Behavioral FINA Short Answer + Computations

Q1. What is the difference between a good company and a good stock?

A good company is one with strong fundamentals (e.g., quality management, growth, innovation), but it may be overpriced. A good stock is one that's undervalued relative to its fundamentals — its price is low compared to its intrinsic value. Key idea: Price ≠ Value. Example: Tesla may be a good company, but if overpriced, it may be a bad stock. Mnemonic: V ≠ P Rule (Value is not always Price).

Q2. Compare Representativeness and Anchoring. How do they bias decisions?

Representativeness: Judging based on similarity to a stereotype (e.g., assuming a startup will succeed because it resembles Apple). Anchoring: Over-relying on an initial value (e.g., stock purchase price). Mnemonic: SAB = Stereotype vs. Anchor Bias. Rep = pattern matching, base-rate neglect. Anchor = sticky thinking, insufficient updating.

Q3. Emotion-Based vs. Rational Decision-Making — Are they incompatible?

Rational decisions rely on logic and optimization (e.g., EUT). Emotion-based ones are intuitive, influenced by feelings (e.g., fear, regret). Emotions may impair or enhance decisions. They're not always incompatible. Skilled traders often balance both. Mnemonic: FEAR = Feelings Erode Analytical Rationality — but not always destructively.

Q4. What is the intuition behind the regression: LTIV = f(Size, B/M, MQ)?

The regression shows that investors associate high long-term investment value with large firms, low B/M (growth stocks), and strong management. But this contradicts empirical data (which shows small value firms outperform). Biases: Representativeness (big = good) and anchoring on firm image. Mnemonic: BIG-MIS = Big firms and MQ are Misleading Indicators of Success.

Q5. Why do people assign different weights to winner vs. loser stocks in retirement accounts?

Due to Disposition Effect (selling winners, holding losers), Self-Attribution (crediting success to skill), and House Money Effect (riskier with gains). Investors treat gains/losses differently, leading to biased weighting. Mnemonic: DISH = Disposition, Internal credit (self-attribution), and House money.

Q6. Are stock market forecasters overconfident? Do they learn from mistakes?

Yes — they display overconfidence, particularly miscalibration. They give narrow confidence intervals. Some learning occurs, but it's slow and biased due to self-attribution bias. Also, success reinforces confidence (even if due to luck). Mnemonic: CLOSE = Confidence, Learning is slow, Overtrading, Self-attribution, Experience backfires.

Q7A. Define and distinguish Momentum and Reversal.

Momentum: Short-term persistence in returns. Investors buy recent winners (0-6 months). Reversal: Long-term mean-reversion — losers outperform, winners underperform (3-5 years). Mnemonic: MR = Momentum-Reversal: Momentum = Ride the wave; Reversal = What goes up, must come down.

Q7B. Explain Mean-Reversion vs. Continuation in the BSV Model (optional).

BSV Model explains both momentum and reversal using representativeness and conservatism. Continuation arises when investors underreact short-term (conservatism). Reversal arises when overreaction (representativeness) sets in. Mnemonic: BSV = Behavioral Switching View.

Q7C. Define Size Factor and Book-to-Market Factor.

Size Factor: Small-cap stocks tend to outperform large caps. Book-to-Market (Value) Factor: High B/M (value) stocks outperform low B/M (growth). These are part of Fama-French 3-Factor Model. Mnemonic: SF/BMF = Size Factor / Book-Market Factor: Size = small wins; B/M = cheap wins.

Q7D. Compare Risk-Based vs. Behavioral Explanations for anomalies.

Risk-Based: Anomalies reflect unmeasured risk (e.g., small firms are riskier). Behavioral: Mispricing due to biases (e.g., overconfidence, anchoring). Arbitrage is limited, so biases persist. Mnemonic: RA vs. BA = Rational Adjustments vs. Behavioral Anomalies.

How do you calculate Expected Utility?

Use: E[U] = p1 × U(w1) + p2 × U(w2). Example: 50% chance of £22K or £18K, U(w) = ln(w). → E[U] ≈ 0.5ln(22000) + 0.5ln(18000) = ~9.895.

How do you calculate Certainty Equivalent (CE)?

U(CE) = E[U]. Invert the utility function. Example: ln(CE) = 9.895 ⇒ CE = e^9.895 ≈ £19,847.

How do you calculate Risk Premium (RP)?

RP = E(W) – CE. Example: Expected Wealth = £20,000, CE = £19,847 ⇒ RP = £153.

What is the Mean-Variance Utility formula?

U = E(r) – 0.05Aσ² (A = risk aversion coefficient). Higher A → lower utility for high variance. Choose asset with highest U.

How do you find Max Willingness to Pay (e.g., for insurance)?

Set E[U(No Insurance)] = E[U(With Insurance)]. Solve for the premium I. U(£100 – I) = E[U]. Example: I = £19 when E[U] = 9 ⇒ √(100 – I) = 9.

How do you calculate Value under Prospect Theory?

Use: V = π(p) × v(x). E.g., π(0.001) = 0.011, v(£5000) = 5000^0.8 ≈ 1799 ⇒ V = 0.011 * 1799 ≈ 19.79.

What is the formula for Absolute Risk Aversion (ARA)?

ARA = –U″(x)/U′(x). Measures aversion to small, local risks. Decreasing ARA → more willing to take risk as wealth increases.

What is the formula for Relative Risk Aversion (RRA)?

RRA = –x × U″(x)/U′(x). Adjusts for wealth. Constant RRA implies investor’s relative aversion doesn’t change with wealth.