Consumer Choice. Marketing Science, 27(1).

Turnbull, O. H., Berry, H., and Bowman, C. H., 2003. Direct versus indirect emotional consequences on the Iowa gambling task. Brain and Cognition, 53, 389–392.

Van Rooij, M., Lusardi, A., & Alessie, R., 2007. Financial literacy and stock market participation. National Bureau of Economic Research Working Paper No. 13565, Cambridge, MA: NEBR.

陳安斌，陳莉貞，蘇秀玲，郭怡君，2018。我國發展機器人理財顧問之研究. 財團法人中華民國證券暨期貨市場發展基金會。

陳正佑，洪榮耀，陳俊賢，2008。投資人投資行為之研究－ 以虛擬交易所為例。商管科技季刊，第九卷第三期。

張道宜，2018。想靠機器人理財，你該先搞懂這些事。Cheers雜誌，210期。

顏乃欣，2010。情緒對決策歷程的影響，心理學門熱門前瞻研究，第11卷第4期。

楊金龍，2018。20年來 (1998至2017年)我國經濟成長率、通貨膨脹率及人均GDP 與新加坡、韓國及香港之比較，立法院財政委員會全體委員會議，第9屆第5會期第11次。