Manifold’s business model didn’t sound like it would work. The platform allows any user to create their own market, it uses a fictional currency instead of real money, and the people who create the markets are in charge of resolving them.
However, Manifold has built a business that has endured since its founding in December 2021. Originally conceived as a company on the Solana blockchain, Manifold’s founders pivoted to a free-to-play model.
“All these other crypto prediction market attempts had these complicated oracles that you had to appeal to and there was a complicated appeals process behind that that just add[ed] a lot of cruft and difficulty to dealing with the markets and we thought the better way was just to let people do whatever they want and then the market itself would select for the people that are creating the good questions and traffic would just naturally flow to them,” Manifold co-founder Stephen Grugett said.
Who’s Using Manifold Markets?
Manifold’s free-to-play model solves a couple of problems. The platform avoids the headaches of crypto infrastructure that’s still in its infancy, and Manifold avoids the regulations that accompany real-money futures markets. Instead, Manifold uses a fictional currency, mana, which it regulates like a real currency.
“Even when you’re playing a game, people need to respect the rules enough in order for gameplay to be fun,” Grugett said. “If people are creating money randomly and haphazardly without any regard to the other rules and the game just ceases to be enjoyable.”
The players creating their own markets and trading in others include industry insiders. Outside of politics, tech and AI are among the most popular topics to create markets on. Markets on when GPT-5’s release date and the date of Sam Altman’s ouster often came from users within those areas of the tech industry.
“I myself have placed trades based upon what I’ve heard from Google or DeepMind people speculating to have added value to the market,” Grugett said. “The nice thing about the market mechanism versus other forecasting mechanisms is that it rewards unique information.”
Prediction markets aren’t just for traders, though. The Effective Altruism movement finds value in a tool that offers snapshots of group opinions about hard issues.
Effective Altruists Want a Crystal Ball
Effective Altruists — EAs — are concerned about how to use their money to create the most good in the world. EAs include devotees such as financial giants, tech gurus, and the Oxford philosopher who wrote the seminal work arguing that individuals should “earn to give.”
“Perhaps the thing that binds everyone in this space is that they view the world in terms of numbers and so quantitative forecasting and prediction markets in particular and Manifold in particular are a good fit for that,” Grugett said.
EAs have also taken an interest in multiple prediction markets. Manifold and Metaculus, a free forecasting platform with no currency, are among the grantees that have benefited from EA investments.
The ability to put a hard number on the possibility of different outcomes is attractive to EAs. In his book On the Edge, Nate Silver notes that many EAs are attracted to utilitarianism, a philosophy that derives its judgment of right and wrong from the outcomes of decisions. Silver quotes a philosopher critical of utilitarianism who believes it “can be seductive to quantitatively inclined people because of its promise of mathematical precision.”
“The reason that they [EAs] care about us versus other forecasting or prediction market platforms is that we have the largest catalog of content on things that EAs value in addition to everything, basically,” Grugett said.
Anyone can create any market on Manifold, so the platform has a catalog that real-money exchanges struggle to match. CFTC regulations prevent derivatives exchanges from offering contracts on the likelihood of war, while Manifold has multiple markets predicting milestones in Ukraine, Gaza, Lebanon, Taiwan, and Iran. Manifold’s focus on prediction rather than real-money payouts allows it to host these markets and others on existential risks that occupy EAs.
Caveats to Reading Prediction Markets
Prediction markets may arrive at a price that captures what the traders believe, but those prices aren’t necessarily good predictions. PredictIt’s market on the 2016 presidential race gave Hillary Clinton an 82% chance of winning on election night before the returns came in.
However, there are two other caveats to reading prediction markets on Manifold: reading conditional markets carefully and extreme prices.
Conditional markets are if/then questions, like “If Biden stepped down, would Kamala win?” Some of Manifold’s common conditionals wonder about CEO firings. Grugett gave the example, “If a CEO stepped down, would the stock price rise?”
“Intuitively, you would think that this is just a measure of how good that CEO is, because if they’re bad and they’re replaced, the stock price would go up,” Grugett said. “But the market is not quite that…You can imagine other worlds where they might be replaced, namely, I don’t know, the CEO dies.…It could be they’re a really good CEO in a bad industry and they might be replaced along with other CEOs.”
The second caveat in Grugett’s mind is extreme pricing. There are certain high points in a market where sell-offs or large purchases are rational. In political markets, the Republican and Democratic conventions were reliable high price points for Donald Trump and Kamala Harris. Both experienced high prices followed by price drops on Polymarket during the conventions. This price drop was likely caused by sell-offs rather than sudden losses of confidence in the people the parties united behind.
“Especially when the probabilities are very extreme, like above 95% or below 5%, then the tails may not be priced correctly just because there are easier ways to get return on your capital,” Grugett said. “So that’s kind of the big one that applies for very improbable events or for events that take place a long time in the future.”
Market Faith
One of the foundational principles Manifold Markets is predicated on is the superiority of market mechanisms. Manifold’s fictional money supply is regulated through small fees to ensure traders’ opinions have similar weights. Across markets and platforms, arbitragers help align prices, with the wisdom of the crowd seemingly at play as Grugett and other prediction market advocates envision.
Manifold’s markets indeed capture the opinions of their traders. Prices reflect its traders’ views. However, questions about where traders get their information and whether prediction markets are being skewed by common misconceptions are something that anyone interested in prediction markets must take seriously.
