FORAXION TIMESNOVEMBER 2026

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Results for “prediction markets”

2026-08-03The Forecasting Machine

Play money, same ballpark: Hypermind’s 12-year accuracy benchmark against Polymarket and Kalshi

Hypermind published the data from 1,141 play-money markets resolved since 2014 and compared them with Polymarket and Kalshi. The report concludes the three are at parity, and an independent commentator agreed that parity, not victory, is the defensible reading.

2026-08-02The Forecasting Machine

France 2027 on the Hypermind Market: How the Odds Moved Between Summer 2025 and Summer 2026

A year of Hypermind forecasts on the 2027 French presidential election, read as a market snapshot rather than a prediction: the RN’s combined chances rose, the “someone else” option shrank, and Édouard Philippe consolidated his position on the centre-right.

2026-07-29The Forecasting Machine

L’Express Interviews Émile Servan-Schreiber on Polymarket and Money-Free Forecasting

Days after France blocked Polymarket, L’Express interviewed Émile Servan-Schreiber, who argues that cash wagering is not what makes a crowd forecast accurate—and who described The Forecasting Machine’s all-AI system to the paper.

2026-07-14The Forecasting Machine

From NewsFutures to The Forecasting Machine: 25 Years in Newsrooms

Agenda Pública’s live AI-forecast integration continues a media-forecasting story that began when NewsFutures probabilities appeared inside USA TODAY articles.

2026-07-08The Forecasting Machine

Prediction markets can work without money on the line: Servan-Schreiber in Bloomberg Opinion

In a Bloomberg Opinion essay on 8 July 2026, Émile Servan-Schreiber revisited a 2003 wager with Justin Wolfers over French and California wine. The bet became a study showing that play-money and real-money markets forecast American football equally well, and he argued that design, not money, drives accuracy.

2026-07-03The Forecasting Machine

Zelensky’s resilience: two different generations of Hypermind leadership forecasts

A July 2026 market image puts Zelensky almost level with Putin on who loses power first, and ahead of Trump on staying longer. The 2022 baseline asked different questions.

2026-05-14The Forecasting Machine

“Supercollective Intelligence”: Servan-Schreiber’s 2018 book on crowds and prediction markets comes out in English

The English edition of Émile Servan-Schreiber’s “Supercollectif” is now on Amazon. He argues that ChatGPT and the rise of Polymarket since 2018 support, rather than overturn, the book’s case.

2026-04-23The Forecasting Machine

Hypermind’s April 2026 Senate forecast: almost an even contest

On 23 April 2026, Hypermind’s market put Democratic control of the US Senate at 49.5%. Its House forecast looked very different.

2026-03-05The Forecasting Machine

“The readership is an intelligence asset”: Servan-Schreiber in Agenda Pública on crowds, AI and the press

In a March 2026 interview with Agenda Pública, Émile Servan-Schreiber argued that prediction markets beat polls on method, that AI now forecasts as well as a smart crowd, and that newspapers have wasted what their readers know.

2026-03-04The Forecasting Machine

Hypermind and beBartlet bring prediction markets to European strategic consulting

At Mobile World Congress in Barcelona on 4 March 2026, Hypermind and the Spanish public-affairs consultancy beBartlet announced an exclusive alliance to use crowd forecasting and prediction markets in strategic advice across Europe.

2026-01-15The Forecasting Machine

Hypermind’s Insurrection Act forecast: two snapshots of a long-running risk

Two archived Hypermind charts put the risk of Trump invoking the Insurrection Act near one in two, with a deadline in 2029. The market question and the political warning deserve separate readings.

2026-01-13The Forecasting Machine

Powell would finish his term: Hypermind’s 87% call in January 2026

An archived Hypermind chart put Jerome Powell’s chance of completing his term as Federal Reserve chair at 87.0%. The forecast concerned tenure, rather than the outcome of a criminal investigation.

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