Learn about behavioral finance biases — Stock-Market notes

WHAT are behavioral biases?

Two broad families:

Cognitive biases — errors in reasoning/processing information (faulty logic, bad statistics). Often correctable with education/data.
Emotional biases — errors driven by feelings (fear, regret, pride). Harder to fix; must be managed, not argued away.

WHY do biases exist? (First-principles derivation)

Your brain evolved to make fast decisions with limited energy under uncertainty. So it uses heuristics (rules of thumb). A heuristic is efficient on the savanna but misfires in financial markets — an environment full of randomness, feedback loops, and low signal-to-noise.

The key biases (with WHY they feel right)

1. Overconfidence

HOW it shows up: excessive trading, under-diversification, tight (too-narrow) forecast ranges.
Cost: trading more → more fees + worse timing → lower net returns.

2. Anchoring

Example: "The stock was ₹1000 last year, so ₹600 is cheap" — you anchored to ₹1000, ignoring that fundamentals changed.

3. Loss Aversion (Prospect Theory)

Leads to the disposition effect: selling winners too early, holding losers too long (to avoid realizing the loss).

4. Confirmation Bias

5. Herding

6. Availability Bias

7. Recency Bias

8. Mental Accounting

The one number worth deriving: Loss Aversion coefficient

Prospect Theory replaces the smooth utility curve with a value function kinked at a reference point $r$ (usually your purchase price or current wealth):

v(x) = \begin{cases} (x-r)^{\alpha} & x \ge r \quad(\text{gains, concave})\\[4pt] -\lambda\,(r-x)^{\beta} & x < r \quad(\text{losses, convex, steeper}) \end{cases}

Derive the "won't take a fair coin flip" result. Offer: win $G$ or lose $L$ with 50/50. A rational risk-neutral person accepts if $G \ge L$ . But under loss aversion (take $\alpha=\beta=1$ for simplicity, reference at $0$ ):

\text{Accept if } \tfrac12 G - \tfrac12 \lambda L \ge 0 \;\Longrightarrow\; G \ge \lambda L

So with $\lambda = 2$ , you demand to win at least twice what you might lose just to flip a fair coin. That single inequality explains the disposition effect, insurance over-buying, and "freezing" during crashes.

Figure — Learn about behavioral finance biases

Worked examples

Common mistakes (Steel-manned)

Recall Feynman: explain to a 12-year-old

Imagine your brain has a "quick-answer" button so you don't have to think hard about everything — that's great for dodging a ball, but bad for money. One quirk: losing feels twice as bad as winning feels good. So if I offer you a coin flip where you win ₹10 or lose ₹10, you'll say "no thanks," even though it's totally fair. In the stock market this makes people hold onto bad stocks (hoping to break even) and sell good ones too soon. Knowing the trick lets you catch yourself doing it.

Flashcards

What makes an error a "bias" rather than random noise?

It is systematic — it pushes the whole crowd the same direction predictably, so it doesn't cancel out and can move prices.

Cognitive vs emotional bias?

Cognitive = faulty reasoning/statistics (correctable with data); Emotional = driven by feelings like fear/regret/pride (must be managed).

Disposition effect?

Tendency to sell winners too early and hold losers too long, to avoid realizing a loss.

Typical empirical loss-aversion coefficient λ?

About 2.25 — losses feel ~2.25× as intense as equal gains.

Under loss aversion (α=β=1), when do you accept a fair 50/50 win-G/lose-L bet?

Only if

G \ge \lambda L

, i.e. potential win must exceed λ times the potential loss.

Why can a loss-averse person be risk-SEEKING?

The value function is convex in the loss domain, so they gamble to "get back to even."

Anchoring bias?

Over-relying on the first number seen when estimating a value.

Availability vs recency bias?

Availability = judge probability by ease of recall; recency = over-weight the most recent events in forecasts.

Mental accounting error?

Treating money differently by arbitrary label, ignoring that money is fungible.

Why does overconfidence lower returns?

It causes over-trading and under-diversification → higher costs and worse risk-adjusted returns.

Connections

Prospect Theory — the formal model of loss aversion
Efficient Market Hypothesis — the rational benchmark biases violate
Factor Investing — some factors (momentum, value) may be paid premia for bias-driven mispricing
Limits to Arbitrage — why biases aren't instantly corrected
Risk Aversion vs Loss Aversion
Herding and Market Bubbles

Concept Map

Hinglish (regional understanding)

Intuition Hinglish mein samjho

Behavioral finance ka core idea simple hai: hum log calculator nahi hain, hum emotional aur pattern-dhoondhne wale insaan hain. Classical finance maanta hai ki investor hamesha rational hai, lekin real life mein humara dimaag shortcuts (heuristics) use karta hai — aur ye shortcuts market mein galtiyan ban jaate hain, jinhe hum biases kehte hain. "Systematic" word yaad rakhna: ye galtiyan random nahi hoti, poori crowd ek hi direction mein galti karti hai, isliye ye prices ko hila deti hain.

Sabse important bias hai loss aversion. Iska matlab — ₹100 kho jaane ka dukh, ₹100 milne ki khushi se lagbhag 2.25 guna zyada hota hai. Isi wajah se log apne loss-making stocks ko pakde rehte hain (taaki loss "book" na karna pade) aur profit wale stocks ko jaldi bech dete hain. Isko disposition effect kehte hain. Formula se dekho: fair coin flip mein tabhi haan bologe jab jeetne ki raqam $G \ge \lambda L$ ho — yaani ₹600 haarne ke risk par tumhe ₹1350 jeetne ka offer chahiye, warna dil mana kar dega, chahe maths mein profit ho.

Baaki biases bhi yaad rakho — overconfidence (zyada trading, kam diversification), anchoring (pehla number chipak jaata hai), herding (bhed-chaal, bubble banati hai), confirmation bias (sirf apni baat confirm karne wali news dekhna), availability (jo yaad aa jaaye wahi zyada probable lage), aur recency bias (jo abhi hua wahi aage bhi hoga, aisa maan lena). In sabko pehchaanna hi tumhara edge hai.

Yaad rakho: ye biases sirf beginners ko nahi, pros ko bhi hote hain. Solution knowledge se zyada system hai — rules, checklist, aur plan pehle se banao, taaki emotion decision na le. Aur ye bhi samajh lo — bias ke bare mein jaan lene se guaranteed profit nahi milta, kyunki "market irrational reh sakta hai tumhare solvent rehne se zyada der tak."

Test yourself — Factor & Behavioral Finance

Connections