A prediction market is a market in which participants trade contracts whose payoff depends on the outcome of a future event. A simple example illustrates the idea:<\/p>\n\n\n\n
A contract pays $1 if Candidate A wins the election, and $0 otherwise.<\/em><\/p>\n\n\n\n If that contract trades at 65 cents, the market is effectively saying there is a 65% chance that Candidate A will win. This probability interpretation is not metaphorical. Under very general conditions, prices in these markets reflect the collective beliefs of participants, weighted by how confident they are and how much they are willing to risk. This is the power of prediction markets: money talks.<\/p>\n\n\n\n Crucially, participants do not need to hold a prediction contract until the event is resolved. If you purchase the contract above for 65 cents and, a few days later, it trades at 70 cents, you can sell it for a 5-cent profit. This ability to trade in and out of positions makes prediction markets far more like financial markets than traditional betting.<\/p>\n\n\n\n Prediction markets have existed in various forms for decades, from informal election betting in the 19th century to modern platforms covering politics, economics, weather, and even pop culture. What is new is their massive scale, which has been driven by technology, and their increasing entanglement with financial regulation.<\/p>\n\n\n\n At their core, however, prediction markets treat beliefs as tradable financial assets. Before prediction markets, betting on an event typically meant going to Las Vegas or placing a wager with a bookie. Prediction markets, by contrast, allow participants to trade positions as beliefs evolve and to profit from changes in perceived likelihoods. In this sense, they resemble markets for stocks or cryptocurrencies more than casinos.<\/p>\n\n\n\n This characterization matters, as financial theory has long emphasized that markets are powerful information-aggregation mechanisms because they reward accuracy and penalize error. As Friedrich Hayek <\/a>famously argued, market prices reflect information that is dispersed across many individuals, information that no single person fully possesses.<\/p>\n\n\n\n Prediction markets are not just forecasting tools; they are decision-support tools. In principle, they can improve decisions wherever uncertainty matters. Governments could use them to assess policy outcomes. Firms could use them to forecast demand, project completion timelines, or regulatory risk. Organizations could use them internally to surface uncomfortable truths that hierarchical structures often suppress.<\/p>\n\n\n\n In this sense, prediction markets are close cousins of financial markets. Just as stock prices summarize expectations about firms, prediction market prices summarize expectations about events.<\/p>\n\n\n\n There is also a democratic element to prediction markets in that they flatten expertise. Anyone can participate and profit from being correct. Credentials, status, or pedigree do not matter. Only accuracy does.<\/p>\n\n\n\n Unsurprisingly, prediction markets have attracted significant regulatory attention, and their legal status is evolving rapidly. These markets straddle several regulatory categories. On the one hand, they can resemble gambling, since participants can \u201cbet\u201d on outcomes like sporting events. On the other hand, they can be viewed as derivatives. From this latter perspective, a prediction market contract is essentially a forward contract on an event outcome. It has a well-defined payoff at a future date, a market price today, and can be traded as beliefs change. What is \u201cdelivered\u201d at settlement is not a commodity or a security, but a realized fact.<\/p>\n\n\n\n The regulation of prediction markets is therefore somewhat of a gray area. In the United States, The Commodity Futures Trading Commission<\/a> (CFTC) has become increasingly involved. Polymarket<\/a> was prohibited from operating in the U.S., but has since secured CFTC approval, subject to agreements and a potentially phased rollout. Other platforms such as Predictit<\/a> and Kalshi<\/a> operate under agreements with the CFTC. This regulatory landscape is changing very rapidly.<\/p>\n\n\n\n Beyond regulation, prediction markets raise ethical concerns. Should people be allowed to profit from events such as wars or elections? To what extent can these markets be manipulated by deep-pocketed traders?<\/p>\n\n\n\n A more subtle, and potentially more troubling issue, is whether prediction markets influence the very outcomes they seek to predict. If a market assigns a 70% probability to a particular candidate winning, could that discourage voter turnout or shape public perception? These concerns are not unique to prediction markets and have long existed in financial markets more generally<\/p>\n\n\n\n Prediction markets are perhaps best understood not as casinos, but as democratized information machines that convert many individual opinions into probabilities through economic incentives. Financial economics repeatedly shows that when people are willing to stake money on their beliefs, whether about the value of a company or the outcome of an election, these markets tend to produce forecasts that are both disciplined and remarkably accurate.<\/p>\n\n\n Featured expert<\/p>\n Richard Warr<\/em><\/a> is a professor of finance and associate dean for faculty and research. His scholarship focuses on finance, the stock market, inflation, cryptocurrencies and investing.<\/em><\/p>\n \n\n\n <\/div>\n <\/div>\n\n\n <\/div>\n<\/div>","protected":false,"raw":"\n\n\n\n\n Prediction markets are all over the news. They often resemble gambling or speculation in that they allow participants to bet on an almost unimaginable range of events, from who will win the Super Bowl to what the weather will be like in London next month. But these markets do more than entertain or speculate, they aggregate information and produce forecasts that are frequently far superior to those generated by opinion polls or experts.<\/p>\n\n\n\n A prediction market is a market in which participants trade contracts whose payoff depends on the outcome of a future event. A simple example illustrates the idea:<\/p>\n\n\n\n A contract pays $1 if Candidate A wins the election, and $0 otherwise.<\/em><\/p>\n\n\n\n If that contract trades at 65 cents, the market is effectively saying there is a 65% chance that Candidate A will win. This probability interpretation is not metaphorical. Under very general conditions, prices in these markets reflect the collective beliefs of participants, weighted by how confident they are and how much they are willing to risk. This is the power of prediction markets: money talks.<\/p>\n\n\n\n Crucially, participants do not need to hold a prediction contract until the event is resolved. If you purchase the contract above for 65 cents and, a few days later, it trades at 70 cents, you can sell it for a 5-cent profit. This ability to trade in and out of positions makes prediction markets far more like financial markets than traditional betting.<\/p>\n\n\n\n Prediction markets have existed in various forms for decades, from informal election betting in the 19th century to modern platforms covering politics, economics, weather, and even pop culture. What is new is their massive scale, which has been driven by technology, and their increasing entanglement with financial regulation.<\/p>\n\n\n\n At their core, however, prediction markets treat beliefs as tradable financial assets. Before prediction markets, betting on an event typically meant going to Las Vegas or placing a wager with a bookie. Prediction markets, by contrast, allow participants to trade positions as beliefs evolve and to profit from changes in perceived likelihoods. In this sense, they resemble markets for stocks or cryptocurrencies more than casinos.<\/p>\n\n\n\n This characterization matters, as financial theory has long emphasized that markets are powerful information-aggregation mechanisms because they reward accuracy and penalize error. As Friedrich Hayek <\/a>famously argued, market prices reflect information that is dispersed across many individuals, information that no single person fully possesses.<\/p>\n\n\n\n Prediction markets are not just forecasting tools; they are decision-support tools. In principle, they can improve decisions wherever uncertainty matters. Governments could use them to assess policy outcomes. Firms could use them to forecast demand, project completion timelines, or regulatory risk. Organizations could use them internally to surface uncomfortable truths that hierarchical structures often suppress.<\/p>\n\n\n\n In this sense, prediction markets are close cousins of financial markets. Just as stock prices summarize expectations about firms, prediction market prices summarize expectations about events.<\/p>\n\n\n\n There is also a democratic element to prediction markets in that they flatten expertise. Anyone can participate and profit from being correct. Credentials, status, or pedigree do not matter. Only accuracy does.<\/p>\n\n\n\n Unsurprisingly, prediction markets have attracted significant regulatory attention, and their legal status is evolving rapidly. These markets straddle several regulatory categories. On the one hand, they can resemble gambling, since participants can \u201cbet\u201d on outcomes like sporting events. On the other hand, they can be viewed as derivatives. From this latter perspective, a prediction market contract is essentially a forward contract on an event outcome. It has a well-defined payoff at a future date, a market price today, and can be traded as beliefs change. What is \u201cdelivered\u201d at settlement is not a commodity or a security, but a realized fact.<\/p>\n\n\n\n The regulation of prediction markets is therefore somewhat of a gray area. In the United States, The Commodity Futures Trading Commission<\/a> (CFTC) has become increasingly involved. Polymarket<\/a> was prohibited from operating in the U.S., but has since secured CFTC approval, subject to agreements and a potentially phased rollout. Other platforms such as Predictit<\/a> and Kalshi<\/a> operate under agreements with the CFTC. This regulatory landscape is changing very rapidly.<\/p>\n\n\n\n Beyond regulation, prediction markets raise ethical concerns. Should people be allowed to profit from events such as wars or elections? To what extent can these markets be manipulated by deep-pocketed traders?<\/p>\n\n\n\n A more subtle, and potentially more troubling issue, is whether prediction markets influence the very outcomes they seek to predict. If a market assigns a 70% probability to a particular candidate winning, could that discourage voter turnout or shape public perception? These concerns are not unique to prediction markets and have long existed in financial markets more generally<\/p>\n\n\n\n Prediction markets are perhaps best understood not as casinos, but as democratized information machines that convert many individual opinions into probabilities through economic incentives. Financial economics repeatedly shows that when people are willing to stake money on their beliefs, whether about the value of a company or the outcome of an election, these markets tend to produce forecasts that are both disciplined and remarkably accurate.<\/p>\n\n\n\n\n\n\n"},"excerpt":{"rendered":" Prediction markets inform and entertain. Poole scholar Richard Warr explains how they work and what they mean to the economy.<\/p>\n","protected":false},"author":50146,"featured_media":34727,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"source":"","ncst_custom_author":"Richard Warr","ncst_show_custom_author":true,"ncst_dynamicHeaderBlockName":"ncst\/default-post-header","ncst_dynamicHeaderData":"{\"caption\":\"A digital ad for the prediction market Kelshi shows probabilities for the New York City mayoral election.\",\"displayCategoryID\":162,\"showAuthor\":true,\"showDate\":true,\"showFeaturedVideo\":false,\"subtitle\":\"Gambling? Speculation? Prediction markets share aspects with both, but they're best understood as a way of converting individual opinions into probabilities.\"}","ncst_content_audit_freq":"","ncst_content_audit_date":"","ncst_content_audit_display":false,"ncst_backToTopFlag":"","footnotes":""},"categories":[105,162,77],"tags":[541,384,566],"_ncst_magazine_issue":[],"series":[],"class_list":["post-34726","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-finance","category-issues-and-insights","category-newswire","tag-christina-lewellen","tag-gambling","tag-richard-warr"],"displayCategory":{"term_id":162,"name":"Issues and Insights","slug":"issues-and-insights","term_group":0,"term_taxonomy_id":162,"taxonomy":"category","description":"Get the latest data, analysis and predictions from experts in the world of business as they identify the opportunities and threats that should inform your decisions.","parent":0,"count":37,"filter":"raw"},"acf":{"ncst_posts_meta_modified_date":null},"_links":{"self":[{"href":"https:\/\/poole.ncsu.edu\/thought-leadership\/wp-json\/wp\/v2\/posts\/34726","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/poole.ncsu.edu\/thought-leadership\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/poole.ncsu.edu\/thought-leadership\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/poole.ncsu.edu\/thought-leadership\/wp-json\/wp\/v2\/users\/50146"}],"replies":[{"embeddable":true,"href":"https:\/\/poole.ncsu.edu\/thought-leadership\/wp-json\/wp\/v2\/comments?post=34726"}],"version-history":[{"count":7,"href":"https:\/\/poole.ncsu.edu\/thought-leadership\/wp-json\/wp\/v2\/posts\/34726\/revisions"}],"predecessor-version":[{"id":34866,"href":"https:\/\/poole.ncsu.edu\/thought-leadership\/wp-json\/wp\/v2\/posts\/34726\/revisions\/34866"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/poole.ncsu.edu\/thought-leadership\/wp-json\/wp\/v2\/media\/34727"}],"wp:attachment":[{"href":"https:\/\/poole.ncsu.edu\/thought-leadership\/wp-json\/wp\/v2\/media?parent=34726"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/poole.ncsu.edu\/thought-leadership\/wp-json\/wp\/v2\/categories?post=34726"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/poole.ncsu.edu\/thought-leadership\/wp-json\/wp\/v2\/tags?post=34726"},{"taxonomy":"_ncst_magazine_issue","embeddable":true,"href":"https:\/\/poole.ncsu.edu\/thought-leadership\/wp-json\/wp\/v2\/_ncst_magazine_issue?post=34726"},{"taxonomy":"series","embeddable":true,"href":"https:\/\/poole.ncsu.edu\/thought-leadership\/wp-json\/wp\/v2\/series?post=34726"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}The Role of Prediction Markets in the Economy<\/strong><\/h3>\n\n\n\n
Regulatory and Ethical Concerns<\/strong><\/h3>\n\n\n\n
Think Computers, Not Casinos<\/strong><\/h3>\n\n\n\n
![\"\"](\"https:\/\/poole.ncsu.edu\/thought-leadership\/wp-content\/uploads\/sites\/423\/2024\/12\/BUS-Warr-Richard_MH19186.jpg\")
\n <\/figure>\n Richard Warr<\/h3>\n
How Do Prediction Markets Work?<\/strong><\/h3>\n\n\n\n
The Role of Prediction Markets in the Economy<\/strong><\/h3>\n\n\n\n
Regulatory and Ethical Concerns<\/strong><\/h3>\n\n\n\n
Think Computers, Not Casinos<\/strong><\/h3>\n\n\n\n