Understand anchoring and confirmation bias — Hinglish notes

6.6.7 · Stock-Market › Factor & Behavioral Finance

YEH biases HAIN kya?

YEH biases EXIST kyun karti hain?

Anchoring ek investment decision ko KAISE distort karta hai (derive karo)

Chaliye ek simple model banate hain rational vs. anchored valuation ka.

Ek rational investor ko stock ki value sirf uski fair value $V^{*}$ se aankni chahiye, jo fundamentals (cash flows, growth) par based ho. Lekin ek anchored investor ki perceived value $\hat{V}$ true value aur anchor $A$ ka ek blend hoti hai:

$\hat{V} = (1 - w) V^{*} + w A$

Yeh form kyun? Agar investor anchor se poori tarah adjust kar leta, toh weight $w = 0$ aur $\hat{V} = V^{*}$ (rational). Agar woh bilkul anchor par stuck hota, toh $w = 1$ aur $\hat{V} = A$ . Real log beech mein hote hain, isliye $0 < w < 1$ anchor ki "stickiness" hai.

Decision error yeh hai:

$ε = \hat{V} - V^{*} = w (A - V^{*})$

Yeh step kyun? Perceived value mein se correct value ghataao. Error proportional hai (a) anchor kitna sticky hai, $w$ , aur (b) anchor truth se kitna door hai, $(A - V^{*})$ .

"Loss pe sell nahi karunga" wala trap

Maano tumne $A = \$ 100 $p a r k ha r i d a (t u mha r aan c h or), l e k in f ai r v a l u e g i r k e$ V^* = $70 $h o g a y i . S t i c k in ess$ w=0.5$ ke saath:

$\hat{V} = 0.5 (70) + 0.5 (100) = $85$

Tumhein lagta hai stock $85 k ahai, i s l i y e t u m$ 70 par sell karne se mana kar dete ho — jabki market bhi maanta hai ki woh $70 ka hai. Tumhara error hai:

$ε = 0.5 (100 - 70) = + $15$

Tum sirf apne purchase price ki wajah se $15 zyada value laga rahe ho.

Figure — Understand anchoring and confirmation bias

Confirmation bias ise KAISE compound karta hai (Bayesian view)

Rational updating Bayes' rule use karta hai. Ek hypothesis $H$ ("yeh stock badhega") ke liye evidence $E$ diya ho toh:

$P (H ∣ E) = \frac{P ( E ∣ H ) P ( H )}{P ( E )}$

Yeh kyun matter karta hai: Ek rational investor sabhi evidence $E$ par update karta hai. Ek confirmation-biased investor evidence set ko filter karta hai — woh sirf woh evidence andar aane deta hai jahan $P (E ∣ H)$ high ho (supportive), aur mentally disconfirming evidence discard kar deta hai.

Toh poore set ${E_{1}, E_{2}, ..., E_{n}}$ par update karne ki jagah, woh sirf supportive subset par update karta hai. Result: unka posterior belief $P (H ∣ E)$ artificially high rehta hai — numerator baar baar boost hota rehta hai, disconfirming evidence kabhi ise neeche nahi laati.

Worked examples

Steel-manned mistakes

Flashcards

Anchoring bias kya hai?

Pehle dekhe gaye number (jaise purchase price, 52-week high) par zyada rely karna aur ussey poori tarah adjust nahi kar paana.

Confirmation bias kya hai?

Sirf woh evidence dhundhna/interpret karna/yaad rakhna jo tumhare existing belief ko support kare, virodhi evidence ko ignore karo.

Model

\hat{V} = (1 - w) V^{*} + w A

mein

w

kya represent karta hai?

Anchor ki "stickiness" — kitna perceived value anchor

A

ki taraf khichi jaati hai true value

V^{*}

ki jagah.

Anchoring se hone wala decision error kya hai?

ε = w (A - V^{*})

— anchor stickiness aur anchor ke fair value se door hone ke proportion mein.

Confirmation bias Bayesian terms mein belief ko kyun inflate karta hai?

Woh evidence ko sirf supportive signals (likelihood ratio > 1) tak filter kar deta hai, isliye posterior badhta rehta hai aur kabhi downward correct nahi hota.

Purchase-price anchor ko beat karne ka sabse accha test?

"Kya main aaj fresh cash se yeh stock kharidta?" Agar nahi, toh sell karo — tumhara past price irrelevant hai.

Kharidne se pehle confirmation bias ka ek antidote?

Pre-mortem: 3 sabse strong reasons likho ki thesis galat kyun ho sakti hai.

Anchoring ek "efficient" lekin bura shortcut kyun hai?

Kisi number ko poori tarah adjust karna mentally costly hai, isliye brain bahut jaldi adjust karna rok deta hai — fast hai lekin inaccurate.

Recall Feynman: ek 12-saal ke bacche ko explain karo

Maano tumne ek toy $10 m e ink ha r i d a . B aa d m e in s abhik e h t e haink i w o ha c t u a l l y s i r f$ 6 ki hai. Lekin kyunki tumne * $10 d i y e t h e *, t u mha r ab r ainbaa r baa r k e h t ahai " nahi, y e h$ 8 ki hai!" Woh sticky pehla number hai anchoring. Ab maano tumhein lagta hai yeh toy sabse best toy hai — toh tum sirf unhi doston ki sunte ho jo agree karte hain aur jo kehta hai yeh bekar hai use ignore kar dete ho. Woh hai confirmation bias: tum sirf "tum sahi ho!" collect karte ho aur "tum galat ho!" phenk dete ho. Dono milke tumhein ek buri toy bahut zyada der tak rakhne par majboor karte hain.

Connections

Loss Aversion and the Disposition Effect — kyun buy price par anchor karna losers hold karwata hai
Overconfidence Bias — confirmation bias iska main fuel hai
Bayesian Updating in Investing — woh rational benchmark jise biases violate karte hain
Behavioral Finance Overview — parent framework
Efficient Market Hypothesis — biases persistent inefficiencies explain karte hain
Mean Reversion vs. Anchoring — valid reference points aur false anchors mein farq