Unit 5: Market outcomes
Market Outcomes in Behavioral Finance
Behavioral finance explains real-world market outcomes that often contradict EMH (Efficient Market Hypothesis).
These outcomes are known as market anomalies because they cannot be explained by rational models.
1. Size Effect and Seasonality
A. Size Effect
- Small-cap stocks consistently generate higher returns than large-cap stocks.
- Discovered by Banz (1981).
- Contradicts CAPM because small firms have higher returns even after adjusting for risk.
Reasons (Behavioral Explanation):
- Investors neglect small firms → underpricing
- Higher uncertainty creates fear → undervaluation
- Less analyst coverage → mispricing persists
B. Seasonality
Markets show patterns at specific times of year.
1. January Effect
- Stocks, especially small-cap, give unusually high returns in January.
- Investors sell in December for tax-loss harvesting and buy back in January.
2. Weekend Effect
-
Monday returns are lower than Friday returns because of negative news over weekends and investor pessimism.
3. Turn-of-the-Month Effect
-
Higher stock returns during the last and first few days of a month.
2. Momentum and Reversal
A. Momentum Effect
- Stocks that performed well in the past continue to perform well in the short term (3–12 months).
- Investors underreact to new information.
Reasons:
- Herding
- Anchoring
- Confirmation bias
- Slow diffusion of information
B. Reversal Effect
- Stocks that performed poorly in the distant past (3–5 years) tend to outperform later.
- Long-term loser → future winner.
Reasons:
- Overreaction to bad news
- Excess pessimism
- Mean reversion in prices
3. Post-Earnings Announcement Drift (PEAD)
After a firm announces better-than-expected earnings, the stock price:
- rises immediately, but not fully
- continues drifting upward for weeks or months.
Similarly, bad earnings → price continues drifting downward.
Reason
Investors underreact to earnings information due to:
- conservatism bias
- anchoring
- slow information processing
This violates EMH because prices should adjust immediately and fully.
4. Value Premium
Value stocks (low P/E, low P/B, high book-to-market) outperform growth stocks consistently.
Why Value Premium Exists (Behavioral Explanation):
- Investors are overly optimistic about growth stocks → overvaluation
- Investors are overly pessimistic about value stocks → undervaluation
- Representativeness bias
- Overreaction to short-term performance
This anomaly forms the basis of Fama–French 3-Factor Model.
5. Equity Premium Puzzle
Historically, equities have earned much higher returns than risk-free assets (like government bonds).
The difference is so large that it cannot be explained by standard economic models.
Behavioral Explanation
- Loss aversion → investors require high premium to hold risky stocks
- Myopic loss aversion → short-term fear drives higher risk premium
- Overreaction and underreaction create additional volatility and risk perception
6. Excessive Volatility
Stock markets fluctuate far more than can be explained by changes in fundamentals (earnings, dividends).
Robert Shiller argued that market prices are too volatile to be rational.
Behavioral Causes
- Overreaction to news
- Fear and greed cycles
- Speculation
- Herd behavior
- Availability bias (recent events dominate decisions)
7. Market Bubbles
A bubble occurs when asset prices rise far above intrinsic value due to irrational behavior.
Stages of a Bubble (Psychological Model)
- Displacement – new technology, policy, or innovation
- Boom – investors become optimistic
- Euphoria – prices skyrocket, FOMO
- Profit Taking – smart investors exit
- Panic & Crash – bubble bursts
Behavioral Reasons
- Herding
- Overconfidence
- Confirmation bias
- Greater fool theory
- Narrative bias (people believe exciting stories)
Examples
- Dot-com bubble (1999–2000)
- Housing bubble (2007–08)
- Crypto booms
8. Behavioral Asset Pricing Model (BAPM)
Traditional Asset Pricing Models like CAPM assume:
- rational investors
- no biases
- perfect markets
Behavioral Asset Pricing Model adds psychological components.
Key Features of BAPM
1. Risk = Statistical Risk + Sentiment Risk
Price = Fundamental Value + Investor Sentiment
Investors require a higher return when:
- uncertainty is high
- sentiment (fear/confidence) fluctuates
2. Includes Behavioral Biases
Pricing is influenced by:
- overconfidence
- herding
- loss aversion
- mental accounting
3. Limits to Arbitrage Matter
Mispricing cannot be easily removed.
4. Mispricing Persists
Because real investors:
- are not fully rational
- react emotionally
- use heuristics
5. Expected Return Depends on
- perceived risk
- psychological factors
- market sentiment index
Summary Table (MBA Exam Friendly)
| Concept | Meaning | Behavioral Reason |
|---|---|---|
| Size Effect | Small-cap > large-cap returns | Neglect, low attention |
| Seasonality | Patterns like January effect | Biases, tax-loss selling |
| Momentum | Winners keep winning | Underreaction |
| Reversal | Long-term losers rebound | Overreaction |
| PEAD | Slow price adjustment after earnings | Conservatism bias |
| Value Premium | Value > Growth returns | Over/underreaction |
| Equity Premium Puzzle | Stocks return far higher than bonds | Loss aversion |
| Excessive Volatility | Prices fluctuate beyond fundamentals | Emotions, herding |
| Bubbles | Prices rise far above intrinsic value | FOMO, overconfidence |
| BAPM | Asset prices affected by psychology | Sentiment + biases |
Value Investing
Value investing is an investment approach that focuses on buying stocks that are trading below their intrinsic (true) value.
It was popularized by Benjamin Graham and Warren Buffett.
Value investors believe: “Price is what you pay; value is what you get.”
1. Central Tenets of Value Investing
1. Intrinsic Value
Every company has a real underlying value based on:
- earnings
- cash flows
- assets
- long-term growth
Value investors purchase when the market price < intrinsic value.
2. Margin of Safety
Buy at a large discount so that even if estimates are wrong, the downside is protected Example: If intrinsic value = ₹100, value investor wants to buy at ₹60–₹70.
3. Long-Term Orientation
- Hold stocks for years, not days.
- Short-term volatility is ignored.
- Compounding generates wealth.
4. Focus on Fundamentals
Value investors examine:
- P/E ratio
- P/B ratio
- Dividend yield
- Debt levels
- Cash flow stability
They avoid hype, speculation, and hot trends.
5. Contrarian Thinking
Value investors buy when others are fearful and sell when others are greedy.
They exploit:
- overreaction
- market panic
- temporary bad news
6. Patience & Discipline
Markets may take time to correct mispricing.
Discipline is essential to avoid emotional decisions.
2. Evidence and Prospects of Value Investing
A. Historical Evidence
Fama–French Research- Value stocks (high book-to-market) outperform growth stocks consistently.
- Known as the Value Premium.
Long-Term Market Returns
Over decades, portfolios based on low P/E, low P/B, high dividend yield, and stable earnings have delivered superior returns.
Global Evidence
Value strategy succeeds in the US, Europe, Japan, and emerging markets.
B. Why Value Investing Works
- Markets overreact to short-term events
- Investors chase trending stocks (growth stocks)
- Fear causes undervaluation of fundamentally strong companies
- Behavioural biases (anchoring, loss aversion) create opportunities
C. Current Prospects
Value investing remains relevant because:
- Human psychology hasn’t changed
- Markets are still prone to overreaction
- Information overload creates more mispricing
- Automated trading increases volatility → more opportunities
Even though growth stocks dominate certain periods (e.g., tech boom), value investing continues to perform strongly over long horizons.
3. Strategies of Well-Known Value Investors
A. Benjamin Graham – Father of Value Investing
Strategy Highlights
- Buy deeply undervalued “cigar-butt” stocks
- Focus on low P/E, low P/B
- Diversify widely
- Strict margin of safety
- Avoid speculation
B. Warren Buffett – Quality + Value
Buffett evolved Graham’s approach.
Strategy Highlights:
-
Buy wonderful companies at fair prices
Focus on:
- strong brands
- competitive advantage (moat)
- high ROE
- consistent profits
- Hold for decades
- Invest in businesses, not tickers
- Avoid companies he doesn’t understand
C. Charlie Munger – Mental Models
Strategy Highlights:
- Use multi-disciplinary thinking
- Look for long-term competitive advantage
- Avoid psychological traps
D. Seth Klarman
Strategy Highlights:
- Deep value investing
- Very high margin of safety
- Willing to hold cash
- Avoids fashionable sectors
E. Joel Greenblatt
Strategy Highlights:
- Magic Formula (Earnings Yield + ROIC)
- Simple quantitative value investing formula
F. Howard Marks
Strategy Highlights:
- Focus on market cycles
- Buy when others panic
- Emphasis on risk control
4. Academic Research on Value Investing
Academic research consistently shows value strategies outperform growth.
A. Fama–French 3-Factor and 5-Factor Models
- Show that high book-to-market (value) stocks earn higher returns.
- Value premium persists across decades and markets.
B. Research on Behavioral Explanations
Studies show value premium exists because:
- Investors overreact to past performance (Lakonesh, De Bondt & Thaler)
- Analysts are overly optimistic about growth stocks
- Markets underreact to long-term fundamentals
C. Research on Risk-Based Explanation
- Some academics argue value stocks are riskier (distressed companies).
- Investors demand higher returns as compensation.
D. Quantitative Value Research
- Low P/E, low PEG, high dividend yield strategies outperform benchmarks.
- Trend holds across 100+ years of market data.
E. Global Evidence
- Value investing works in both developed and emerging markets.
- Even during tech or growth booms, value stocks rebound strongly later.
Exam-Ready Summary Table
| Topic | Key Points |
|---|---|
| Tenets | Intrinsic value, margin of safety, long-term, fundamentals, contrarian thinking |
| Evidence | Fama-French value premium, long-term outperformance, global evidence |
| Famous Investors | Graham (deep value), Buffett (quality + value), Munger (mental models), Klarman, Greenblatt |
| Research | Behavioral reasons, risk-based explanations, quantitative models |