Topics in Behavioral Finance (I)
[Pages:27]Topics in Behavioral Finance (I)
Mei Wang Brownbag Lunch Seminar, March 3, 2008
1
About myself...
? Bachelor in Computer Science, Xiamen University, China ? PhD in Decision Science, Carnegie Mellon University,
Pittsburgh, USA
Assistant professor of Finance and Financial Markets.
Leader of University Priority Research Program "Finance and Financial Markets": subproject "Behavioral Finance"
Research:
?Behavioral Finance ?Decision Theory ?Cultural Finance
Teaching:
?Behavioral Finance ? Banking: Structured products ?Behavioral Decision Theory
Mei Wang,Topics in Behavioral Finance
2
Brownbag Lunch Seminar, March 3rd, 2008
A couple of words about Carnegie Mellon University
Department of Social and Decision Science:
? Behavioral Economics ? Experimental economics ? Policy analysis ? Active in interdisciplinary research ? Herbert Simon: Bounded Rationality
Mei Wang,Topics in Behavioral Finance
Brownbag Lunch Seminar, March 3rd, 2008
What is behavioral finance?
Behavioral Finance = "open-minded Finance"
"Sometimes, in order to find the solution to an empirical puzzle, it is necessary to entertain the possibility that some of the agents in the economy behave less than fully rationally some of the time. Any financial economist willing to consider this possibility seriously is ready to take a try at behavioral finance." (Thaler, 1993)
Mei Wang,Topics in Behavioral Finance
4
Brownbag Lunch Seminar, March 3rd, 2008
Key issues in BF
Empirical work: Phenomena inconsistent
with fully-rational framework
Theoretical work: What if we relax rational assumptions?
Does further empirical evidence supports the improved model?
Mei Wang,Topics in Behavioral Finance
5
Brownbag Lunch Seminar, March 3rd, 2008
A brief overview of my research
1. Prospect Theory
? Empirical tests ? Theoretical improvements
2. Risk Perception (in financial investments) 3. Cross-cultural comparison
? Risk-attitudes ? Financial data (e.g. equity premium)
Mei Wang,Topics in Behavioral Finance
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Brownbag Lunch Seminar, March 3rd, 2008
1. Prospect Theory
Descriptive extension of Expected Utility Theory. Main ideas:
ADVANCES IN PROSPECT THEORY
313
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Mei Wang,Topics in Behavioral Finance
and
is overweighted with a Figures 4a and 4b are in general agreement with the main empirical generalizations that have emerged from the studies of the triangle diagram; see Camerer (1992), and Camerer and Ho (1991) for reviews. First, departures from linearity, which violate expected utility theory, are most pronounced near the edges of the triangle. Second, the nonlinear function w. indifference curves exhibit both fanning in and fanning out. Third, the curves are concave in the upper part of the triangle and convex in the lower right. Finally, the indifference curves for nonpositive prospects resemble the curves for nonnegative prospects reflected around the 45? line, which represents risk neutrality. For example, a sure gain of $100 is Brownbag Lunch Seminar, March 3rd, 2008 equally as attractive as a 71% chance to win $200 or nothing (see figure 4a), and a sure 7 loss of $100 is equally as aversive as a 64% chance to lose $200 or nothing (see figure 4b). The approximate reflection of the curves is of special interest because it distinguishes the present theory from the standard rank-dependent model in which the two sets of curves are essentially the same.
Empirical studies on PT
Comparison of Chinese and American
? Experiments (with Fischbeck, J. of Risk Research, 2008)
? Field data (with Fischbeck, J. of Risk & Uncertainty, 2004)
Predictive power of PT
? Disposition effect (with Martin Vlcek, working paper)
Mei Wang,Topics in Behavioral Finance
8
Brownbag Lunch Seminar, March 3rd, 2008
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