science

Prediction market

Prediction market is a science topic covered in the lgStudy science library. This page brings together a partial reference excerpt, illustrations, worked examples, real-world applications and a short study plan, so you can understand Prediction market rather than just read about it. In short: Prediction markets, also known as betting markets, information markets, decision markets, idea futures, or event derivatives, are open markets that enable the prediction of specific outcomes using financial incentives. They are exchange-traded markets established for trading bets in the outcome of various events.

Key takeaways

Prediction market belongs to science; place it in that map before memorising details.
Learn the definition first, then one example that makes the definition concrete.
Connect Prediction market to a quantity you can measure, compute or draw — that is where exam questions come from.
Reproduce the core statement of Prediction market from memory before moving on to harder problems.

Reference excerpt

Prediction markets, also known as betting markets, information markets, decision markets, idea futures, or event derivatives, are open markets that enable the prediction of specific outcomes using financial incentives. They are exchange-traded markets established for trading bets in the outcome of various events. The most common form of a prediction market is a binary option market, which will expire at the price of 0 or 100%. Prediction markets can be thought of as belonging to the more general concept of crowdsourcing which is specially designed to aggregate beliefs on particular topics of interest, where the market price can indicate what the crowd thinks the probability of the event is. Traders with different beliefs trade on contracts whose payoffs are related to the unknown future outcome and the market prices of the contracts are considered as the aggregated belief. Prediction markets are considered gambling by many governments, and are banned in some locations. Some users and researchers have reported that prediction markets are similar to gambling and can cause addiction.

History Before the era of scientific polling, early forms of prediction markets often existed in the form of political betting. One such political bet dates back to 1503, in which people bet on who would be the papal successor. Even then, it was already considered "an old practice". According to Paul Rhode and Koleman Strumpf, who have researched the history of prediction markets, there are records of election betting in Wall Street dating back to 1884. Rhode and Strumpf estimate that average betting turnover per US presidential election is equivalent to over 50 percent of the campaign spend. Economic theory for the ideas behind prediction markets can be credited to Friedrich Hayek in his 1945 article "The Use of Knowledge in Society" and Ludwig von Mises in his "Economic Calculation in the Socialist Commonwealth". Modern economists agree that Mises' argument, combined with Hayek's elaboration of it, is correct. Prediction markets are championed in James Surowiecki's 2004 book The Wisdom of Crowds, Cass Sunstein's 2006 Infotopia, and Douglas Hubbard's How to Measure Anything: Finding the Value of Intangibles in Business.

Milestones One of the first modern electronic prediction markets is the University of Iowa's Iowa Electronic Markets, introduced during the 1988 US presidential election. HedgeStreet was the first prediction market to seek approval by the Commodity Futures Trading Commission as a designated contract market after the Commodity Futures Modernization Act of 2000, and it was granted in 2004. The exchange was acquired by the United Kingdom–based IG Group and rebranded to Nadex in 2007; Nadex was then acquired by Crypto.com in 2021. In July 2003, the U.S. Department of Defense publicized a Policy Analysis Market on their website, and speculated that additional topics for markets might include terrorist attacks. A critical backlash quickly denounced the program as a "terrorism futures market" and the Pentagon hastily canceled the program. In 2005, an article in Nature stated how major pharmaceutical company Eli Lilly and Company used prediction markets to help predict which development drugs might have the best chance of advancing through clinical trials by using internal markets to forecast outcomes of drug research and development efforts. Also in 2005, Google announced that it had been using prediction markets to forecast product launch dates, new office openings, and many other things of strategic importance. Other companies, such as HP and Microsoft, also conduct private markets for statistical forecasts. Starting around 2022, mainstream adoption of prediction markets Polymarket and Kalshi began. In October 2024, the Kalshi prediction market won a lawsuit against the Commodity Futures Trading Commission, allowing it to relist its election prediction markets. Kalshi's court victory led to a much broader range of prediction markets offered on their platform and by competitors.

Core Concepts and Mechanics

General Mechanics Prediction markets are financial markets made up of binary contracts that resolve based on whether certain events happen or not. These contracts are usually exchange traded through a free floating order book system. The price of such contracts are set between $0.01 and $1 and represent the odds of an event occurring. Each event will have a “Yes” or “No” tradable contract. For example, if a “Yes” contract around an event occurring has a market price of $0.93 then the market is implying that there is a 93% that this event will take place. In the same way the “No” contract in the same market will have a price of $0.07 and thus the market thinks this event has a 7% chance of occurring. The free-floating central limit order book (CLOB) has shown to be an incredibly efficient mechanism for matching pure supply and demand by giving participants the ability to submit trades at whatever price they choose and only being able to take on a trade or prediction if another market participant disagrees.

… excerpt ends here. Continue reading the full article.

Worked examples

Example 1 — a first encounter with Prediction market

Start with the simplest possible case. Write down what Prediction market claims or describes in one sentence, then invent the smallest concrete situation in which that sentence is true. In science, the smallest case is usually a single object, a single equation or a single measurement. Check that every symbol or term in your sentence has a meaning in that case.

Example 2 — changing one variable

Take the situation from Example 1 and change exactly one quantity: double it, halve it, or set it to zero. Predict what should happen to Prediction market before you calculate. Comparing your prediction with the result is the fastest way to find out whether you understand the idea or only the words.

Example 3 — an exam-style question

Typical questions about Prediction market ask you to (a) state it precisely, (b) apply it to given data, and (c) explain a limitation. Practise writing all three answers in under five minutes; the third part is what separates a full-mark answer from an average one.

Applications of Prediction market

In research: Prediction market appears in science research whenever the underlying quantities have to be modelled precisely. Papers usually cite it as a starting assumption and then explore where it breaks down.
In technology and industry: Engineering practice reuses Prediction market in design rules, simulations and safety margins. Knowing the idea lets you read a specification sheet and understand why the numbers look the way they do.
In the classroom: Prediction market is common in secondary-school and first-year university syllabi. It links to neighbouring topics Forecasting, Market (economics), Prediction markets, so understanding it makes those chapters shorter.
In everyday life: Look for Prediction market outside the textbook — in sport, cooking, traffic, electronics or the sky above you. An example you found yourself is remembered far longer than one you were given.

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How to study Prediction market in 20 minutes

Read the reference excerpt below once, without taking notes.
Close the page and write down what Prediction market means in your own words.
Compare your version with the excerpt and mark what you missed.
Work through the three examples above with pen and paper.
Explain Prediction market out loud to somebody else — or to Teacher Smith in the lgStudy chat.

Frequently asked questions

What is Prediction market in simple terms?

Why does Prediction market matter?

Because it connects several science ideas at once: it gives you a definition you can apply, a quantity you can calculate, and a way to check whether a result is plausible.

How should I study Prediction market?

Read the excerpt, restate it from memory, then work through the examples and applications listed on this page. The five-step study plan above takes about twenty minutes.

What does this page cover?

It gives you a compact reference excerpt plus original lgStudy explanations, examples, applications and study material on Prediction market.