1 / 24

Exploring Choices Amid Uncertainty in Behavioral Economics

Delve into decision-making under uncertain alternatives, lotteries, and paradoxes in economics and behavioral finance. Explore expected value and utility. Discover the Allais Paradox and how to make rational choices.

barnettj
Download Presentation

Exploring Choices Amid Uncertainty in Behavioral Economics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Behavioral Finance Economics 437

  2. Choices When Alternatives are Uncertain • Lotteries • Choices Among Lotteries • Maximize Expected Value • Maximize Expected Utility • Allais Paradox

  3. What happens with uncertainty • Suppose you know all the relevant probabilities • Which do you prefer? • 50 % chance of $ 100 or 50 % chance of $ 200 • 25 % chance of $ 800 or 75 % chance of zero

  4. Expected Value Calculates the Average Value: • 50 % chance of $ 100 or 50 % chance of $ 200 • Expected Value = ½ times $100 plus ½ times $200, which equals $ 150 • 25 % chance of $ 800 or 75 % chance of zero • Expected Value = ¼ times $ 800, which equals $ 200 • These two have the same “expected value.” Are you indifferent between them?

  5. How to decide which to choose? • Would you simply pick the highest “expected value,” regardless of how low the probability of success might be, e.g. • 1/10th chance of $ 2,000 or 9/10th chance of zero has an “expected value” of $ 200. • Would you pick this over the two previous choices, both of which have an “expected value” of $ 200? • If you are still indifferent between the three choices, then you probably order uncertain choices by their expected value.

  6. Bernoulli Paradox • Suppose you have a chance to play the following game: • You flip a coin. If head results you receive $ 2 • Expected value is $ 1 dollar • Suppose you get to continue flipping until your first head flip and that you receive 2N dollars if that first heads occurs on the Nth flip. • Exp Value of the entire game is: • $ 1 plus ¼($4) plus 1/8($ 8) plus ………. • Infinity, in other words • This suggest you would pay an arbitrarily large amount of money to play this flipping game • Would you?

  7. So, how do you resolve the Bernouilli Paradox?

  8. This lead folks to reconsider using “expected value” to order uncertain prospects • Maybe those high payoffs with low probabilities are not so valuable • This lead to the concept of a lottery and how to order different lotteries

  9. Lotteries • A lottery has two things: • A set of (dollar) outcomes: X1, X2, X3,…..XN • A set of probabilities: p1, p2, p3,…..pN • X1 with p1 • X2 with p2 • Etc. • p’s are all positive and sum to one (that’s required for the p’s to be probabilities)

  10. For any lottery • We can define “expected value” • p1X1 + p2X2 + p3X3 +……..pNXN • But “Bernoulli paradox” is a big, big weakness of using expected value to order lotteries • So, how do we order lotteries?

  11. “Reasonableness” • Four “reasonable” axioms: • Completeness: for every A and B either A ≥ B or B ≥ A (≥ means “at least as good as” • Transitivity: for every A, B,C with A ≥ B and B ≥ C then A ≥ C • Independence: let t be a number between 0 and 1; if A ≥ B, then for any C,: • t A + (1- t) C ≥ t B + (1- t) C • Continuity: for any A,B,C where A ≥ B ≥ C: there is some p between 0 and 1 such that: • B ≥ p A + (1 – p) C

  12. Conclusion • If those four axioms are satisfied, there is a utility function that will order “lotteries” • Known as “Expected Utility”

  13. For any two lotteries, calculate Expected Utility II • p U(X) + (1 – p) U(Y) • q U(S) + (1 – q) U(T) • U(X) is the utility of X when X is known for certain; similar with U(Y), U(S), U(T)

  14. Expected Utility Simplified • Image that you have a utility function on all certain prospects • If only money is considered, then: Utility Money

  15. Assume that Utility Function • Has positive marginal utility • Diminishing marginal utility (which means “risk aversion”)

  16. So, begin with a utility function that values certain dollars • Then consider a lottery • Calculate Average Utilities Lotteries involving $ 1 and $ 2 $ 1 $ 2

  17. If th

  18. Now, try this: • Choice of lotteries • Lottery C • 89 % chance of zero • 11 % chance of $ 1 million • Or, Lottery D: • 90 % chance of zero • 10 % chance of $ 5 million • Which would you prefer? C or D

  19. Back to A and B • Choice of lotteries • Lottery A: sure $ 1 million • Or, Lottery B: • 89 % chance of $ 1 million • 1 % chance of zero • 10 % chance of $ 5 million • If you prefer B to A, then • .89 (U ($ 1M)) + .10 (U($ 5M)) > U($ 1 M) • Or .10 *U($ 5M) > .11*U($ 1 M)

  20. And for C and D • Choice of lotteries • Lottery C • 89 % chance of zero • 11 % chance of $ 1 million • Or, Lottery D: • 90 % chance of zero • 10 % chance of $ 5 million • If you prefer C to D: • Then .10*U($ 5 M) < .11*U($ 1M)

  21. Allais Paradox • Choice of lotteries • Lottery A: sure $ 1 million • Or, Lottery B: • 89 % chance of $ 1 million • 1 % chance of zero • 10 % chance of $ 5 million • Which would you prefer? A or B

  22. Now, try this: • Choice of lotteries • Lottery C • 89 % chance of zero • 11 % chance of $ 1 million • Or, Lottery D: • 90 % chance of zero • 10 % chance of $ 5 million • Which would you prefer? C or D

  23. So, if you prefer • B to A and C to D • It must be the case that: • .10 *U($ 5M) > .11*U($ 1 M) • And • .10*U($ 5 M) < .11*U($ 1M)

  24. The End

More Related