Prices Algorithmically Quote by Brian Christian
““look no further than Peter A. Lawrence’s developmental biology text The Making of a Fly, which in April 2011 was selling for $23,698,655.93 (plus $3.99 shipping) on Amazon’s third-party marketplace. How and why had this—admittedly respected—book reached a sale price of more than $23 million? It turns out that two of the sellers were setting their prices algorithmically as constant fractions of each other: one was always setting it to 0.99830 times the competitor’s price, while the competitor was automatically setting their own price to 1.27059 times the other’s. Neither seller apparently thought to set any limit on the resulting numbers, and eventually the process spiraled totally out of control. It’s possible that a similar mechanism was in play during the enigmatic and controversial stock market “flash crash” of May 6, 2010, when, in a matter of minutes, the price of several seemingly random companies in the S&P 500 rose to more than $100,000 a share, while others dropped precipitously—sometimes to $0.01 a share. Almost $1 trillion of value instantaneously went up in smoke.””
About This Quote
Source Book: The Making of a Fly by Peter A. Lawrence, 2011
Infinite feedback loops can cause prices to explode when each participant mirrors the other without limits.
In simple terms: Algorithms can drive prices to extreme values.
Set safeguards on automated pricing.
Themes
Mood
Type
When to use this quote
- e‑commerce pricing
- stock market flash crashes
- automated bidding
- financial modeling
- regulatory oversight
Key Concepts
Questions to Reflect On
- How can we design algorithms to prevent self‑reinforcing price spikes?
- What safeguards are needed in automated trading?
If participants ignore bounds, runaway escalation can destabilize markets.