From Kasparov to WallStreetBets: how collective wisdom is shaking up financial markets and redefining the role of the expert in modern finance.
NOVEMBER 4, 2025
BY REMY
Abstract :
This article examines how collective intelligence can rival expert performance in complex decision environments, from chess to financial markets. Revisiting Kasparov’s encounters with both Deep Blue and a global online crowd, it highlights how diversity and independent judgment enhance aggregated decision accuracy. Drawing on established research in behavioral finance and cognitive diversity, the article argues that modern markets - characterized by instability and rapid information diffusion - amplify the advantages of well-structured collectives over isolated experts. Events such as the GameStop short squeeze illustrate this shift. The article concludes that collective intelligence remains underexploited in finance, despite its growing predictive and analytical potential.
📑 Table of Contents
- The day the crowd nearly beat the master
- The laws of collective wisdom
- From chess to finance: an unexpected parallel
- Collective intelligence put to the test by the markets
- The figures say it all
- Collective intelligence in finance: an underused resource
1. The Day the Crowd Almost Beat the Master
On May 11, 1997, in New York, a drop of sweat trickles down Garry Kasparov’s forehead.
The world chess champion, a brilliant strategist, is about to lose a historic match.
His opponent does not breathe, tremble, or blink. It stands two meters tall, weighs 1,400 kg, and goes by the name Deep Blue. This IBM supercomputer, capable of analyzing 200 million positions per second, is the result of years of relentless effort and repeated failures. Built at the very last minute, it now finds itself playing one of the most important games in chess history.
Facing Kasparov, Deep Blue prevails.
Chess has just entered a new era: one in which the computing power of a machine surpasses human thought.
Today, even a cheap chess engine running on a standard laptop would easily beat any grandmaster. The machine has definitively conquered the game of kings.
But two years later, another match would shatter yet another certainty. And this time, Kasparov wasn’t playing against a machine, but against a crowd of other players.
In 1999, MSN Gaming Zone presented Kasparov with an unprecedented challenge: to face an entire crowd.
Nearly 50,000 participants from 75 different countries signed up.
Each day, internet users voted on the next move; the most popular choice was played against the champion.
Experts predicted a disaster for the crowd. Their reasoning was simple: how could a scattered multitude of amateurs stand up to the best player in the world?
Yet the crowd surprised them.
From the very first moves, it played accurately. Faced with Kasparov’s opening, it replied with a Sicilian Defense, the best theoretical option. Then, on move ten, it innovated. A 53% majority voted for a novel queen move to E6 - one never before seen in high-level play.
Kasparov would later call it a “remarkable theoretical novelty.”
The game lasted four months.
Kasparov eventually won, but just barely.
“The sheer number of ideas, the complexity, and the contribution it has made to chess make it the most important game ever played.”
— Garry Kasparov
The crowd lost… but it proved something:
👉 a multitude of individuals, coordinated yet free, can rival a world expert in a specialized field.
2. The Laws of Collective Wisdom
According to James Surowiecki (The Wisdom of Crowds, 2004), a crowd becomes “wise” when two conditions are met:
- Diversity of viewpoints
- Independence of judgments
Scott Page (2007) shows that high cognitive diversity enhances collective performance by avoiding groupthink and shared biases.
These findings extend the early insights of Francis Galton (1907), who discovered that the average of a crowd’s estimates can be more accurate than that of an expert.
This is the famous “Galton effect.”
At an early 20th-century fair, hundreds of visitors estimated the weight of an ox.
The average of their guesses?
Exactly the correct weight.
3. From Chess to Finance: The Same Game, Only More Chaotic
Twenty-five years after the Kasparov matches, the 64-square board has been replaced by a far more unstable arena for collective intelligence: the financial markets.
And here, the modern “Kasparovs” - analysts, fund managers, star economists - no longer enjoy such a clear advantage.
Why?
Because in the stock market, the rules are constantly changing.
A tweet from Elon Musk, a Chinese regulation, a breakthrough in AI, a war, a TikTok trend…
So many unpredictable moves that no model can reliably anticipate over time.
In this shifting environment, the diversity of perspectives - those of the young crypto investor, the cautious father, the marketing student - forms a collective radar far broader than that of any isolated expert.
The chess grandmaster plays in a world with stable rules, where accumulated experience ensures performance.
The financial analyst navigates an unstable, self-referential ecosystem, where each prediction can influence the market itself.
In his research, David Hirshleifer (2001) described how collective psychology shapes asset pricing. His conclusions have been confirmed by more recent work, including Robert Shiller (2015), who showed how market bubbles rest on “irrational exuberance.”
In other words:
📉 Expertise ages quickly.
📈 Collective adaptation endures.
4. Collective Intelligence Put to the Test by the Markets
Traditional economists long looked down on retail investors.
But decades of “wisdom of crowds” research have shown the opposite.
When large numbers of individuals express their judgments with diversity and independence, the average of their opinions is often more accurate than that of isolated experts.
Markets are not an exact science.
They are a mirror of our collective behavior.
And today, more than ever, that mirror belongs to the crowd.
A well-structured crowd is not a disorganized mass.
It is a living organism that:
- filters noise,
- detects weak signals,
- learns faster than any individual.
In markets, this distributed intelligence becomes a strategic advantage.
Forums, communities, and shared information flows create a collective memory that learns and adapts in real time.
5. The figures say it all
- 1.7 million active retail investors were counted in France in 2024 by the AMF, up 21.5% in two years. This illustrates the massive rise of the crowd in the markets, disrupting the historical supremacy of experts.
- $3.75 billion: the loss suffered by Melvin Capital due to the coordination of WallStreetBets users during the GameStop saga, a quantified demonstration of the disruptive power of collective intelligence in modern markets.
- Just 1% separated the crowd’s median estimate from the true weight of an ox in Francis Galton’s 1907 experiment - outperforming many experts and forming the statistical foundation of collective wisdom.
6. Collective Intelligence in Finance: An Underused Resource
In recent years, several signs indicate that finance is no longer the exclusive domain of institutions.
Individual investors are gathering, exchanging, and experimenting with new forms of coordination - often more agile and sometimes more effective than traditional players.
The GameStop episode proved it: a community of independent investors can influence a global market simply by sharing a common conviction.
Researchers Greene and Rao (2021) showed that coordinated groups can exert lasting influence on financial markets.
On X (Twitter), “finfluencers” create collective-monitoring spaces where ideas circulate faster than in analyst reports.
Platforms like eToro have institutionalized this energy through social trading.
And Polymarket, by leveraging prediction-market logic, shows that crowds can forecast the future with accuracy sometimes superior to experts.
But these initiatives remain fragmented, opportunistic, or speculation-focused.
They tap into collective intelligence without truly structuring it.
What’s missing today is a place where this intelligence can gather - not to imitate, speculate, or copy, but to understand, analyze, and collectively anticipate market dynamics: a place where weak signals, intuitions, and cross-analysis from diverse investors become a true predictive intelligence capable of guiding individual decisions.
In short: to be neither dependent on a bank, nor on the empty promises of a passing financial influencer.
The potential is huge.
📚 References
- Surowiecki, J. (2004). The Wisdom of Crowds. Anchor Books.
- Page, S. E. (2007). The Difference. Princeton University Press.
- Galton, F. (1907). Vox Populi. Nature, 75, 450–451.
- Shiller, R. J. (2015). Irrational Exuberance. Princeton University Press.
- Hirshleifer, D. (2001). Investor Psychology and Asset Pricing. The Journal of Finance.
- Greene, J., & Rao, G. (2021). Lessons from the WallStreetBets Frenzy. Journal of Behavioral Finance.
- Antweiler, W., & Frank, M. Z. (2004). Is All That Talk Just Noise? The Journal of Finance.
- Easley, D., & O’Hara, M. (2010). Microstructure and Ambiguity. American Economic Review.