The seminar gives an introduction into various aspects of Behavioral Finance. Investors are expected to act irrationally and without complete information. Investors as actors and their behavior are in the focus of analysis. We investigate how investment decisions are formed and how investors err. We look at strategies and instruments to alleviate those errors.
To pass the course, you have to successfully pass the following examinations:
1. Written Report (due two weeks before assigned presentation date, electronic and print version; scope 10-15 pages per person). Detailed outlines may be sent to Prof. Teichert in advance to get feedback before handing in.
2. Presentation of own topic (15 to 20 minutes presentation, 10 minutes discussion)
3. Short presentation (5 min) on topic of fellow students with critical feedback. Assignment is conducted by the Chair. The documents are sent out two weeks in advance.
In the following, you will find literature for every single topic. Students should derive the conceptual framework and apply them to a specific application case. Students are expected to draw from consumer behavior literature and, in a second step, relate the findings to behavioral investing. Exceptions are topics that are exclusively relevant for behavioral investing.
Block 1: Foundations of Behavior Finance
Traditional versus Behavioral Finance
- Ricciardi, V., & Simon, H. K. (2000). What is behavioral finance?. Business, Education & Technology Journal, 2(2), 1-9.
- Ricciardi, V. (2008). Risk: Traditional finance versus behavioral finance. Handbook Of Finance, 3.
- Nigam, R. M., Srivastava, S., & Banwet, D. K. (2018). Behavioral mediators of financial decision making–a state-of-art literature review. Review of Behavioral Finance, 10(1), 2-41.
- Massa, M., & Simonov, A. (2005). Behavioral biases and investment. Review of Finance, 9(4), 483-507. Cheng, P. Y. (2007).
- Zahera, S. A., & Bansal, R. (2018). Do investors exhibit behavioral biases in investment decision making? A systematic review. Qualitative Research in Financial Markets, 10(2), 210-251.
Behavioral Investing of Professionals
- Aharoni, Y. (2010). Behavioral elements in foreign direct investments. In The Past, Present and Future of International Business & Management (pp. 73-111). Emerald Group Publishing Limited.
- Hunjra, A. I., Rehman, K. U., & Ali Qureshi, S. (2012). Factors affecting investment decision making of equity fund managers. Wulfenia Journal, 19(10).
- Khan, A. M. (1987). Assessing venture capital investments with noncompensatory behavioral decision models. Journal of Business Venturing, 2(3), 193-205.
Block 2: Determinants of investor behavior
- Wang, X.L., Shi, K. and Fan, H.X. (2006), “Psychological mechanisms of investors in Chinese stock markets”, Journal of Economic Psychology, Vol. 27 No. 6, pp. 762-780.
- Sachse, K., Jungermann, H. and Belting, J.M. (2012), “Investment risk–the perspective of individual investors”, Journal of Economic Psychology, Vol. 33 No. 3, pp. 437-447.
- Subrahmanyam, A. (2008), “Behavioural finance: a review and synthesis”, European Financial Management, Vol. 0, pp. 12-29
- Soufian, M., Forbes, W. and Hudson, R. (2014), “Adapting financial rationality: is a new paradigm emerging?”, Critical Perspectives on Accounting, Vol. 25 No. 8, pp. 724-742.^
- Van Rooij, M., Lusardi, A., & Alessie, R. (2011). Financial literacy and stock market participation. Journal of Financial Economics, 101(2), 449-472.
- Hayat, A. and Anwar, M. (2016), “Impact of behavioral biases on investment decision; moderating role of financial literacy”, SSRN Electronic Journal, pp. 1-14, available at: https://doi.org/10.2139/ssrn.2842502
Psychology and Emotions
- Muradoglu, G., & Harvey, N. (2012). Behavioural finance: the role of psychological factors in financial decisions. Review of Behavioural Finance, 4(2), 68-80.
- Wolf, E. (2005), Why the House Always Wins: A Behavioral Perspective on Investor Trading in the Stock Market?, available at SSRN: https://ssrn.com/abstract=2026577
- Duxbury, D. (2015). Behavioral finance: insights from experiments II: biases, moods and emotions. Review of Behavioral Finance, 7(2), 151-175.
- Kubilay, B., & Bayrakdaroglu, A. (2016). An empirical research on investor biases in financial decision-making, financial risk tolerance and financial personality. International Journal of Financial Research, 7(2), 171-182.
- Rizvi, S., & Fatima, A. (2015). Behavioral finance: A study of correlation between personality traits with the investment patterns in the stock market. In Managing in recovering markets (pp. 143-155). Springer, New Delhi.
Socio-Economic Wealth Considerations
- Gomez–Mejia, L. R., Campbell, J. T., Martin, G., Hoskisson, R. E., Makri, M., & Sirmon, D. G. (2014). Socioemotional wealth as a mixed gamble: Revisiting family firm R&D investments with the behavioral agency model. Entrepreneurship Theory and Practice, 38(6), 1351-1374.
Behavioral Decision Making
- Stracca, L. (2004). Behavioral finance and asset prices: Where do we stand?. Journal of Economic Psychology, 25(3), 373-405.
- Benartzi, S., & Thaler, R. (2007). Heuristics and biases in retirement savings behavior. Journal of Economic perspectives, 21(3), 81-104.
- Schwartz, H. (2010). Heuristics or rules of thumb. Behavioral Finance: Investors, Corporations and Markets, Ed. by H. Kent Baker ve John R. Nofsinger, New Jersey, John Wiley & Sons, 57-72.
Block 3: Biases
Overconfidence and Self-Attribution Bias
- Cheng, P. Y. (2007). The trader interaction effect on the impact of overconfidence on trading performance: An empirical study. The Journal of Behavioral Finance, 8(2), 59-69.
- Van de Venter, G., & Michayluk, D. (2008). An insight into overconfidence in the forecasting abilities of financial advisors. Australian Journal of Management, 32(3), 545-557.
- Kafayat, A. (2014), “Interrelationship of biases: effect investment decisions ultimately”, Theoretical and Applied Economics, Vol. 11 No. 6, pp. 85-110.
Disposition and Endowment effect
- Shefrin, H. and Statman, M. (1985), “The disposition to sell winners too early and ride losers too long: theory and evidence”, The Journal of Finance, Vol. 40 No. 3, pp. 777-790.
- Aspara, J. and Hoffmann, A.O.I. (2015), “Cut your losses and let your profits run: how shifting feelings of personal responsibility reverses the disposition effect”, Journal of Behavioral and Experimental Finance, Vol. 8, pp. 18-24.
- Suresh, A. (2013), “Understanding behavioral finance through biases and traits of trader vis À-vis investor”, Journal of Finance, Accounting and Management, Vol. 4 No. 2, pp. 11-25.
- Demirer, R. and Kutan, A.M. (2006), “Does herding behavior exist in Chinese stock markets?”, Journal of International Financial Markets, Institutions and Money, Vol. 16 No. 2, pp. 123-142
- Casavecchia, L. (2016), “Fund managers’ herding and mutual fund governance”, International Journal of Managerial Finance, Vol. 12 No. 3, pp. 242-276
Loss aversion and regret aversion
- Fellner, G. and Sutter, M. (2009), “Causes, consequences, and cures of myopic loss aversion–an experimental investigation”, The Economic Journal, Vol. 119 No. 537, pp. 900-916.
- Godoi, K.C., Marcon, R. and da Silva, A.B. (2005), “Loss aversion: a qualitative study in behavioral finance”, Managerial Finance, Vol. 31 No. 4, pp. 46-56.
- Reb, J. (2008), “Regret aversion and decision process quality: Effects of regret salience on decision process carefulness”, Organizational Behavior and Human Decision Processes, Vol. 105 No. 2, pp. 169-182.
- Barberis, N. and Huang, M. (2001), “Mental accounting, loss aversion, and individual stock returns”, The Journal of Finance, Vol. 56 No. 4, pp. 1247-1292
- Zhou, R., & Pham, M. T. (2004). Promotion and prevention across mental accounts: When financial products dictate consumers& investment goals. Journal of Consumer Research, 31(1), 125-135.
Availability, Recency, Representativeness
- Mallick, L.R. (2015), “Biases in behavioural finance: a review of literature”, Journal of Advances in Business Management, Vol. 1 No. 3, pp. 100-104.
- Nofsinger, J. R., & Varma, A. (2013). Availability, recency, and sophistication in the repurchasing behavior of retail investors. Journal of Banking & Finance, 37(7), 2572-2585.
Anchoring, Conformation and Hindsight Bias
- Biais, B. and Weber, M. (2009), “Hindsight bias, risk perception, and investment performance”, Management Science, Vol. 55 No. 6, pp. 1018-1029.
- Costa, D. F., de Melo Carvalho, F., de Melo Moreira, B. C., & do Prado, J. W. (2017). Bibliometric analysis on the association between behavioral finance and decision making with cognitive biases such as overconfidence, anchoring effect and confirmation bias. Scientometrics, 111(3), 1775-1799.
Conservatism and Home bias
- Ahsan, S.M. and Malik, H. (2016), “Moderating role of conservatism bias in personality traits and investment management”, available at SSRN: https://ssrn.com/abstract=2812604
- Mohlmann, A. (2013), “Investor home bias and sentiment about the country benefiting from the tax revenue”, Journal of Economic Psychology, Vol. 35, pp. 32-36.
- Oehler, A., Wendt, S. and Horn, M. (2017), “Are investors really home-biased when investing at home?”,Research in International Business and Finance, Vol. 40, pp. 52-60.
Block 4: Implications
Portfolio analysis and formation
- Hoffmann, A.O.I., Shefrin, H.M. and Pennings, J.M.E. (2010), “Behavioral portfolio analysis of individual investors”, SSRN Electronic Journal, pp. 1-45, available at: https://doi.org/10.2139/ssrn.1629786
- Daly, K. and Vo, X.V. (2013), “The determinants of home bias puzzle in equity portfolio investment in Australia”, International Review of Financial Analysis, Vol. 27, pp. 34-42.
Stock market volatility
Olsen, R. A. (1998). Behavioral finance and its implications for stock-price volatility. Financial analysts journal, 54(2), 10-18.
Glaser, M. and Weber, M. (2007), “Overconfidence and trading volume overconfidence and trading volume”, The Geneva Risk and Insurance Review, Vol. 32 No. 1, pp. 1-36.
Messis, P. and Zapranis, A. (2014), “Herding behaviour and volatility in the Athens stock exchange”, The Journal of Risk Finance, Vol. 15 No. 5, pp. 572-590
- Chandra, A., & Thenmozhi, M. (2017). Behavioural asset pricing: Review and synthesis. Journal of Interdisciplinary Economics, 29(1), 1-31.
- Daniel, K.D., Hirshleifer, D. and Subrahmanyam, A. (1998), “Investor psychology and security market under- and overreactions”, Journal of Finance, Vol. 53 No. 6, pp. 1839-1886
- Dash, S.R. (2016), “Does investor sentiment as conditioning information help to explain stock returns behaviour? a test of alternative asset pricing models”, Review of Behavioral Finance, Vol. 8 No. 2, pp. 174-198.
Nudging & other instruments to limit the effects of biases
- Benartzi, S., & Thaler, R. H. (2013). Behavioral economics and the retirement savings crisis. Science, 339(6124), 1152-1153.
- Pompian, M. M. (2012). Behavioral finance and investor types: managing behavior to make better investment decisions. John Wiley & Sons.
- Nenkov, G.Y., Inman, J.J., Hulland, J. and Morrin, M. (2009), “The impact of outcome elaboration on susceptibility to contextual and presentation biases”, Journal of Marketing Research (JMR), Vol. 46 No. 6, pp. 764-776,
Designing Investment Products
- Pompian, M. M., & Longo, J. M. (2004). A new paradigm for practical application of behavioral finance: creating investment programs based on personality type and gender to produce better investment outcomes. The Journal of Wealth Management, 7(2), 9-15.
- Dierkes, M., Erner, C., & Zeisberger, S. (2010). Investment horizon and the attractiveness of investment strategies: A behavioral approach. Journal of Banking & Finance, 34(5), 1032-1046.
- Pompian, M. M. (2011). Behavioral finance and wealth management: how to build investment strategies that account for investor biases (Vol. 667). John Wiley & Sons.
- Kumiega, A., & Van Vliet, B. E. (2012). Automated finance: The assumptions and behavioral aspects of algorithmic trading. Journal of Behavioral Finance, 13(1), 51-55.
- Groß-Klußmann, A., & Hautsch, N. (2011). When machines read the news: Using automated text analytics to quantify high frequency news-implied market reactions. Journal of Empirical Finance, 18(2), 321-340.
- Rook, D. (2013). Paying attention (due) to memory structure: Tail simulation and cyborg finance. Available at SSRN 2356929.
- Gonçalves, C. P. (2018). Financial Risk and Returns Prediction with Modular Networked Learning. arXiv preprint arXiv:1806.05876