02 — Cognitive Biases

Anchoring#

Statistical1 min read
◆ The PatternOver-relying on the first piece of information encountered (the "anchor").

Anchoring — over-relying on the first or most prominent piece of information as a reference point.

Your buy price ($50) → stock drops to $30 → "it's cheap" ← anchored to $50, not to intrinsic value
Common anchors:
• Purchase price ("I'll sell when I get back to even")
• 52-week highs ("it was $100, now $60 — bargain!")
• Round numbers ($100, $10,000 Bitcoin)
• Analyst price targets

Solution: value assets on future fundamentals, not past prices.

Worked example

The stock’s 52-week high is 80 and it now trades at 62: 0.775 of the high, or “22.5% off”. To someone who bought at 75 it is also 17.3% below cost. Both numbers feel like information about value; neither is. The 80 is where other people traded last year, and the 75 is where you did.

Where it misleads
  • Anchors are not always irrational: the 52-week high is watched by so many traders that it can matter for behaviour around it, even though it says nothing about value.
  • George & Hwang (2004) found that stocks near their 52-week high go on to outperform — investors anchor and underreact to good news, so “too close to the high” is not a sell signal.
  • Replacing one anchor with another (an analyst’s target) is not a cure. A valuation built from expected cash flows is.
In code
close = pd.Series([80, 78, 74, 70, 66, 63, 61, 64, 62, 60, 63, 62])   # twelve month-end closes, made up
high52 = close.max()                     # the anchor: the 52-week high
ratio = close.iloc[-1] / high52          # George & Hwang's measure, price over its 52-week high
off_high = 1 - ratio
cost = 75                                # where this holder bought: a second anchor
vs_cost = close.iloc[-1] / cost - 1
Python, in your browser — edit the code and run it again

Assumes import numpy as np and import pandas as pd. Each snippet carries its own example numbers; the comments say which are made up.

Sources
  • A. Tversky & D. Kahneman, “Judgment under Uncertainty: Heuristics and Biases”, Science 185(4157), 1974
  • T. J. George & C.-Y. Hwang, “The 52-Week High and Momentum Investing”, Journal of Finance 59(5), 2004
  • G. B. Northcraft & M. A. Neale, “Experts, Amateurs, and Real Estate: An Anchoring-and-Adjustment Perspective on Property Pricing Decisions”, Organizational Behavior and Human Decision Processes 39(1), 1987

Last reviewed October 2026 · How this site checks its content · Report a mistake

Check yourself

1. What is anchoring?

Show answer

A. In Tversky & Kahneman’s 1974 experiment, a spun wheel of fortune shifted people’s estimates of a factual quantity.

2. George and Hwang (2004) linked the 52-week high to momentum. What did they find?

Show answer

A. Nearness to the 52-week high explained much of the momentum effect in their sample.

3. A common anchor in your own portfolio is…

Show answer

B. Judge a holding on its prospects from today’s price, not on whether it is above or below your entry.

Pattern bridge: Anchoring to a reference price is the psychological cousin of the mean — a central value everything is measured from. In ML, weight initialization anchors where training begins.
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