| IQ (Intelligence Quotient) | EQ (Emotional Quotient) | |
|---|---|---|
| What it measures | Cognitive/intellectual ability: logic, reasoning, problem-solving, mathematics | Ability to identify, understand, manage, and use emotions — in oneself and others |
| Stability | Relatively fixed over time | Can be developed and improved |
| Components | Verbal, spatial, numerical reasoning | Self-awareness, self-regulation, motivation, empathy, social skills |
| Role in investing | Helps with quantitative analysis and information processing | Helps manage fear, greed, and emotional biases in decision-making |
Key distinction: IQ measures what you know and how fast you process it; EQ measures how well you recognise and regulate emotions to make effective decisions.
| Mood | Emotion | |
|---|---|---|
| Intensity | Low to moderate | High (acute) |
| Duration | Prolonged (hours to days) | Brief (seconds to minutes) |
| Trigger | Diffuse — no specific identifiable cause | Specific event or stimulus |
| Object/Direction | Non-directed; pervasive background feeling | Directed at a specific object or situation |
| Example | Feeling generally optimistic about the market | Fear when watching a stock fall 10% in a day |
Key distinction: Emotions are short, sharp, and event-specific; moods are long, diffuse, and background-level states. Both can distort financial decisions, but through different mechanisms.
Both are landmark neurological case studies that demonstrate the link between emotion and rational decision-making.
Phineas Gage (1848): - A railroad construction worker in Vermont whose frontal lobe was destroyed when a tamping iron passed through his skull in an explosion. - He physically survived, and his cognitive faculties (memory, language, IQ) were largely intact. - However: his personality transformed entirely — he became impulsive, unreliable, irreverent, and unable to make sound decisions or plan for the future. - Lesson: The prefrontal cortex, which integrates emotion and cognition, is essential for goal-directed rational behaviour. Emotion loss → decision impairment.
Elliot (studied by Damasio): - A patient who had a benign brain tumour removed from the prefrontal cortex. - Post-surgery: normal IQ, intact memory, normal language — but completely emotionally flat. - However: he became incapable of making decisions. He could spend hours debating where to have lunch, endlessly listing pros and cons without ever choosing. - Lesson: Emotions are necessary for decision-making, not merely disruptive add-ons. Without them, even trivial choices become intractable.
Combined lesson: Both cases support Damasio’s Somatic Marker Hypothesis — emotional signals (gut feelings encoded from past experience) are required to narrow down options and commit to a choice. Emotion and reason are neurologically integrated, not separate.
An emotion is not a single, monolithic experience — it is a complex, multi-component state. The six defining substances are:
| # | Component | Description | Example (Fear of a market crash) |
|---|---|---|---|
| 1 | Cognitive Appraisal | How you evaluate and interpret the triggering event | “This market drop signals a recession” |
| 2 | Subjective Feeling | The conscious, inner experience of the emotion | Feeling dread and unease |
| 3 | Physiological Response | Bodily changes — nervous system activation | Increased heart rate, sweating, tension |
| 4 | Action Tendency | The urge to behave in a certain way | Impulse to sell all holdings immediately |
| 5 | Expressive Behaviour | Observable external signals — facial, vocal, postural | Furrowed brow, rigid posture, terse speech |
| 6 | Emotional Regulation | Ability to manage, suppress, or modulate the emotion | Taking a breath, consulting a plan before selling |
Note: These six components are what allow researchers to define, measure, and distinguish between different emotions. Observables (components 3, 4, and 5) are particularly important for empirical research.
Position: Yes — EQ is equally, if not more, important.
Arguments in favour:
Emotion governs the execution of knowledge. An investor may understand valuation models perfectly (high IQ) but panic-sell at market lows because of fear. EQ determines whether knowledge is applied effectively under pressure.
The Elliot case demonstrates that intelligence without emotion leads to decision paralysis. In investing, indecision is as costly as bad decisions.
Bias management. Cognitive biases — loss aversion, overconfidence, herding — are emotionally rooted. High EQ helps an investor recognise when emotions are distorting their judgment and step back.
Market sentiment. Much of price movement is driven by crowd psychology. Investors with high EQ can read market sentiment and identify when fear or greed is mispricing assets.
Long-term discipline. Investment success (as evidenced by Buffett) depends heavily on temperament — staying rational when others are emotional. This is fundamentally an EQ skill.
Counter-argument to acknowledge: - Without technical knowledge, EQ alone is insufficient — you still need to understand what you are investing in.
Conclusion: The ideal investor combines both. IQ provides the tools; EQ determines whether those tools are used wisely.
Primary emotions likely felt: Happiness and Surprise (and possibly Fear).
| Component | Description |
|---|---|
| Cognitive Appraisal | “This is an extraordinary, life-changing, positive event” |
| Subjective Feeling | Elation, joy, a sense of great fortune |
| Physiological Response | Heart racing, warmth, energy surge, release of dopamine |
| Action Tendency | Urge to celebrate, tell loved ones, spend or invest |
| Expressive Behaviour | Broad smile (Duchenne smile — raised cheeks, crow’s feet), laughter, wide eyes |
| Emotional Regulation | Attempting to stay composed and not announce it publicly immediately |
| Component | Description |
|---|---|
| Cognitive Appraisal | “This was completely unexpected — I didn’t expect to win” |
| Subjective Feeling | Shock, disbelief, sudden alertness |
| Physiological Response | Startle response, sharp intake of breath, elevated adrenaline |
| Action Tendency | Freeze momentarily, then seek to verify the win is real |
| Expressive Behaviour | Raised eyebrows, open mouth, wide eyes |
| Emotional Regulation | Re-reading the ticket multiple times to confirm |
Note: Surprise is typically very brief and transitions quickly into happiness. Fear may also arise (fear of managing the money, fear of who to tell) — illustrating how one event can trigger multiple simultaneous emotions.
Position: No — emotion and reasoning are neurologically and functionally intertwined.
Arguments:
Somatic Marker Hypothesis (Damasio): Emotional signals encoded from past experiences act as background “markers” that unconsciously guide attention and narrow decision options before conscious reasoning begins. Reason and emotion operate in parallel, not in sequence.
Neurological evidence: Both Phineas Gage and Elliot demonstrate that damage to emotional-processing areas of the brain (prefrontal cortex) directly impairs rational decision-making — even when pure cognitive abilities remain intact.
Emotions as information: Fear signals risk, excitement signals opportunity, disgust signals ethical violation. These emotional signals inform the reasoning process with heuristic assessments that would take far longer to compute analytically.
Cognitive-emotional interaction: Research in cognitive appraisal theory shows that emotions are triggered by cognition (you have to evaluate a situation before you feel afraid) — meaning the two processes are fundamentally linked.
Concession: Emotions can distort reasoning — panic selling, greed-driven bubbles, sunk-cost thinking. But distortion does not mean separation; it means the interaction is imperfect.
Conclusion: Emotion and reasoning are best understood as complementary, interactive systems — not independent ones. The goal is not to separate them but to regulate emotions so they enhance rather than undermine reasoning.
Position: No — removing emotions would impair, not improve, decision-making.
Arguments:
The Elliot case (direct evidence): Elliot had no emotional response to anything after surgery. Despite a fully intact intellect, he was unable to make simple decisions. Emotionlessness is empirically associated with decision paralysis, not better decisions.
Computational intractability: Pure logic requires evaluating every possible option against all possible outcomes. Emotions function as efficient heuristic shortcuts — fear rapidly eliminates highly risky options; enthusiasm directs attention toward promising ones. Without these shortcuts, analysis becomes infinite regression.
Motivation and goal-setting: Emotions provide the motivational force behind goals. Without caring (an emotional state), there is no basis for preferring one outcome over another — rendering “better” decisions meaningless.
Social and market context: Financial markets are social systems. Reading other participants’ emotions, anticipating market sentiment, and recognising crowd psychology all require emotional intelligence.
However — acknowledge the risk: - Unregulated emotions (panic, greed, overconfidence) lead to documented errors: buying at market peaks, selling at troughs, the disposition effect. - The answer is not removing emotions, but regulating them — developing the self-awareness (EQ) to recognise when an emotional response is appropriate vs. distorting.
Conclusion: The optimal state is regulated emotion — not emotionlessness. Decisions without emotion lack direction; decisions dominated by unregulated emotion lack discipline.
As an equity fund manager selecting stocks, emotions can enhance (not just impair) the process in several ways:
Intuitive pattern recognition: Experienced managers develop an emotional “sense” for quality — a feeling of unease about a management team or excitement about a business model — that synthesises information faster than explicit analysis.
Risk sensing: Anxiety or discomfort when reviewing a highly leveraged position serves as a signal to investigate further, acting as an internal risk alert system.
Reading market sentiment: Emotions help gauge when markets are driven by fear or euphoria — enabling contrarian positions (buy when others are fearful, sell when others are greedy).
Commitment and discipline: Emotional conviction in a thesis helps maintain positions through short-term volatility rather than abandoning sound strategy due to noise.
Team dynamics: EQ helps manage portfolio team dynamics, client relationships, and stressful market conditions — all essential for sustainable performance.
Caveat: These benefits depend on emotional regulation. The same intuition that helps an experienced manager can lead a less self-aware investor into overconfidence, confirmation bias, or groupthink.
| Regret | Disappointment | |
|---|---|---|
| Cause | Bad outcome from a decision you made — you could have chosen differently | Bad outcome from chance or external events beyond your control |
| Agency | High — you feel personally responsible | Low — you feel unlucky, not responsible |
| Counterfactual | “If I had sold yesterday, I wouldn’t have lost” | “The market crashed; there was nothing I could do” |
| Investing example | Holding a stock that then collapses when you had the chance to sell | A stock falling due to an unexpected geopolitical event |
Key formula for understanding regret:
Regret arises when: Actual Outcome < Outcome of foregone alternative, AND the agent believes they could have chosen differently.
Behavioural consequence: Regret aversion causes investors to avoid making decisions that could lead to regret — particularly selling (crystallising losses). This contributes to the disposition effect.
Both arise from mental accounting and reference-point thinking, but operate in opposite positions relative to the reference point.
House Money Effect (Thaler & Johnson, 1990): - After a prior gain, investors become more risk-tolerant. - The gain creates a “cushion” — losses feel less painful because they are subtracted from winnings rather than principal. - Investors feel they are “playing with the house’s money,” so they take larger bets.
Reference point (RP): After a gain, the investor feels above their RP. Further losses are partially offset by prior gains → they take more risk.
Break-Even Effect: - After a prior loss, investors become more risk-seeking in an attempt to recover to the original reference point. - The emotional drive to “break even” leads to taking disproportionate risks. - This explains why gamblers keep betting after losses and traders “double down” on losing positions.
Reference point (RP): After a loss, the investor is below their RP. Prospect theory’s loss domain = risk-seeking → they take more risk to recover.
| House Money Effect | Break-Even Effect | |
|---|---|---|
| Prior position | After a gain | After a loss |
| Risk behaviour | More risk-tolerant | More risk-seeking |
| Psychological driver | Gains create a safety buffer | Desire to return to reference point |
| Market example | Investor gambles profits on speculative stocks | Trader doubles down on a losing position |
Affect (noun) — a psychological/finance term: - Refers to the emotional valence (positive or negative feeling tone) associated with a stimulus, object, or idea. - In finance: the affect heuristic is the tendency to evaluate investments based on overall good/bad feelings rather than analytical assessment. - Example: Investors may assign a lower risk rating to a company they like (e.g., an ethical company) and a higher risk rating to a company they find distasteful (e.g., tobacco), independent of actual risk measures.
Affect Heuristic: If you feel good about an asset → perceive high return, low risk. If you feel bad about it → perceive low return, high risk. (Return and risk ratings are inversely correlated in investor perception, contrary to finance theory.)
Affect (verb) — standard English: - To influence or have an impact on something. - Example: “Negative mood affects the price investors are willing to pay for risky assets.”
Key distinction: Affect (noun) is a state (an emotional feeling); affect (verb) is an action (to influence).
The emotional mechanism:
Pride → Sell Winners: - When a stock has risen above the purchase price, the investor is in a gain position. - Selling locks in the gain and generates a feeling of pride (“I made a good call”). - The anticipation of pride creates an incentive to sell too early — before the full upside is realised.
Regret Aversion → Hold Losers: - When a stock has fallen below the purchase price, selling makes the loss real and permanent. - This triggers regret — “I made a bad decision and am now realising it.” - To avoid this painful emotion, investors hold losers too long, hoping for a recovery that justifies the original decision. - As long as the position is open, the loss is “paper” — not yet confirmed.
The Bias Explained: The Disposition Effect
Disposition Effect (Shefrin & Statman, 1985): The systematic tendency to sell winners too early and hold losers too long.
This is directly contrary to rational investing: - Tax-optimal strategy → sell losers to realise tax losses - Momentum strategy → hold winners (they tend to keep rising) - The disposition effect does the opposite on both counts
Prospect Theory link:
Using the S-shaped value function:
Value
| / (Gains domain: concave → risk-averse → SELL)
| /
|------•--------- Reference Point (Purchase Price)
| \
| \ (Loss domain: convex → risk-seeking → HOLD)
|
OutcomeBeyond pride and regret, the disposition effect has several cognitive/behavioural explanations:
Short answer: No — this practice is not wise and creates significant risk.
Why it is problematic:
Conclusion: The practice conflates investment risk-taking with operational performance management. These should be kept separate. Risk limits in proprietary trading should be set independently of the firm’s P&L needs elsewhere.
At the individual level — yes, this is consistent with mood-influenced decision-making.
The sequence of events: - Sports loss → negative mood - Coffee queue → mood reinforced - Rain/umbrella → mood further reinforced - Falling stock → negative mood amplifies the negativity of the situation → sell
This is consistent with mood congruence theory — people in negative moods are more likely to interpret ambiguous information negatively (a falling stock is ambiguous: it could be a buying opportunity or a signal to exit). The negative mood tips the interpretation toward selling.
At the market level — this single case is NOT sufficient evidence.
For mood to move markets, the effect must be: - Systematic — many investors must experience the same mood simultaneously - Aggregate — individual trades must collectively shift price in the same direction
What research actually shows: - Hirshleifer & Shumway (2003): Sunshine in the city of a stock exchange is positively correlated with daily stock returns — a systematic mood effect. - Kamstra et al. (2003): Seasonal Affective Disorder (SAD) linked to lower risk-taking and lower returns in autumn/winter months. - Sporting events: Major national sports losses have been associated with short-term negative market returns in affected countries.
Conclusion: One individual selling one stock is noise, not a market movement. However, if a shared event (e.g., a major sporting event, widespread bad weather) affects many investors simultaneously, mood effects can aggregate into measurable market-level patterns. The individual example is illustrative but not sufficient evidence on its own.
Background: Post, van den Assem, Baltussen & Thaler (2008) analysed hundreds of episodes of Deal or No Deal to test prospect theory and expected utility theory in a real, high-stakes setting.
Definition: Decision-making is path-dependent when the sequence of outcomes (not just the final state) affects current choices — in violation of rational expected utility theory (which says only current wealth and current prospects should matter).
Findings from Deal or No Deal: - Contestants who had a bad path early (opened many high-value cases early, reducing expected value) became significantly more risk-seeking — consistent with the Break-Even Effect. - They rejected banker offers that, based on expected value, appeared fair — because they were trying to recover to an earlier reference point. - Contestants who had a good path (eliminated low-value cases, preserving high-value ones) became more risk-averse. - Consistent with the House Money Effect — they had already “won” and wanted to preserve it.
Key insight: Two contestants with identical current prospects (same cases remaining, same expected value) made different decisions based solely on how they got there. This directly violates rational theory and confirms prospect theory’s emphasis on reference points.
Path-dependence formula:
Under rational theory:
Decision = f(current wealth, current prospects)Under behavioural theory:
Decision = f(current wealth, current prospects, PATH to get here, reference point)
Integration: Evaluating all outcomes together as a combined change in total wealth. Segregation: Evaluating each gamble in isolation, relative to a separate reference point.
Rational (EU) prediction: Contestants should integrate all outcomes — considering their total final wealth, not just each round’s outcome in isolation.
Findings from Deal or No Deal: - Contestants evaluated each round’s banker offer relative to their current reference point (what they believed they “should” have), not their total wealth. - They segregated each round — treating it as a separate gamble with a fresh gain/loss evaluation. - This produced behaviour consistent with prospect theory’s framing effects: the same dollar amount felt like a gain or a loss depending on the path, not the absolute wealth position.
Combined Insight:
| Concept | What DoND Shows |
|---|---|
| Path-dependence | Risk preferences shift based on prior outcomes, not just current state |
| Segregation | Each round is evaluated separately vs. reference point, not as total wealth change |
| Break-Even Effect | Bad-path contestants take more risk to recover → reject fair offers |
| House Money Effect | Good-path contestants become more risk-averse → accept lower offers |
Conclusion: Deal or No Deal provides rare, high-stakes real-world evidence that human decision-making under risk is path-dependent and segregated — consistent with prospect theory and inconsistent with expected utility theory.
End of Tutorial 5 Solutions Reference: AckertDeaves, Chapters 7 and 10 | FINM3407 Behavioural Finance, UQ