lesson 4- uncertainty and behavorial econ

Question 1

uncertainty

Answer 1

The state of not knowing what will happen in the future; multiple possible outcomes. Example: Investing in the stock market.

Question 2

risk

Answer 2

The possibility of experiencing a loss or negative outcome. Example: The risk of losing money in a stock market investment.

Question 3

probability

Answer 3

The likelihood of a particular outcome occurring, expressed as a number between 0 and 1 (or as a percentage).

Question 4

Expected Value (EV)

Answer 4

The average outcome you expect from a decision, considering the probabilities of different outcomes.
Formula: E(X) = Pr₁X₁ + Pr₂X₂ (two outcomes) or
E(X) = Pr₁X₁ + Pr₂X₂ + … + PrₙXₙ (n outcomes), where Prᵢ is the probability of outcome Xᵢ.

Example: A lottery with a 50% chance of winning $10 and a 50% chance of winning $20 has an EV of $15.

Question 5

Risk Premium.

Answer 5

The amount of money a risk-averse person would pay to avoid a risky situation.

Formula: Risk premium = Expected money value – Certainty equivalent.

Question 6

Certainty Equivalent.

Answer 6

The certain amount of money that an individual considers equally desirable as a risky asset.

Question 7

Risk Aversion.

Answer 7

Preference for a certain outcome over a risky one with the same expected value. Visual aid: Draw a concave utility function.
- risk averse person had diminishing MU
- most common attitude towards risk
- utility of certain income > E.U of uncertain income

Question 8

Risk Neutrality

Answer 8

Indifference between a certain outcome and a risky one with the same expected value. Visual aid: Draw a linear utility function.
- slope doesnt change
- MU is constant for risk neutral person

Question 9

Risk Loving

Answer 9

Preference for a risky outcome over a certain one, even if the risky outcome has a lower expected value. Visual aid: Draw a convex utility function.
- MU of money is increasing

Question 10

Standard Deviation (SD)

Answer 10

A measure of the variability or dispersion of a set of values around their mean (expected value). Note: A higher SD indicates higher risk.

Formula for Standard Deviation (Simple Example with two equal probability outcomes)
√[0.5 * (X₁ - EV)² + 0.5 * (X₂ - EV)²] where X1 and X2 are the outcomes and EV is the expected value.

Question 11

Expected Utility (EU)

Answer 11

The average utility you expect from a decision, considering the probabilities of different outcomes and the utility associated with each outcome. (SUM OF UTILITIES ASSOCIATED WITH ALL POSSIBLE OUTCOMES)

Formula: EU(X) = Σᵢ₌₁ᴺ U(Xᵢ)Prᵢ.

Note: Utility is not necessarily linear with monetary value.
IN EV -> TAKE WEIGHTED AVERAGE OF VALUES
IN EU -> TAKE WEIGHTED AVERAGE OF UTILITY FUNCTION

Question 12

REDUCING RISK - diversification and insurance

Answer 12

Diversification- Spreading investments across different assets to reduce overall risk. Example: Investing in stocks, bonds, and real estate.

Insurance- A mechanism to transfer risk from an individual to an insurance company. Example: Health insurance, car insurance.

Law of Large Numbers.- The average outcome of many similar events tends to approach the expected value as the number of events increases.
it enables insurance companies to provide insurance for which the premiums paid equals the expected value of losses being insured against.

Question 13

A. Behavioral Economics

Homo Economicus

Answer 13

The traditional economic model that assumes perfectly rational individuals who maximize utility. Note: Behavioral economics challenges this assumption.
- The field of economics that studies how psychological factors influence economic decisions. Note: It acknowledges that people don’t always behave rationally.

Question 14

Subjective Probability Weighting

Answer 14

The tendency to overestimate or underestimate the probabilities of certain outcomes, based on personal perception and bias.

Question 15

Certainty Effect.

Answer 15

A reduction in winning chance is always a displeasure. But, we feel, a reduction
results in larger psychological effect when it is a reduction from certainty than
from uncertainty.
reduction of prob frm 100 to 90 is worse than reduction frm 90 to 80.

Question 16

reference point

Answer 16

a benchmark against which we compare our options, significantly influencing our decisions

Question 17

status quo bias

Answer 17

also called endowment effect - The tendency to value something more highly once we own it. Example: The mug experiment.

• emotional bias
• The preference for maintaining the current state of affairs. Example: Keeping an old phone even if there are better options available.

Question 18

“Opt-Out” vs. “Opt-In” Policies.

Answer 18

Explain how default options influence choices, leading to higher participation rates in “opt-out” systems (organ donation example).

Opt-in systems: Individuals must actively choose to become organ donors. This requires an affirmative action, which many people may not take, even if they support organ donation in principle. Inertia, the tendency to do nothing, is at play.

Opt-out systems: Individuals are automatically enrolled as organ donors unless they explicitly choose to opt out. This leverages the status quo bias; the default is to donate, and many people will remain in that default state due to the effort involved in opting out. Even if they initially weren’t strongly committed to organ donation, the ease of remaining in the default state increases participation.

Question 19

Loss Aversion

Answer 19

The pain from a loss is felt more strongly than the pleasure from an equivalent gain. The pain from a loss and the
pleasure from the same size of
gain is not symmetric.

Visual Aid: Illustrate with a graph showing steeper curve for losses, than for gains

Question 20

Framing Effects.

Answer 20

How the presentation of information influences decisions.
relying on the context in which a choice is described when making a decision

Example: Skin cream packaging example.

Question 21

Anchoring Effects.

Answer 21

The tendency to rely too heavily on the first piece of information received (the “anchor”) when making decisions.

Example: Charity donation example.
- The price of a painting sold at an art auction and the experts’ pre-sale
valuations are anchored on the price at which the painting previously
sold at auction.

Question 22

Nudging.

Answer 22

Gently guiding people toward making better decisions without restricting their choices.
Behavioral findings of human nature
and psychology can manipulate
people’s decisions.

Example: The “Save More Tomorrow” plan for retirement savings, SP Group energy usage prompts.

Question 23

Formulas

Answer 23

Expected Value (with two possible outcomes): E(X) = Pr₁X₁ + Pr₂X₂

Expected Value (with n possible outcomes): E(X) = Pr₁X₁ + Pr₂X₂ + … + PrₙXₙ

Expected Utility: EU(X) = Σᵢ₌₁ᴺ U(Xᵢ)Prᵢ (where the summation is from i=1 to N)

risk premium = expected value - certainty equivalent