Behavioural Finance — Module 3: Heuristics, Biases & Bounded Rationality
Course Code: BBA5CJ302 • Lecture Notes • Complete Study Material
1. Ellsberg's Paradoxes and Ambiguity Aversion
Classical probability theory assumes that individuals evaluate uncertainty using well-defined subjective probabilities. Daniel Ellsberg (1961) challenged this framework by demonstrating that human decision-makers draw a sharp cognitive distinction between Risk (known probability distributions) and Ambiguity (unknown or unquantifiable probability distributions).
The Ellsberg Paradox Experiment
Consider an urn containing 30 Red balls and 60 Black and Yellow balls in an unknown proportion:
| Gamble Option | Gamble Details | Observed Human Preference | Theoretical Violation |
|---|---|---|---|
| Choice 1 (Gamble A vs B) | A: Win $100 on Red (Known 1/3) B: Win $100 on Black (Unknown 0 to 2/3) | Majority choose Gamble A (Known Probability). | Implies subjective belief that P(Red) > P(Black). |
| Choice 2 (Gamble C vs D) | C: Win $100 on Red or Yellow D: Win $100 on Black or Yellow (Known 2/3) | Majority choose Gamble D (Known Probability). | Implies subjective belief that P(Black) > P(Red), directly contradicting Choice 1! |
Ambiguity Aversion in Financial Markets
Investors demand a significantly higher risk premium to invest in foreign assets, new technology stocks, or complex derivatives where probability distributions are ambiguous, explaining home-country bias in international portfolio management.
2 & 3. Perspectives on Rationality, Time Horizons, and Group Dynamics
Classical vs Evolutionary Perspectives on Rationality
Classical Economic Rationality
Defines rationality as mathematical consistency: optimizing a well-defined utility function subject to resource constraints using all available information without error.
Evolutionary Psychology Rationality
Views human cognitive heuristics as adaptive survival mechanisms designed by natural selection for ancestral hunter-gatherer environments, not complex modern stock markets.
Time Horizons & Group Rationality
- Time-Horizon Dependence: Decisions that appear irrational over short time horizons (e.g., hoarding cash during panic) may represent optimal survival strategies over extended generational horizons.
- Individual vs. Group Rationality (Herding): An action that is individually rational (e.g., exiting a bank during a panic run to secure cash) generates catastrophic group irrationality (bank collapse).
- Groupthink in Investment Committees: Collective decision-making bodies often suffer from pressure for consensus, suppression of dissenting analysis, and extreme risk-shifting.
4. Herbert Simon and Bounded Rationality
Nobel Laureate Herbert Simon formulated the concept of Bounded Rationality, acknowledging that human beings lack the cognitive capacity, perfect information, and computational time required to calculate absolute mathematical optima.
Satisficing vs. Optimizing
Instead of searching endlessly for the single optimal solution, human decision-makers engage in Satisficing—searching through choices until they find an alternative that meets a pre-determined threshold of adequacy (“good enough”).
| Decision Axis | Classical Optimization (Homo Economicus) | Bounded Rationality / Satisficing (Real Humans) |
|---|---|---|
| Information Processing | Infinite computational capacity; evaluates all choices simultaneously. | Limited cognitive capacity; processes information sequentially using mental shortcuts. |
| Search Termination Rule | Stops search only when absolute global mathematical maximum is reached. | Stops search as soon as an alternative satisfies baseline aspiration levels. |
| Real-World Application | Unrealistic mathematical ideal. | Accurate descriptive model of real human decision behavior. |
5 & 6. Cognitive Heuristics, Biases, Bubbles & Sentiment
To navigate a complex world under bounded rationality, the human brain relies on Heuristics—mental shortcuts or rules-of-thumb that speed up decision-making but introduce systematic cognitive errors.
Core Cognitive Heuristics & Biases
1. Availability Heuristic
Assessing the likelihood of an event based on how easily recent, vivid, or dramatic examples come to mind (e.g., overestimating market crash risks immediately after a crash).
2. Representativeness Heuristic
Judging the probability of an item belonging to a category based on superficial similarity, leading to sample size neglect and over-extrapolating short track records.
3. Anchoring and Adjustment
Fixating heavily on an initial arbitrary piece of information (e.g., historical 52-week high stock price) and making insufficient adjustments when evaluating current worth.
4. Confirmation Bias & Limited Attention
Selectively seeking out data that confirms pre-existing investment theses while actively ignoring or discounting contradictory evidence.
5. Overconfidence & Hubris
Investors overestimating the accuracy of their knowledge and predictive ability, leading to excessive trading volume and reduced net returns.
6. Self-Attribution Bias
Attributing successful investment outcomes to personal skill and intellect while blaming investment losses on bad luck or external manipulation.
Non-Traditional Preferences, Bubbles & Sentiment
- Hyperbolic Discounting: Human preference for immediate gratification over long-term rewards, leading to time-inconsistent financial savings behavior.
- Speculative Asset Bubbles: Multi-stage market phenomena driven by narrative stories, media amplification, herding, and credit expansion (e.g., Tulip Mania 1637, Dot-Com Bubble 2000, 2008 Housing Bubble).
- Baker-Wurgler Sentiment Index: Measuring systematic investor sentiment using market indicators including closed-end fund discounts, IPO first-day returns, equity issuance share, and dividend premium.
Download Module 3 Notes (PDF)
Calicut University • FYUGP 2024 Syllabus
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