Behavioral Economics and Finance

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Behavioral Economics and Finance Lecturer: Alexis V. Belianin, Dmitry V. Repin

Course description The course aims to introduce students to a relatively new and quickly growing area of research which studies the impact of psychological regularities of perception, judgment and action on economic behavior. Unlike traditional economics, which commits itself to a rather streamlined model of homo economicus, behavioural economics takes into account a much broader range of psychologically-driven phenomena which condition the decisions made by real people. In that sense, behavioural economics is a modern ‘descriptive’ face of economic studies of human decision-making in a broad range of contexts. These include, but are not limited to: individual choice under risk and uncertainty; decision heuristics, learning and cognition, motivation in interactive and collective contexts, intertemporal preferences and financial decision-making in corporate and markets settings. In all these areas behavioural economics offers a bulk of new results which help explaining the existing ‘puzzles’, and new insights which shed new lights onto the nature of human cognition, judgment and behaviour. A particularly important area of study within the course is behavioural finance. This part of the course covers the link between the peculiarities of human behavior and aspects of financial and investment management, as well as corporate and risk management. It puts various “behavioral mechanisms” into more basic psychological framework spanning the mechanisms of information perception, emotions, memory, and attention. This material is primarily built upon empirical data on financial markets and corporate behavior. Other sources of data comes from experimental economics — a closely related area of research, which is responsible for registering many of the observed ‘paradoxes’, and for paving the way to their resolution. Practicing experimental economics, i.e. participation in several classroom experiments, will be an integral part of the course.

Assessment There will be several activities which are to be assessed separately. First, there will be several homeworks devoted to practical problem solving and discussion of particular topics of interest. Second, students will have to write a research essay on a particular problem: find a behavioural phenomenon of economic importance, or a case in behavioural finance, and describe it using analytical methods and/or empirical model you have studied. Third — as a matter of

2 saliency — some credits will be given for performance in the classroom experiments. Fourth, a small percentage of points will be awarded for the classroom activity.

Grade determination Finally, grade will depend on the final exam. Percentages for these kinds of activities are as follows: • Homework — 15% • Research essay — 15% • Classroom experiments — 10% • Classwork — 10% • Final examination — 50%

Main reading There is no single textbook for the course, although there are quite a few sources which cover the material discussed. Some of them are listed below, and the list includes both collections of elsewhere published papers, and special monographs. 1. Camerer C., Loewenstein G., Rabin M. Advances in Behavioural Economics. Princeton: Princeton University Press, 2004.

Additional reading 1. Bell D.E., Raiffa H., Tversky A. (1988) Decision-making: descriptive, normative and prescriptive interactions. Cambridge: Cambridge University Press. 2. Kahneman D. and Tversky A., eds. (2000). Choices, values and frames. Cambridge: Cambridge University Press. 3. Kahneman D., Slovic P., Tversky A. (1982) Judgement under uncertainty: Heuristics and biases, Cambridge: Cambridge University Press. 4. Kagel J. and Roth A. (1995) Handbook of experimental economics. Princeton: Princeton University Press, 1995. 5. Rubinstein A. (1998) Modeling bounded rationality. MIT Press.

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6. Shleifer, Andrei (1995) Inefficient Markets: an introduction to behavioural finance. Oxford University Press. 7. Plous, Scott (1993) The Psychology of Judgment and Decision Making.

Course outline 1. Rationality Origins of rationality: normative, descriptive and prescriptive aspects. Normative theory of rationality. Substantial vs. bounded rationality. Methodology of economic analysis: positivist vs. behavioural economics. 1. Simon H.A. (1978) Rationality as the process and as a product of thought. American Economic Review, v.68, no.2, p.1-16.Simon H.A. QJE 1955 2. Conlisk J. Why bounded rationality. Journal of Economic Literature, Vol. 34, No. 2 (Jun., 1996), pp. 669-700 3. Arrow K.J. Rationality of self and others in an economic system. In: R.M. Hogarth and M.W. Reder (eds.). Rational choice: the contrast between economics and psychology. Chicago: The University of Chicago Press, 1987. 4. Sen A.K. (1987) Rational behaviour. In: J. Eatwell, M. Milgate, P. Newman eds. The New Palgrave. A Dictionary of Economics. London: Macmillan. 5. Rabin M. (1998) Psychology and economics. Journal of Economic Literature, Vol. 36, No. 1, pp. 11-46. 6. Friedman M. (1953) Methodology of positive economics. In: M.Friedman. Essays in positive economics. Chicago: University of Chicago Press. 2. Heuristics, biases and beyond Puzzles and limitations of individual decision: context-dependence, overconfidence, hindsight, law of small numbers, violations of monotonicity, confirmatory bias etc. Representation of preferences of less-than-perfectly-rational decision maker. Heuristics and biases paradigm vs. adaptive approach. 1. Tversky A. and Kahneman D. (1981) The framing of decisions and the psychology of choice. Science, vol. 211, pp. 453-458. 2. Gigerenzer Gerd (2001) The Adaptive Toolbox. In: G. Gigerenzer and R. Selten, eds. Bounded Rationality: The Adaptive Toolbox, MIT Press.

4 3. Krantz D.H., Luce R.D., Suppes P., Tversky A. (1971) Foundations of measurement. Vol. 1. New York: Academic Press. 4. Broome J. (1991) Utility. Economics and Philosophy, vol. 7, no. 1, pp. 1-12. 5. Farquhar P.H. (1984) Utility assessment methods. Management Science, vol. 30, no. 11, pp. 1283-1300. 6. Camerer C. and Lovallo D. Overconfidence and Excess Entry: An Experimental Approach. CVF 23 http://masada.hss.caltech.edu/˜camerer/camerer.html 7. Fischhoff B. (1975) Hindsight 6= foresight: the effect of outcome knowledge n judgment under uncertainty. Journal of Experimental Psychology: Human Perception and Performance, vol. 1, pp. 288-299. 8. Fischhoff B. and Beyth R. (1975) ‘I knew it would happen’ — remembered probabilities of once-future things. Organizational Behaviour and Human Decision Processes, vol. 13, pp. 1-16. 9. Rabin, M. Risk Aversion and Expected-Utility Theory: A Calibration Theorem. Econometrica, Vol. 68, No. 5 (Sep., 2000), pp. 1281-1292. 3. Alternative decision theories Expected utility vs. its extensions: prospect theory, rank-dependent expected utility, indirect utility, lottery-dependent utility, regret theory etc. Advantages and limitations of these theories. Procedural decision theories. Empirical tests. 1. Kahneman, D., Tversky, A. “Prospect theory: An analysis of decision under risk”, Econometrica, vol. 47, no. 2, March 1979, pp. 263-91. 2. Tversky, A. and Kahneman, D. “Advances in Prospect theory: Cumulative representation of uncertainty”, Journal of risk and uncertainty, v. 5 (4), 1992. 3. Quiggin J. (1993) Generalized expected utility theory: the rand-dependent model. Boston: Kluwer. 4. Wakker P.P. (1994) Separating marginal utility and probabilistic risk aversion. Theory and Decision, vol. 36, pp. 1-44. 5. Loomes G. and Sugden R. (1982) Regret theory: an alternative theory of rational choice under uncertainty. Economic Journal, vol. 92, pp. 805-824.

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6. Becker J. and Sarin R. (1987) Lottery-dependent utility. Management Science, v.33, no.11, p.1367-1382. 7. Rubinstein A. (1988) Similarity and decision-making under risk (Is there a utility theory resolution to the Allais paradox?). Journal of Economic Theory, v.46, p.145-153. 8. Gilboa I. and Schmeidler D. (1995) Case-based decision theory. Quarterly Journal of Economics, v.110, p.605-639. 9. Chechile R.A. and Cooke A.D.J. (1997) An experimental test of a general class of utility models: evidence for context dependency. Journal of Risk and Uncertainty, v.14, no.1, p.75-93. 10. Hey J.D. and Orme C. (1994) Investigating generalizations of expected utility theory using experimental data. Econometrica, v.62, p.1291-1326. 4. Memory, cognition and their economic implications Limitations of memory, track dependence, learning effects in individual and interactive settings. Intertemporal preferences and choice: theory of multiple selves. Motivation and incentives. Cognitive limitations, perception biases and their economic implications. 1. Rabin M. and Schrag K. (1999). First impressions matter: a simple model of confirmatory bias. Quarterly Journal of Economics, Vol. 114, No. 1 (Feb., 1999), pp. 37-82 2. Mullainathan S. A memory based model of bounded rationality. Quarterly Journal of Economics. Vol. 117, No. 3 (Aug., 2002), pp. 735-774 3. Romer P. (2000) Thinking and Feeling. American Economic Review, Vol. 90, No. 2, Papers and Proceedings of the One Hundred Twelfth Annual Meeting of the American Economic Association (May, 2000), pp. 439-443. 4. Shafir, E., Diamond, P., and Tversky, A. Money illusion. Quarterly Journal of Economics, v112 n2, May 1997, p.341-74. 5. Benabou R. and Tirole J. Intrinsic and extrinsic motivation. Review of Economic Studies, Vol. 70, No. 3 (Jul., 2003), pp. 489-520. 6. Benabou R. and Tirole J. Self-confidence and personal motivation. Quarterly Journal of Economics, Vol. 117, No. 3 (Aug., 2002), pp. 871-915 5. Game theory models I: Evolutionary games Evolutionary game theory and its applications to bounded rationality. Evolutionary stability of equilibria, evolutionary dynamics and their applications to modeling learning and long-run economic behaviour.

6 1. Gintis H. Game theory evolving. Princeton University Press, 2002. 2. Erev, Ido and Roth, Alvin. (1998) Predicting how people play games. American Economic Review, v.88 n.4, September 1998, p.848-81. 3. Kandori M., Mailath G., Rob R. Learning, mutations and long-run equilibria in games. Econometrica, Vol. 61, No. 1 (Jan., 1993), pp. 29-56. 4. Samuelson L. Evolutionary Games and Equilibrium Selection, MIT Press, 1997. 5. Weibull J. Evolutionary game theory. MIT Press, 1995. 6. Game theory models II: Psychological games Modelling feelings in social interactions: the psychological games framework. Applications to fairness, altruism, reciprocity; experimental and theoretical results. 1. Geanakoplos, J., D. Pearce & E. Stacchetti. 1989. Psychological Games and Sequential Rationality. Games & Economic Behavior 1, 60–79. 2. Rabin M. (1993). Incorporating fairness into game theory. American Economic Review, Vol. 83, No. 5 (Dec., 1993), pp. 1281-1302. 3. Duwfenberg M. and Kirchsteiger G. (2004) A Theory of Sequential Reciprocity. Games & Economic Behavior 47, 268-98 4. Fehr E. and Gaechter S. (2000) Fairness and Retaliation: The Economics of Reciprocity", Journal of Economic Perspectives 14(3), Summer 2000, 159-181. 7. Applied behavioural models in economics Models of procedurally rational behaviour and their economic implications (labor economics, macroeconomics, financial economics). 1. Akerlof G. and Yellen J.L. Can Small Deviations from Rationality Make Significant Differences to Economic Equilibria? American Economic Review Vol. 75 (4). p 708-720, September 1985. 2. Akerlof, G. (1982) Labor contracts as partial gift exchange”. Quarterly Journal of Economics, Vol. 97, No. 4, p.543-69. 3. Akerlof, G.and Dickens T. (1982) Economic consequences of cognitive dissonance. American Economic Review, Vol. 72, No. 3 (Jun., 1982), pp. 307-319

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4. Laibson D. Golden eggs and hyperbolic discounting. Quarterly Journal of Economics, Vol. 112, No. 2, In Memory of Amos Tversky (1937-1996) (May, 1997), pp. 443-477 5. Shafir E., Diamond P., Tversky, A. (1997) Money illusion. Quarterly Journal of Economics, v112 n2, May 1997, p.341-74. 8. Behavioral factors and financial markets Empirical data that challenge the Efficient Markets Hypothesis. Fundamental information and financial markets. Information available for marlet participants and market efficiency. Market predictability. The concept of limits of arbitrage and model by Shleifer and Vishny. Case study: Long Term Capital Management. Asset management and behavioral factors. Active portfolio management: return statistics and sources of systematic underperformance. Fundamental information, technical analysis, and behavioral factors. 1. Shleifer, Andrei and Vishny, Robert W., 1997, The Limits of Arbitrage, Journal of Finance, 52, 35-55. 2. Froot, Kenneth A. and Perold, Andre F., 1996, Global Equity Markets: The Case of Royal Dutch and Shell, Harvard Business School Case 296077. 3. Loewenstein, George, 2002. When Genius Failed: The Rise and Fall of Long-Term Capital Management. 4. Baker, M. and Savasoglu, S., 2002, Limited arbitrage in mergers and acquisitions. Journal of Financial Economics, 64, 91-115. 9. External factors and investor behavior Weather, emotions, and financial markets: sunshine, geomagnetic activity. Mechanisms of the external factor influence on risk perception and attitudes. Connection to human psychophysiology and emotional regulation. Misattribution as a mechanism for externals factors influence. Statistical methodology for capturing the effects of external influence onto stock market returns. Emotional content of news articles and their correlation with market dynamics. Social trends and market dynamics: music, fashion, demographics. Active portfolio management — the source of the systematic underperformance. Fundamental information and technical analysis — the case for psychological influence. Case study: Fidelity Magellan Fund and Peter Lynch. 1. Krivelyova, Anna and Robotti, Cezare, 2003, Playing the field: Geomagnetic storms and international stock markets. Working paper 2003-5a, Federal Reserve Bank of Atlanta. 2. Hirshleifer, D., and T. Shumway, 2003, Good Day Sunshine: Stock Returns and the Weather”, Journal of Finance, Forthcoming.

8 3. Kamstra, Mark, Kramer, Lisa, and Levi, Maurice, 2002, Winter blues: A SAD stock market cycle. Working paper 2002-13, Federal Reserve Bank of Atlanta. 4. Prechter, Robert, 2003, Social Causality chapter in Pioneering Studies in Socionomics. 10. Behavioral corporate finance Behavioral factors and corporate decisions on capital structure and dividend policy. Capital structure dependence on market timing. Empirical data on dividend presence or absence. Timing of good and bad corporate news announcement. Mergers and acquisitions and the Winner’s Curse. M&A waves and market timing. IPO underpricing. Systematic excessive optimism and overconfidence in managers’ decisions. Company name and its market value. Sunk costs and mental accounting. Evolutionary explanations for behavioral effects. Evidence from behavioral game theory. Systematic approach to using behavioral factors in corporate decision-making. 1. Baker, Malcolm and Wurgler, Jeffrey, 2002, Market Timing and Capital Structure, Journal of Finance, 57, 1-32. 2. Shefrin, Hersh, 2000, Biased Reaction to Earnings Announcements, Chapter 8 in Beyond Greed and Fear: Understanding Behavioral Finance and the Psychology of Investing, Harvard Business School Press. 3. Heaton, J. B., 2002, Managerial Optimism and Corporate Finance, Financial Management, 31, 33-45. 4. Shefrin, Hersh, 2000, Beyond Greed and Fear, Harvard Business School Press. 5. Gervalis, S, Heaton, J. B., Odean, T., 2002, The Positive Role of Overconfidence and Optimism in Investment Policy, Working paper. 6. Rau P.R., Patel, A., Osobov, I., Khorana, A., Cooper, M.J., 2001, The Game of the Name: Value Changes Accompanying Dot.com Additions and Deletions.

Distribution of hours #

Topic

1. 2.

Rationality Heuristics, biases and beyond

Total Contact hours Self hours Lectures Seminars study 6 12

2 4

4 8

9

BEHAVIORAL ECONOMICS AND FINANCE #

Topic

3. 4.

Alternative decision theories Memory, cognition and their economic implications 5. Game theory models I: Evolutionary games 6. Game theory models II: Psychological games 7. Applied behavioral models in economics 8. Behavioral factors and financial markets 9. External factors and investor behavior 10. Behavioral corporate finance Total:

Total Contact hours Self hours Lectures Seminars study 12 12

4 4

8 8

12

4

8

12

4

8

12

4

8

12

4

8

12

4

8

6

2

4

108

36

0

72