Consult our panel of champion forecasters

We consolidate the predictions of a large international community of news enthusiasts into reliable probability forecasts.

Community of forecasters

Our international community of thousands of minds makes numerical predictions on specific issues.

Prediction market + algorithm

Our prediction markets and proprietary algorithms combine their diverging perspectives according to the science of collective intelligence.

Reliable forecasts

Anticipate strategic issues: business environment, KPI, geopolitical events, economy.

Borrow the predictive power of our panel of seasoned forecasters for reliable predictions

Real-time quantitative forecasts on the most complex subjects

Our forecasting competitions give you insights into international politics, geopolitics, economics, and science

Election results

infectious disease severity

GDP, inflation, business KPIs

« The ability to predict is the essence of intelligence »

« The calculation of probabilities, applied to the life of nations, is the foundation of all high politics. To govern is to predict. »

Why forecast ?

Augmenting traditional forecasting with collective intelligence

10 000 heads are better than 1

The human mind excels when a situation is too new or too complex for big data statistical approaches.

By combining the knowledge of many minds, you get more reliable forecasts than from even the best experts.

How Johns Hopkins used our crowd forecasts to predict infectious disease

Hypermind's forecasting accuracy on over 875,000 forecasts

The forecasts of our prediction market almost perfectly match the observed frequency of events, at all levels of probability.

Reality seemingly aligns itself with our crow forecasts.
For example: 70% of all events estimated to have a 70% chance of happening have actually happened.

Reality

Frequency of occurence of predicted outcomes

99 % correlation between prediction and reality

All events forecasted with a 70 % probability actually happen 70 % of the time.

Each data point in this graph answers the question:
"What is the proportion of events forecasted with probability p that actually happen ?"

Predicted probability

Observed probabilities

Predicted probability

Outcome prices on the prediction market

Data:

875 735

forecasts

816

geopolitical / economic questions

2 535

possible outcomes

8,5

years (2014 – 2022)

"To predict election outcomes, you're better off looking to betting crowds than listening to pollsters."

Estimates of Macron's vote share in a second round duel against Le Pen
Hypermind's crowd forecasts predicted Macron's final score with twice the accuracy of the pollsters

Our crowd forecasts outperformed France's 3 major pollsters on the 2022 presidential elections

2x as accurate as pollsters

Our forecasts were 1.3% points shy of the final score, versus 2.9% for an average of the 3 main pollsters.

Closer to the final score 87% of the time

Our crowd forecasts outperformed the pollsters on 128 out of 146 days.

Prediction markets: predict uncertain futures with betting crowds

Instead of relying on a representative panel, we harness our crowd’s collective intelligence via an online betting platform called a prediction market.

This innovative method stems from research programs into crowd forecasting conducted over the past decade by U.S. intelligence agencies.

Instead of polling the preferences of representative samples of voters, a contest is held to predict the outcome of the election.

A few hundred amateur political scientists make their predictions, and the best are rewarded.

The resulting collective forecast is updated daily by calculating a weighted average of the most recent half of the individual predictions.

Within this average, we increase the weighting of forecasters who frequently adjust their predictions or whose track record is established in previous competitions.

Prediction markets are most useful when forecasting short to medium term observable events (under 24 months), especially in the following cases:

When the past becomes irrelevant:

Traditional forecasting methods such as time series forecasting rely on the past to predict the future, the assumption being that the past can inform the future. 

But sometimes you’ll have little relevant or reliable data at your disposal to make useful projections, and hanging on to historical data may skew your forecasts. Predictions markets aggregate all the available relevant data using the wisdom of crowds.

When knowledge is decentralized:

Nobody knows everything, but everybody knows something. Usually, we solve hard problems by asking an expert: an engineer, a doctor, a lawyer. But sometimes when a problem is too complex,  when too many variables are involved for a single expert to handle, or when there is too little data to train an artificial intelligence individual expertise falls short.

Prediction markets (or prediction polls like our Prescience platform) help consolidate the informed guesses of the many based on all the available data.

When the situation is fluid:

Forecasts need to integrate new information continuously, you need real time forecasts to be able to react accordingly. 

Human forecasters excel at integrating new information because they spot things that AI would miss, information available on the ground but not yet in data bases.

Businesses and governments have used prediction markets in various settings:

  • Intel, Hewlett Packard, Ford, Eli Lilly, and EDF (Electricité de France) have used prediction markets to anticipate KPIs, market shifts, sales volumes, a product’s chances of success, and delays in projects.
  • The US intelligence community used prediction markets in geopolitical forecasting to understand the likelihood of election results, wars and diplomatic events.
  • In the public health sector, the Johns Hopkins Center for Health Security has used crowd forecasting to anticipate the spread and severity of infectious diseases like dengue, malaria and Covid-19.

A prediction market is a competitive betting game designed to predict specific future events or quantities by tapping into the collective intelligence of a large group of participants. Prediction markets combine many diverging viewpoints, expressed as probability forecasts, into a single probability. This collective estimate changes in real time according to all the available information to human minds.

Individual forecasters place bets on outcomes and receive payouts based on their success. The best forecasters are given more weight in the final mix.

Prediction markets (or prediction polls) offer 3 main advantages for companies and governments seeking a clearer view of the future:

  • Prediction markets shine under uncertainty. They excel at accurate prediction where other methods fail because they do not rely on AI crunching structured data, but on the informed guesswork of a diversely minded crowd of humans. (hence “crowd forecasting”)

  • Prediction markets offer precise predictions expressed as probability forecasts. Saying an event is “probable” means different things to different people. “Probable” could mean a 60% chance to one person, but 85% to another. Numbers make things crystal clear, so you can make an informed decision.

  • Prediction markets are a sturdy and trustworthy forecasting method. By gathering information from many minds thanks to an objective aggregation process, prediction markets easily outperform biased or noisy individual judgments. Relying on a crowd helps reduce the risk of listening to the wrong person, instead trusting a decentralized network of independent points of view.

You can use prediction markets to forecast four types of questions:

  • binary: “will John Doe win the election ?” (yes/no)
  • discrete: “who will win the election ?”(John, Jane, Kane)
  • ordered: “what will John Doe’s share of the vote be ?” (more than 55% / 50 to 55% / 45 to 50% …)
  • linear: “what will John Doe’s share of the vote be ?” (market price = predicted vote share in %)

They have been used to predict events in various application domains like sports, elections, geopolitics, medicine, science and technology.

The first modern prediction market began in 1988 as an academic research project at the University of Iowa’s Tippie College of Business and offered forecasts on that year’s US presidential election. The World Wide Web soon enabled the launch of larger prediction markets targeted at the general public, sometimes bearing other names, like betting exchanges or idea futures.

Hypermind’s pioneering prediction market was first launched in 2000 under the name NewsFutures.

Over the years, this form of “crowd wisdom” has acquired an impressive track record of accurate forecasting in diverse fields ranging from sports and film to business, elections, geopolitics and even medicine.

Our predictions for the 2022 French presidential race "Who will be the next President of the Republic?"

The probability of victory for each candidate is expressed in %.