Wrap-Up & Exam Revision

1. Foundations & Rationality

• Traditional Finance (Standard Finance):
  • Assumes investors are Rational (maximise utility).
  • Markets are Efficient (EMH - prices reflect all info).
  • Arbitrage is unlimited and risk-free.
• Behavioral Finance:
  • Investors are Normal (Boundedly Rational).
  • Markets are Inefficient (Mispricing persists).
  • Limits to Arbitrage prevent correction of anomalies.

2. Key Heuristics & Biases (The "Errors")

Information Processing Errors

• Representativeness: Judging probability by similarity (stereotyping).
  • Example: "Good company = Good stock" (ignoring price/valuation).
  • Fallacy: Recency bias (chasing recent winners).
• Anchoring: Fixating on an initial value.
  • Example: Refusing to sell a stock below purchase price (Cost price anchor).
• Availability: Overweighting information that is easy to recall.
  • Example: Avoiding stocks after a crash because the "crash" memory is vivid.
• Confirmation Bias: Seeking only info that supports your view; ignoring contradictory data.

Emotional & Ego Biases

• Overconfidence: Overestimating one's own skill (Better-than-average effect) and precision of knowledge (Miscalibration).
  • Result: Excessive trading, under-diversification.
• Loss Aversion: Pain of loss is ~2-2.5x stronger than joy of equivalent gain.
  • Result: Holding losers too long.
• Regret Aversion: Avoiding actions that might lead to regret.
  • Result: Herding (buying what everyone buys to avoid "missing out" or being wrong alone).
• Disposition Effect: Selling winners too early (to catch joy) and holding losers too long (to avoid pain/regret).

3. Prospect Theory (Kahneman & Tversky)

• Reference Point: We evaluate outcomes as Gains vs Losses relative to a reference point (usually status quo/purchase price), not final wealth levels.
• S-Shaped Value Function:
  • Concave for Gains (Risk Averse: take the profit).
  • Convex for Losses (Risk Seeking: hold/gamble to break even).
  • Steeper for Losses (Loss Aversion).
• Probability Weighting: We overweight small probabilities (lottery tickets, insurance) and underweight moderate/high probabilities.

4. Limits to Arbitrage (Why Markets Stay Wrong)

• Fundamental Risk: The mispriced asset could get worse before it gets better.
• Noise Trader Risk: Irrational traders (noise traders) can drive prices further away from value, forcing arbitrageurs to liquidate at a loss (De Long et al.).
  • Quote: "Markets can remain irrational longer than you can remain solvent."
• Implementation Costs: Transaction fees, short-selling constraints, cost of carry.

5. Market Anomalies

• Calendar: January Effect (small caps rise in Jan), Weekend Effect.
• Momentum: Winners keep winning (3-12 months) due to underreaction/herding.
• Value: Low P/E stocks outperform High P/E stocks (contradicts EMH).
• Post-Earnings Announcement Drift (PEAD): Prices drift for weeks after surprise earnings (Underreaction).

6. Behavioral Corporate Finance

• Rational Managers vs Irrational Market: Managers time the market (Issue equity when overvalued, Buyback when undervalued).
• Irrational Managers:
  • Hubris Hypothesis: Overconfident CEOs overpay for acquisitions (Winner's Curse).
  • Sunk Cost Fallacy: Throwing good money after bad projects.
• Dividend Signaling: Paying dividends not just for cash, but to signal strength/cater to investor preference for "bird in the hand."

7. Neurofinance & Emotions

• Triune Brain:
  • Reptilian: Fear/Survival (Panic selling).
  • Limbic: Emotions (Greed, FOMO).
  • Neocortex: Rational analysis (often overridden).
• Fear & Greed Cycles: Biologically driven. Cortisol (stress) creates risk aversion; Dopamine (reward) creates risk seeking.

8. Exam Quick Tips

• Defining a Bias: State the definition -> Give a generic example -> Give a stock market example.
• EMH vs Behavioral: Always contrast "Price = Value" (EMH) with "Price = Value + Sediment/Noise" (Behavioral).
• Arbitrage: Remember it is not risk-free in the real world.

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