Behavioral Finance on the CMT Exam
Behavioral finance carries 15% weight on CMT Level 2 and is increasingly tested on Level 3. It bridges technical analysis with psychology — explaining why patterns repeat.
See the CMT exam guide 2026 for the full Level 2 breakdown.
Key Cognitive Biases
Overconfidence Bias
Investors overestimate their ability to predict market movements, leading to:
- Excessive trading
- Under-diversification
- Ignoring risk management principles
Anchoring
Relying too heavily on the first piece of information (the "anchor"). Example: refusing to sell because the stock was "worth" its ATH.
Confirmation Bias
Seeking information that confirms existing beliefs while ignoring contradictory data — dangerous for chart pattern analysis.
Loss Aversion
Kahneman & Tversky found the pain of losses is ~2× more powerful than the pleasure of equivalent gains.
Disposition Effect
Investors sell winners too early and hold losers too long — the reverse of optimal risk management.
Prospect Theory
The most important behavioral model for the CMT exam:
- People are risk-averse for gains = they lock in profits early
- People are risk-seeking for losses = they gamble to avoid realizing losses
- The value function is S-shaped: concave for gains, convex for losses
Herd Behavior
Markets exhibit herding when investors follow the crowd:
- Drives momentum effects (useful for moving average strategies)
- Creates bubbles and panic selling
- Measured through sentiment indicators
Market Anomalies
| Anomaly | Description | CMT Relevance |
|---|---|---|
| January Effect | Stocks tend to rise in January | Calendar analysis |
| Momentum | Winners continue winning | Trend-following systems |
| Mean Reversion | Extreme performers revert | Oscillator signals |
| Value Effect | Cheap stocks outperform | Fundamental overlay |
Practice behavioral finance questions in our test bank. See the full guide.
Prospect Theory — Value Function (Kahneman & Tversky)
Losses loom larger than equivalent gains — the curve is steeper for losses
Prevalence of Cognitive Biases Among Investors
Survey of 2,000 investment professionals — % affected by each bias