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70-386 Behavioral Decision Making

70-386 Behavioral Decision Making. Lecture 13: Behavioral Finance. Administrative. Quiz results this afternoon I’ll bring to class on Sunday or feel free to stop by my office Presentations

morgan-vazquez
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70-386 Behavioral Decision Making

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  1. 70-386 Behavioral Decision Making Lecture 13: Behavioral Finance

  2. Administrative • Quiz results this afternoon • I’ll bring to class on Sunday or feel free to stop by my office • Presentations • Email me to find a time to meet. Propose some times when you are all free (don’t just give me one option) • Group 4 next Tuesday • Last Quiz next Thursday • Behavioral Game Theory readings • JMDM chp 8 • Scanned readings • Maybe JMDM chp 10/11

  3. Behavioral Finance • Over the past few weeks we’ve already discussed several examples and applications Finance. Such as? • Disposition effect: reluctance to sell assets trading at a loss relative to purchase price • US: tax incentives to sell! • Why? What biases might account for this behavior? • Excessive trading • Most rational models predict less trading than is observed. Why? • Overconfidence • Evidence that men are more overconfident than women  also evidence that men trade excessively more than women • Different accounts (retirement vs upside account, etc) are optimized separately • Different risk preferences.

  4. Behavioral Finance: more biases • Home bias • Investments in markets across the world should not depend on the home country of the investor • Should depend on risk/return • Portfolio construction and hedging internationally • Percentage of domestic equities in US, Japanese, and UK portfolios was 94%, 98% and 82% respectively • Within country people tend to invest in companies from their region • Why? • Behavioral Econ: Ambiguity aversion – local stocks are more familiar • Rational: Information search easier

  5. Ambiguity Aversion • What is ambiguity? • When the probability isn’t given… • This bias is difficult for economics since ambiguity doesn’t really exist for a decision theorist. All uncertainty is embedded in a probability measure. • Bayesian decision theory says that a beliefs are probabilities. So any uncertainty can be represented by a subjective belief. • Great in theory. In practice, eh… (full disclosure: I’m very much a Bayesian, from a normative point of view)

  6. Back to Gambling • Don’t do it. • Consider the highly uncertain investment opportunity: • Your benevolent friend has an urn with three kinds of balls inside of it: red, black, and yellow. • The urn contains 90 balls, 30 of which are red. You don’t know how many of the remaining balls are black (or yellow). • You’re offered investment (1) or (2), which do you choose? • $100 if a randomly drawn ball is red • $100 if a randomly drawn ball is black

  7. Back to Gambling • Highly uncertain investment opportunity #2 • Your benevolent friend has an urn with three kinds of balls inside of it: red, black, and yellow. • The urn contains 90 balls, 30 of which are red. You don’t know how many of the remaining balls are black (or yellow). • You’re offered investment (3) or (4), which do you choose? • $100 if a randomly drawn ball is yellow or red • $100 if a randomly drawn ball is yellow or black

  8. Ambiguity • Most people prefer (1) to (2) and prefer (4) to (3) • (1) to (2) because the probability of red is well specified. • (4) to (3) because they know that black or yellow is 2/3’s likely • But… that’s a problem. Violates the “sure thing principle”

  9. Behavioral Finance: more biases • Naïve Diversification • Most people know that a portfolio means diversification • They diversify but naïvely: 1/n of the money to the n options • For example: 50%-50% between stocks and bonds • Experiment: • Group 1: stock fund and bond fund • Group 2: stock fund and balanced fund • Group 3: bond fund and balanced fund • Which group would you think has the highest allocation of equities? • Percentage of stocks in Groups 1-3: 54%, 73%, and 35%.

  10. Equity Premium Puzzle • Given people’s stated risk preferences and historical returns, why so few stocks being held? • Case 6.1 on Mental Accounting handout. • At some level, still a puzzle. • Depends on who you ask… some say no puzzle, some say puzzle but resolved, some say still a puzzle.

  11. Excessive M&A activity • When company A acquires company B, we often see B’s stock price go up and A’s go down. Why? • One explanation is that markets are correcting for irrational, i.e, biased, management • If management is overconfident then they might overestimate the degree of synergy between the two companies, • “hubris hypothesis” • Therefore the M&A isn’t as good of a deal for A. • Prediction: M&A activity but net effect on stock prices should be closer to zero. • This is an example of rational markets correcting irrational, biased, managerial behavior. The other examples are often the verse.

  12. Strategic Interaction

  13. Learning by doing • We’ll really cover a bit more Game Theory next week but start with some basic experiments to get an idea. • Game U: two players, 10 tokens • Player 1: proposes an allocation of the 10 tokens to herself and player 2 • Player 2: either agrees to 1’s proposal, or rejects. If rejection, then no one gets anything.

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