Decision-Making Under Risk & Uncertainty

Risk vs Uncertainty

Risk: Known probabilities (coin flip = 50/50)
Uncertainty: Unknown probabilities (will new product succeed?)

Traditional finance conflates these. Behavioral finance recognizes people treat them differently.

Decision Under Risk

When probabilities are known, Expected Utility Theory predicts choices:

Example: Choose between A (certain ₹100) or B (50% ₹200, 50% ₹0)

• EV(A) = ₹100
• EV(B) = ₹100
• Risk-averse: Choose A
• Risk-neutral: Indifferent
• Risk-seeking: Choose B

Behavioral Deviations

Certainty Effect: Overweight certainty vs high probability

• Prefer certain ₹30 over 80% chance of ₹45 (even though EV is ₹36)
• Prospect Theory explains this via probability weighting

Possibility Effect: Overweight small probabilities

• Lottery tickets (0.0001% chance of ₹10 crore feels worth ₹100)
• Insurance (overweight small disaster probability)

Decision Under Uncertainty (Ambiguity)

Ellsberg Paradox: People avoid ambiguous gambles even with same expected value.

Urn A: 50 red, 50 black balls (known)
Urn B: 100 balls, unknown red/black ratio

Most people prefer betting on Urn A even though both have EV of 50% win!

Ambiguity Aversion: Prefer known risks over unknown risks.

Investment Implications

Home Bias: Domestic stocks feel less ambiguous (more information)
Familiarity Bias: Invest in employer stock (feels less uncertain)
New Market Aversion: Avoid emerging markets despite higher returns (ambiguity)

Cost: Missing diversification, lower returns

Key Takeaways

• Risk: Known probabilities; Uncertainty: Unknown probabilities
• Certainty effect: Overweight sure outcomes
• Possibility effect: Overweight tiny probabilities
• Ambiguity aversion: Prefer known risks over unknown
• Investment impact: Home bias, familiarity bias, missed opportunities

Loading quiz…