Behavioral Finance

Overview

When to Use

• Explaining market anomalies (momentum, bubbles, crashes) through investor psychology
• Diagnosing decision biases in portfolio management
• Designing de-biasing strategies for investment processes
• Evaluating why "rational" strategies underperform expectations

When NOT to Use

• As a catch-all explanation for any price movement — biases must be identified specifically
• When standard rational models already explain the phenomenon adequately
• For normative portfolio construction without considering limits to arbitrage

Assumptions

IRON LAW: Investors are NOT rational — systematic biases create
predictable pricing errors. These errors persist because arbitrage
is limited (costs, risk, horizon constraints).

1. Cognitive biases are systematic, not random — they create directional price effects
2. Limits to arbitrage prevent rational traders from fully correcting mispricings
3. Reference points and framing significantly affect decisions

Methodology

Step 1 — Identify the Behavioral Anomaly

Step 2 — Map to Specific Biases

Step 3 — Assess Limits to Arbitrage

• Fundamental risk, noise trader risk, implementation costs
• Short-selling constraints, model risk, horizon mismatch

Step 4 — Propose De-biasing or Exploitation Strategy

• De-bias: pre-commitment rules, systematic rebalancing, checklists
• Exploit: contrarian strategies, but only if limits to arbitrage are manageable

Output Format

## Behavioral Finance Analysis: [Context]

### Observed Anomaly
- [Description of pricing pattern or decision error]

### Bias Diagnosis
| Bias | Evidence | Severity |
|------|----------|----------|
| [bias name] | [specific observation] | [High/Medium/Low] |

### Limits to Arbitrage
- [Why rational traders cannot fully correct this]

### Recommendations
1. [De-biasing strategy or trading implication]
2. [Process improvement]

Gotchas

• Behavioral biases explain patterns but rarely predict timing — "the market can stay irrational longer than you can stay solvent"
• Not all anomalies are behavioral; some reflect rational risk compensation
• Prospect theory is descriptive, not prescriptive — it explains behavior, not optimal decisions
• Biases interact; loss aversion plus overconfidence can produce contradictory predictions
• Publication bias may inflate the number of "real" behavioral anomalies
• Institutional investors exhibit different biases than retail investors

References

• Kahneman, D. & Tversky, A. (1979). Prospect theory: an analysis of decision under risk. Econometrica, 47(2), 263-292.
• Shleifer, A. & Vishny, R. (1997). The limits of arbitrage. Journal of Finance, 52(1), 35-55.
• Barberis, N. & Thaler, R. (2003). A survey of behavioral finance. Handbook of the Economics of Finance, 1, 1053-1128.