040212 Decisions under Uncertainty
 

• Introduction
• Expected Utility Theory (until slide II.16 (p.8))
  • Introductory examples, Bernoulli principle
  • Lotteries and their graphical representation

Topics:

• Expected Utility Theory (until slide II.25 (p.11))
  • Axioms underlying Expected Utility Theory
  • Expected Utility Theorem

• Expected Utility Theory (until slide II.39 (p.15))
  • Expected Utility Theorem (cont)
  • Geometric representation in the state space
  • Demand for insurance

• Demand for insurance: Example
• Risk aversion
  • definition and characterization
  • certainty equivalent and risk premium
  • measuring risk aversion (absolute risk aversion)
  (until slide III.13 (p.22))

• Taylor Polynomials
• Animation
• Taylor Series

• Risk aversion (until slide III.34 (p.29))
  • measuring risk aversion (relative risk aversion)
  • some commonly used utility functions

• Risk aversion: Example
• First order stochastic dominance (until slide IV.15)

• Increases in risk (until slide IV.35):
  • Mean preserving spread
  • Second order stochastic dominance

• Increases in risk
  • Second order stochastic dominance and risk preferences
  • Characterizations
• Mean-variance approach (until slide V.12)
  • Distribution of returns (see additional slides in Moodle)

• Mean-variance approach
  • Distribution of returns
  • Problems and limitation of the mean-variance approach
• Role of information in decision-making under risk (until slide VIII.12)

• Role of information in decision-making under risk (until slide VIII.29)
  • General model
  • Updating of beliefs
    Bayes' Theorem
• Empirical facts (until slide VI.14)

• Empirical facts
• Prospect Theory: 4 ideas (until slide VII.38)

• Prospect Theory and Cumulative Prospect Theory