23 — Market Cycles

Euphoria & Panic#

Heuristic
◆ The PatternThe two emotional extremes of market cycles.

Euphoria and Panic — the two emotional extremes that mark market tops and bottoms.

Signs of euphoria:
• "This time is different" — the four most expensive words
• Retail investor participation surges
• IPOs of marginal companies succeed wildly
• Taxi drivers / neighbors give stock tips

Signs of panic:
• "I can't take it anymore" — capitulation
• Margin calls force selling at any price
• VIX spikes to 40+
• "Stocks are dead" headlines
Worked example

The Nasdaq Composite closed at 5,048.62 on 10 March 2000 and at 1,114.11 on 9 October 2002: a fall of 78%. Getting back needed a rise of 353%; it did not close above the 2000 peak again until 2015. The asymmetry is the whole lesson: a +150% run followed by a −60% fall leaves you at exactly 0%.

Where it misleads
  • Big run-ups do not reliably predict lower average returns, but they do predict a higher chance of a crash (Greenwood, Shleifer & You 2019).
  • “This time is different” is sometimes true; the internet did change the economy. Euphoria is about price relative to plausible outcomes, not about the story being false.
  • Panic bottoms are only clear afterwards; buying the first panic is often early.
In code
peak, trough = 5048.62, 1114.11                  # Nasdaq Composite closes, 10 Mar 2000 and 9 Oct 2002
fall = trough / peak - 1
needed = peak / trough - 1                       # the rise needed just to get back
up, down = 1.50, -0.60
round_trip = (1 + up) * (1 + down) - 1           # +150% then -60%
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
  • R. Greenwood, A. Shleifer & Y. You, “Bubbles for Fama”, Journal of Financial Economics 131(1), 2019
  • Manias, Panics, and Crashes: A History of Financial Crises, C. P. Kindleberger (later editions with R. Z. Aliber), 1978
  • Irrational Exuberance, R. J. Shiller, Princeton University Press, 2000

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

Pattern bridge: Extreme sentiment at both ends of the distribution tails. In ML, diffusion models add noise (panic) then learn to reverse it (recovery).
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