Betting Exchanges, Prediction Markets, and Crypto Event Contracts
Trading on exchange-style betting markets differs from simply placing a wager with a conventional bookmaker. The underlying subject might still be a football match, election, economic announcement, or cryptocurrency price, but an exchange-style betting market allows participants to buy and sell positions as expectations change. A trader can therefore profit from a movement in the market price without necessarily holding the original position until the event finishes.
This makes some betting markets behave surprisingly similar to financial markets. Prices respond to information, buyers and sellers meet through order books, liquidity affects execution, and the difference between buying and selling prices creates a spread. The terminology changes according to the platform, but much of the underlying trading logic will be familiar to anyone who has traded shares, futures, or exchange-traded derivatives. Traders can take directional positions, provide liquidity, or close a position after the market has moved in their favour. The trader can even close a losing position, to limit their loss, a risk-management technique well known among conventional financial traders.
What Does Trading on a Betting Market Mean?
Traditional Bookmaking vs. Betting Markets
A traditional bookmaker offers odds and takes the customer’s bet. The bookmaker generally has financial exposure to the result. A betting exchange uses a different structure. It provides a venue where customers can take opposing sides of the same wager. The UK Gambling Commission defines a betting exchange as a platform designed to facilitate bets between other parties, rather than becoming a party to those bets itself.
That change allows odds to behave like tradable prices. A participant can offer a price rather than simply accepting one supplied by a bookmaker. Other participants decide whether they are willing to trade at that level. If new information changes expectations, available prices move. Someone who entered earlier can take an opposing position later and potentially lock in part or all of the price movement.
The trader is trying to estimate whether the current market price incorrectly reflects the probability of an outcome. A strong opinion about the outcome itself is not enough. If the market already prices the event more aggressively than your own estimate, the trade may offer poor value even though you still believe the event is likely to happen.
For traders, the most useful habit is now to ignore the product label for a moment and inspect the mechanics. Ask how the price is formed, how the position can be closed, how much liquidity exists, what determines settlement and what happens if the prediction is wrong. Those questions reveal far more about the real risk than whether the website calls the product a bet, an event contract, a prediction share, or a binary option.
Betting Markets as Information Markets
Betting and prediction markets can provide useful information, since a liquid market aggregates the views of participants who have different data, models, and incentives. Election markets can show changes in political expectations, while economic event contracts can reflect how traders assess the probability of inflation or interest-rate outcomes. The quality of that signal depends on participation. A market with deep liquidity and narrow spreads contains more meaningful information than one where a single small trade moves the displayed probability by twenty percentage points. This is another area where active and knowledgable traders have an advantage over casual observers. Rather than reading a displayed probability as fact, they can examine the depth, spread and recent order flow behind it. The market is expressing a price, not issuing a guarantee.
The displayed probability is only as informative as the market behind it. Traders should distinguish between a genuine repricing caused by new information and a temporary price movement caused by thin liquidity or a small number of aggressive orders. A market may also be influenced by traders who are hedging other positions, managing risk, or expressing views for reasons that have little to do with maximizing forecast accuracy. The price therefore represents the outcome of trading activity, not a pure consensus forecast.
For traders, this distinction matters because an apparently attractive probability can be misleading. A contract trading at 70% does not necessarily mean that the event has a 70% “true” probability, nor does it mean that buying at that price is attractive. The relevant question is whether the trader’s own assessment of the probability is sufficiently different from the market price to compensate for the spread, fees, liquidity constraints, and risk of being wrong. In this sense, prediction markets can be viewed not only as sources of information, but also as markets in which traders attempt to identify when the available information has been mispriced.
Backing and Laying on a Betting Exchange
Backing vs. Laying
The two basic actions on a conventional betting exchange are backing and laying. Backing means betting that an outcome will happen. Laying means taking the opposite position and accepting another participant’s bet that the outcome will happen. A trader can therefore “sell an outcome” without first owning it in much the same conceptual way that financial traders can take short exposure.
Suppose a football team is available to back at decimal odds of 3.00. A £100 back bet produces £200 of gross profit if the team wins, with the £100 stake also returned. If the team loses, the £100 stake is lost. The quoted odds can also be converted into a rough implied probability by dividing one by the decimal price. Odds of 3.00 imply approximately 33.3%, before accounting for commission, spreads, and other market effects.
A lay position reverses the relationship. If a trader lays a team at 3.00 against a £100 opposing stake, the potential profit is £100 if the team does not win, while the liability is £200 if it does. Lay liability can therefore exceed the amount shown as the opposing stake. For traders, it is important to understand that a £100 lay transaction does not necessarily mean £100 is the maximum amount at risk.
Betting Odds as Market Prices
Treating odds as prices makes exchange trading easier to understand. Decimal odds of 2.00 correspond to a simple 50% implied probability, 4.00 to 25%, and 1.25 to 80%. If an outcome becomes more likely, its decimal odds shorten. If it becomes less likely, the odds lengthen.
Imagine a tennis player trading at 4.00 before a match. A trader believes the market has underestimated that player’s prospects and backs at 4.00. The player then wins the opening set and available odds fall to 2.20. The trader does not need to keep the original position open until the final point. A lay order at the lower odds can reduce the exposure or distribute profit across both possible match outcomes.
This is the basic reason exchange betting can be traded rather than simply wagered upon. The final event remains important, but the trader can focus on how the market’s probability assessment changes before settlement. Someone can make a profitable price trade and later turn out to have been completely wrong about the eventual winner.
Back-to-Lay and Lay-to-Back Trading
A back-to-lay trade begins by backing an outcome and later laying it at shorter odds. In implied-probability terms, the trader buys when the market assigns a lower chance to the event and sells after that perceived chance increases. A “horse race trader” might back a horse at 6.00 before a race and lay at 3.50 after the horse starts strongly. The trade is successful because the price shortened, not because the horse necessarily wins.
Lay-to-back trading works in reverse. A trader lays an outcome when the odds appear too short and hopes to buy back later at longer odds. A football team may start at 1.60 but struggle badly during the opening twenty minutes. If its price moves to 2.10, someone who laid at the lower odds can place a back bet at the higher price and reduce or close the liability.
These strategies resemble ordinary long and short trading, but there is one important difference. The contract eventually resolves around an event rather than than continuously following the shifting market value of an asset. A company’s share can continue trading for decades. A match market eventually stops, settles, and disappears. Time therefore plays a much more explicit role in betting-market prices.
Trading Out Before Settlement
The ability to close a position is one of the main differences between exchange betting and a simple fixed wager. A trader can place an opposing transaction once the market moves and attempt to create an acceptable result before the event finishes. Depending on stake calculations, the profit can be concentrated on one outcome or distributed across several outcomes.
This creates a market for changing expectations. A trader who buys a political candidate at an implied probability of 30% and sells when the market reaches 45% can profit without waiting for election night. The same logic applies to an economic event contract or a football market. The important question becomes whether the trader can enter and later find enough liquidity to exit at a favourable price.
The ability to trade out is not guaranteed, because the second transaction may never become available. A market can move directly against the original position, or liquidity can disappear. Until the offsetting position is actually matched, the trader still carries directional exposure to the underlying event.
Liquidity Matters More Than the Headline Odds
A displayed betting price means little to the trader if almost no money is available at that level. This is the same problem conventional financial traders encounter when looking at thinly traded shares or other instruments. A quoted price can appear attractive while being available for only a very small stake.
Suppose the best lay price is 2.00, but only £25 is offered there. A trader trying to place £2,000 cannot assume the complete order will execute at the headline price. The first £25 may be matched at 2.00 while the remainder has to trade at worse levels. The trader’s average execution price can therefore be materially worse than the headline price shown at the top of the order book.
This is essentially a form of slippage; the difference between the price a trader sees and the average price at which the desired position can actually be executed. The larger the order relative to the available liquidity, the greater the potential slippage. Large betting-market traders therefore need to watch the depth of the order-book before deciding how much capital can realistically be deployed.
Liquidity also matters when a position needs to be closed. A market can appear sufficiently liquid when entering a trade but become much thinner after a major piece of information causes prices to move sharply. A trader who needs to exit quickly may then have to accept substantially worse prices, particularly if other participants are trying to exit at the same time.
For retail traders, this creates an important distinction between theoretical value and executable value. Finding a market that appears to offer attractive odds is only the first step. The relevant question is whether those odds are available in sufficient size to make the trade worthwhile after accounting for the spread, fees, and potential slippage. In thin markets, the price shown on the screen may describe what one small order can trade at, rather than what the trader can actually buy or sell. For a trader, it is important to never confuse “the market is trading at X” with “I can trade my desired amount at X.”
Spreads and Commissions
Betting Markets Have Spreads
An exchange has a back and lay spread in much the same way that securities markets have bid and ask prices. If the best available back price is 2.02 and the best lay price is 2.08, a participant immediately crossing both sides would lose money even if the broader market did not move.
The size of this spread is heavily connected to liquidity. Large sporting events close to kickoff can attract substantial money and relatively tight pricing. Smaller leagues, obscure events and markets opened far in advance may show much wider gaps. The spread should therefore be treated as a trading cost even where the exchange does not explicitly describe it as a fee.
A strategy built around frequent small price changes can be particularly vulnerable. If the expected gain from an average trade is smaller than the spread, commission and occasional slippage, the strategy can look active while steadily transferring money to other market participants and the platform.
Commissions and the Real Break-Even Point
Betting exchanges often charge commission on profitable markets, while event exchanges can use transaction fees or maker and taker pricing. A grossly profitable trading record can therefore produce a considerably smaller net return, when all costs are considered.
The exact fee model varies by entity and jurisdiction. Traders should account for commission, spreads, slippage and any additional payment costs before deciding whether a strategy has an advantage. A trader whose average theoretical edge is only a few basis points cannot afford to ignore small charges simply because the individual numbers look insignificant.
The problem becomes more severe as turnover increases. Day trading a betting exchange hundreds of times produces far more friction than placing a handful of longer-term positions. Higher frequency is useful only if the trading advantage survives the cost of repeatedly crossing or providing the market.
In-Play Trading and Latency
In-play markets provide the clearest example of betting behaving like high-speed trading. A football goal, tennis break of serve, or cricket wicket can reprice the entire market within seconds. Traders can react to what is happening rather than relying exclusively on pre-event analysis. The problem is that not everyone receives information at the same time. Broadcast television and online streams can be delayed. Traders using faster data feeds or attending the venue may know what has happened before someone watching from home. By the time a television viewer sees a goal and attempts to trade, the exchange may already have repriced the event. This is an information-latency problem rather than a forecasting problem.
A trader can react correctly to the event and still receive a poor price because someone else reacted first. In very fast markets, the quality and timing of the information source can matter as much as the interpretation of the event itself. For traders, this creates an important limitation. Being fast enough to notice an event is not the same as being fast enough to trade on it. There may be several stages between an event occurring and an order being matched. The event must first be observed, transmitted through a data or broadcast feed, processed by the trader, converted into an order, sent to the exchange, and finally matched against available liquidity. Each stage introduces some delay.
Latency can also create the illusion of opportunity. A trader may see a price that appears to have remained unchanged after an important event and assume that the market has not reacted yet. In reality, the displayed price may already be stale, the available liquidity may have disappeared, or the order may be rejected or remain unmatched while the market reprices. Attempting to “beat the market” by reacting to information visible on a delayed broadcast is therefore considerably harder than it appears. For traders who already have experience from fast-paced trading on conventional financial broker platforms online, the core problem is well-known.
The suspension mechanism used by many betting exchanges is another important consideration. When a major event occurs, such as a goal or a penalty, the exchange may temporarily suspend the market to prevent trading while the new information is incorporated. When trading resumes, prices can be substantially different from where they were before the suspension. A retail trader should therefore not assume that an order submitted immediately before or during a suspension will necessarily be matched at the expected price. The suspension is broadly comparable to a trading halt or volatility interruption on a stock exchange.
Combined, all these factors make in-play trading particularly unforgiving for inexperienced traders. A useful starting point is to understand the limitations of one’s own information source before attempting to trade very short-term movements. If you are watching a delayed television broadcast, and trading through your home internet connection, competing against participants with faster feeds and better internet infrastructure is generally an unfavourable setup. Novice traders can typically find greater opportunities in slower-moving markets, where analysis, probability assessment, and disciplined execution matter more than milliseconds.
Latency should be viewed as a structural trading cost, even though no explicit fee is charged for it. A trader who consistently receives prices after the market has already moved is effectively paying for that delay through poorer execution. This is why experienced large-scale in-play traders tend to invest heavily in data quality, connectivity, and execution infrastructure. For a small-scale hobby trader, the lesson is not necessarily to replicate that infrastructure (it would be prohibitively expensive), but to recognize when the market’s speed makes the trader’s informational disadvantage too large to overcome.
Market Making
Exchange traders do not have to accept available prices. They can submit limit-style orders and wait for another participant to trade against them. This means some traders act more like market makers than directional punters. They continuously offer prices on both sides and attempt to earn from the spread.
Market making works best where there is enough turnover to repeatedly buy and sell positions. The spread provides potential compensation for supplying liquidity, but earning that spread is uncertain because liquidity providers face inventory risk, execution risk, and adverse selection. Someone with better information can trade against a stale quote immediately after conditions change. This is known as adverse selection. A resting order often receives the most attention precisely when it has become badly priced. A market maker offering odds before an unexpected team announcement may suddenly find every order filled because other traders learned the news first. Providing liquidity therefore requires quick repricing and strict exposure control.
For a retail trader, the key lesson is that a filled limit order is not necessarily a sign that you got a good deal. If your order is filled unusually quickly, especially during a fast-moving market, it may be because other participants are happy to trade with you at that price. The question is not simply whether you captured the spread, but whether the price continues to move in your favour after the trade. This is why liquidity provision can look attractive on paper while producing poor results in practice. The spread earned on many small trades can be outweighed by a smaller number of adverse moves.
How Prediction Markets Are Taking Betting-Market Trading Beyond Sports
Prediction-Markets
Prediction markets apply similar trading mechanics to future events that may have nothing to do with sport. Contracts can for instance ask whether a candidate will win an election, whether inflation will exceed a threshold, whether a central bank will change interest rates, or whether Bitcoin will finish above a particular price.
In the United States, the CFTC describes prediction-market products as event contracts and notes that they are commonly structured as swaps. Many use yes-or-no outcomes, meaning the contract ultimately pays according to whether a defined event occurred.
A market price of $0.65 for YES is generally interpreted as roughly a 65% implied probability. If the event occurs, the winning contract may settle at $1. If it fails, the contract settles at zero. Traders can still buy and sell before that settlement, so the price moves continuously even though the final payoff is binary.
How Prediction-Market Prices Are Formed
A prediction contract does not need an operator to declare that an event has a 63% chance of happening. Buyers and sellers establish that price through the order book. On Polymarket, for example, the displayed probability is generally derived from the midpoint between bid and ask prices where the spread is reasonably tight. Polymarket’s current pricing documentation explains that the system switches to the last traded price when the spread becomes unusually wide. This matters because a displayed probability is not an objective scientific estimate. A market showing 60% might actually have bids at 56 and offers at 64. That gap represents disagreement and transaction friction. Thin markets can display an apparently precise percentage while having very little capital supporting the price. The sensible way to read the contract is therefore to examine the order book rather than relying entirely on the prominent probability number. A 60% price backed by millions in competing orders carries different informational weight from one created by a handful of small trades.
Trading the Change in Probability
Prediction-market traders often care more about repricing than final settlement. Suppose a contract asks whether a central bank will cut rates at its next meeting. YES trades at $0.30. A trader believes the market is underestimating the probability and buys. Economic data then weakens, central-bank commentary turns softer, and YES rises to $0.58. The trader can sell before the meeting takes place. The contract might eventually resolve NO, but the original trade can still have been profitable because the market repriced in the expected direction while the trader held it.
This is the feature that makes prediction markets genuinely tradable. A classic punter thinks mainly about whether the event will happen. A trader also thinks about how other participants will update their expectations before the answer becomes known.
Crypto-Based Prediction Markets
Blockchain Infrastructure
Crypto-based prediction markets use blockchain infrastructure and stable-coins or tokenised outcome shares to implement the event-contract idea. The underlying question can for instance concern politics, sport, economics, or cryptocurrency exchange rates.
On platforms such as Polymarket, YES and NO positions can be represented through outcome shares backed by collateral. The winning side becomes redeemable for the full settlement amount after resolution, while the losing side becomes worthless. Polymarket’s current resolution documentation states that its markets follow predefined rules and currently use the UMA Optimistic Oracle in the resolution process.
Blockchain settlement can make parts of the collateral and transaction structure more visible, but it adds risks that do not exist in exactly the same form on a conventional betting exchange. Factors such as wallet security, smart contracts, stable-coin infrastructure, and oracle resolution can become part of the risk assessment.
Crypto Price Prediction Contracts vs. Binary Options On Crypto
For many traders, one of the most interesting developments within this field has been the rise of short-duration crypto prediction contracts. In many ways, these contracts are very similar to binary options based on cryptocurrency. Retail binary options rose sharply in popularity during the 2010s, particularly in the mid-to-late part of the decade, before regulators in many countries either banned them or imposed heavy restrictions.
A market asking whether Bitcoin will finish above a specified price in 5 minutes may trade through an order book and use blockchain collateral, but its final $1-or-zero payoff makes it very similar to a short-term binary option. That does not make every prediction market identical to the old binary-options industry. Exchange pricing, secondary trading, transparent order books, and market-based counterparties can create meaningful structural differences. Those differences shrink, however, as expiry becomes shorter and the contract is reduced to a yes-or-no financial price at one precise moment.
Consider a contract asking whether Bitcoin will be above $125,000 at 16:00 UTC on Friday. A YES share might trade at $0.55 and settle at $1 if the condition is satisfied. This is very different from buying Bitcoin. If BTC finishes at $125,001, the YES contract wins. If it finishes at $150,000, the contract still pays the same $1 settlement value. Additional upside in Bitcoin does not create a larger terminal payout. The same discontinuity applies on the downside. Bitcoin at $124,999 results in a loss of 100% of the stake, even though the difference from the winning price is minimal. The underlying asset moves continuously, but the prediction contract compresses that movement into a binary condition at settlement.
The resemblance becomes stronger as the expiry becomes shorter. A six-month event contract can move repeatedly as traders process new information. A five-minute Bitcoin-above-strike contract leaves far less time for repricing and behaves mainly as a bet on where the asset will sit at one exact point. That is almost the same economic problem presented by short-duration binary options. The trader chooses whether an underlying market will finish above or below a strike at a defined expiry. A correct prediction earns a fixed amount and an incorrect one loses the stake or contract value.
The user interface may look different. One platform may call the position a YES share and another a call binary. One may use stable-coin collateral and an order book, while another quotes a fixed payout in USD. Those differences matter operationally, but the terminal payoff and underlying mechanics can be nearly identical.
A simple Bitcoin example:
Assume BTC is trading around $100,000 and a one-minute event contract asks whether it will finish above $100,050. YES is offered at $0.48. A trader buys 100 contracts for $48 before fees. If the official settlement source records BTC at $100,051 at expiry, the contracts become worth $100 in total, giving a gross gain of $52. If the settlement price is $100,049, the same contracts become worthless and the $48 is lost. Only two dollars separate those underlying outcomes, yet the contract result changes by $100. This cliff-like settlement is the defining feature of a binary payoff. The trader is not primarily trading how far Bitcoin moves. The trader is trading which side of a threshold it occupies at a predetermined time.
Prediction Shares Can Still Be More Flexible Than Traditional Binaries, But Lifespan Matters
The similarities explained above does not mean prediction exchanges and old-style binary-option brokers are identical. A liquid event exchange can offer considerably more control before expiry. The trader can submit a limit order, sell part of a position, reverse direction or leave a resting order at a better price. Many older retail binary platforms gave the customer a quoted payout and little meaningful secondary-market liquidity. The customer placed the trade and waited for settlement. The operator could also be the direct counterparty, creating an obvious conflict where customer losses contributed directly to company revenue. An exchange-style prediction market can instead allow participants to trade against each other. The terminal payoff remains binary, but the contract behaves more like a tradable derivative during its lifetime. This distinction matters most on longer-duration markets where there is enough time and liquidity for meaningful repricing.
With that said, a very short expiry makes these differences less important. With a very short lifespan, the advantages of continuous trading can diminish rapidly. A one-minute Bitcoin contract may technically have an order book, but the practical ability to exit can disappear if the market moves sharply during the final seconds. Prices can jump from $0.70 to $0.20 without giving every trader a useful opportunity to transact between those levels. This is where short-term event contracts become especially close to short-term binary options. The market is dominated by the position of the underlying asset relative to the strike, and the potential settlement approaches either $1 or zero. A tiny underlying movement can produce an enormous percentage change in the event contract. A stop-loss order is not guaranteed to solve this problem. Stops require someone willing to take the opposite side. An order book cannot manufacture liquidity during a violent repricing.
The Importance of Payout Mathematics
Binary-style contracts can produce deceptively high winning percentages. Suppose a YES share costs $0.95. If it settles successfully, the remaining profit is only $0.05. If it fails, the loss is $0.95. A trader can therefore win nineteen such contracts, earning $0.95 in total, and lose the twentieth contract, giving back the entire gain before fees. A 95% win rate would produce no profit in that simplified sequence. The same problem historically appeared with fixed-payout binary options. If a platform paid 80% profit when correct but took 100% of the stake when wrong, the trader needed to win approximately 55.6% of equivalent trades simply to break even before other costs. Frequent wins can therefore create psychological confidence without producing positive expected value over time. Probability, price and payout need to be considered together.
Settlement Rules
An event contract must define exactly what determines the result. A crypto-price market might for instance specify a particular exchange, index, observation period, and timestamp. Another might use an average across several venues. Those definitions can produce different outcomes near the strike.
This makes the contract terms extra important. A trader who reads only “Bitcoin above $100,000?” may think the answer is obvious, while the detailed rules could specify a particular price index at 12:00:00 UTC. A temporary print on another exchange might be irrelevant.
Polymarket explicitly states that market rules define the resolution source and edge cases, and that the title alone does not determine settlement. That principle applies broadly to prediction contracts; the headline attracts the trade, but the settlement wording decides who gets paid.
Crypto Prediction Markets Change Infrastructure Risk
A trader using a conventional sports exchange or bookmaker primarily faces risks related to the market itself, the counterparty, the platform, and the payment system. Crypto-based prediction markets come with many of the same underlying risks, but add a different set of technical and operational considerations to the mix. Depending on how the market is structured, users may need to manage wallet security, blockchain transactions, smart contracts, and network compatibility. A user can, for example, approve a malicious transaction, lose access to a wallet, interact with the wrong contract, or send assets over an unsupported network.
The important distinction is therefore not that crypto prediction markets are inherently more or less risky. It is that the risk profile is different and therefore require a different risk assessment Conventional platforms may concentrate more of the operational and custody risk within the bookmaker, exchange, or payment provider, while crypto-based markets can place more responsibility directly on the user. Evaluating the risks requires looking at the right set of parameters, including counterparty exposure, platform reliability, custody, settlement, payment rails, smart-contract and blockchain risk, and the user’s own operational security.
Smart contracts introduce another layer. Correctly written software can automate collateral and settlement, but software is not immune to bugs. Oracle systems also need procedures for disputed outcomes. A market can therefore become economically controversial even where everyone agrees that the underlying event occurred, simply because the contract wording or external data source produced an unexpected interpretation.
Stable-coin collateral is another consideration. A contract priced in a token designed to track something such as the USD or EUR removes most normal crypto volatility from the unit of account, but it still depends on the reliability of that token and the infrastructure holding it. A stable-coin is designed to maintain a stable value, but it is not necessarily guaranteed to do so. The mechanisms supporting the peg can fail or weaken under stress.
The Legal Status of Betting Exchanges
The legal and regulatory landscape for betting exchanges and prediction markets is currently evolving rapidly. Their status varies substantially between jurisdictions, and the rules are largely still developing as law makers and regulators attempt to determine how these platforms should be classified, regulated, and supervised. New products, technologies, and business models are creating regulatory questions that existing frameworks were not designed to address. As a result, the legal status of a particular platform or market, and the specific products they offer, can remain uncertain until regulators provide clearer guidance or courts establish how existing laws apply.
Are Prediction Markets Just Binary Options 2.0? Examples From Around The World
The United Kingdom
The underlying event can have a significant impact on how a prediction market is treated from a legal and regulatory perspective. One notable example is the current situation in the United Kingdom. The Financial Conduct Authority´s (FCA) 2026 perimeter report states that prediction market products linked to non-financial events, such as sporting or political outcomes, fall under the Gambling Commission’s remit, while products referencing financial or certain climatic events fall within the FCA’s regulatory perimeter. The FCA’s current view is also that the financial prediction market products it has examined fulfil the requirements to be classified as binary options. They are therefore subject to the FCA’s permanent ban on the sale of binary options to retail consumers.
European Union
In the European Union, the relationship between prediction markets and binary options is no longer merely an analytical comparison. ESMA clarified the legal situation in their July 2026 statement.
“Where event contracts are financial instruments, they classify as derivatives and, given the binary outcome, fall within the scope of the existing national product intervention measures on binary options adopted by national competent authorities prohibiting their marketing, distribution or sale to retail clients.” Source: ESMA reminds firms of existing rules and obligations under binary option measures amid growing popularity of prediction markets globally – 03/07/2026
This regulatory view focuses on economic substance. Calling a product a prediction share, forecast contract, or event token does does not on its own turn it into an approved financial instrument if the underlying mechanics still are those of a binary option. This is particularly relevant to very short crypto-price markets. A contract asking whether Bitcoin will be above a strike in five minutes may use modern blockchain infrastructure, but its economic structure can be almost indistinguishable from a short binary option referencing the same price.
South Africa
South Africa is particularly interesting because it actually has a historical example of an exchange-based binary-options market. In 2008, the Bond Exchange of South Africa launched Justrade.com, an online market for event-driven futures and binary options. The former Financial Services Board (FSB), now part of the Financial Sector Conduct Authority (FSCA), described the products as binary options whose value was determined by the outcome of a future event. The contracts had a fixed payout if the event condition was satisfied and zero otherwise, and traded between 0 and 100. The FSB stated that these instruments could be interpreted as derivative instruments falling within the securities framework.
The experiment appears to have been short-lived. Justrade.com was operating in 2008 and was still described as an active prediction market in March 2009, but the platform did not become a lasting product of the South African exchange landscape. BESA itself was acquired by the Johannesburg Stock Exchange in June 2009, and there is no evidence that the Justrade market continued as a JSE product.
Unlike the UK and the EU, South Africa does not impose any blanket prohibition on retail binary options. This is relevant to emerging prediction and event markets, given South Africa’s historical experience with exchange-traded binary event contracts. However, the absence of a blanket prohibition should not be interpreted as a general authorization. Individual products can still be subject to financial-services licensing, derivatives regulation, gambling legislation, or other applicable requirements, and it is possible that a product will run into legal obstacles on that level even without the blanket ban.
The United States
In the United States, certain event contracts are regulated as derivatives under the federal commodities framework. The Commodity Futures Trading Commission (CFTC) states that event contracts are typically structured as swaps and can be used for forecasting, hedging economic risk, or speculation on price movements and event outcomes. The regulator has continued working on prediction-market rules during 2026, including a March request for public comment covering the application of Commodity Exchange Act requirements to these markets.
The CFTC’s own product filings make the binary relationship unusually clear. Its database includes certified event products explicitly classified as binary-option swaps, including crypto price target forecast contracts. This does not mean every prediction platform accessible online is a regulated US exchange. Traders still need to identify the legal company, jurisdiction and permissions applying to the exact account they use.
It should also be noted that the legal status of prediction markets is currently the subject of significant political and legal conflict in the United States. A central issue is whether markets on sports and elections should be treated as financial contracts subject to federal regulation, or as gambling and betting activities regulated by state law.
Risk Management on Betting and Prediction Markets
Position size, liquidity, and expiry
Position size remains the most basic control. A high-confidence outcome can still fail, and binary-style settlement can make the final loss much larger than the remaining potential gain. A trader buying a 90-cent contract should understand that the available upside is ten cents while nearly the whole purchase price remains at risk.
Liquidity should influence position size. A market might comfortably absorb a £100 order but become difficult to exit with £20,000. Traders who scale a successful small strategy without studying market depth can discover that their own orders become part of the price movement.
Short-duration markets require particular restraint because the time available to react disappears quickly. If a one-minute crypto contract moves from 70 cents to 15 cents, the trader may have no practical opportunity to execute the planned exit in between. Maximum theoretical loss should therefore be treated as a realistic possibility rather than an abstract worst case.
The Difference Between Disciplined Trading and Chasing Outcomes
Betting-market trading can look analytical while still becoming compulsive. The presence of charts, order books and probability calculations does not change the behavioural risk created by rapid repeated decisions. A trader who loses a football position and immediately doubles the next stake is not managing a portfolio merely because both trades appeared on an exchange screen. The same applies to prediction contracts. Repeatedly buying another five-minute crypto market after a loss can reproduce the same loss-chasing pattern associated with short binary options and casino-style products. A trading plan should therefore define maximum exposure before the event begins. The question is not simply how much the platform permits the user to stake, but how much the account can lose without forcing the next decision to become an attempt at recovery.
Examples of notable entities
- Polymarket
Polymarket is one of the most well-known prediction markets and it brought the prediction-market model to a large global audience. It uses an order-book model for contracts on politics, economics, crypto, sports, geopolitics, and other events.
Polymarket´s international platform operates through blockchain-based infrastructure, meaning that trading involves not only the usual market and counterparty considerations but also additional issues relating to wallets, blockchain transactions, custody, and digital assets. The international platform uses the cryptocurrency USDS as collateral; a stable-coin issued by the company Circle. - Kalshi
This is a United States-regulated event-contract platform. It offers contracts on economic data, politics, weather, sports, and other events. Kalshi is regulated by the Commodity Futures Trading Commission (CFTC) as a designated contract market (DCM), meaning that its event contracts are treated as financial contracts. At the time of writing, Kalshi is than Polymarket by trading volume, although the exact comparison depends on how the two platforms’ volumes are measured. For July 2026, Kalshi recorded about $37.7 billion in trading volume, compared with roughly $12.9 billion combined for Polymarket International and Polymarket US. That puts Kalshi at roughly three times Polymarket’s combined volume for that month.
Sports trading has become a major source of volume on Kalshi. A Pew Research Center analysis of trading from July 2024 through April 2026 found that sports accounted for 80% of Kalshi’s trading volume, compared with 39% on Polymarket. During the same period, politics accounted for 4% of Kalshi’s volume but 32% of Polymarket’s, while cryptocurrency accounted for 7% and 20%, respectively.
- PredictIt
Historically one of the best-known political prediction markets. It is much more narrowly focused than Polymarket or Kalshi, but is important historically and academically because of its long-running role in US political prediction markets. PredictIt played an important role in the development and study of real-money prediction markets. Unlike broader platforms such as Polymarket and Kalshi, PredictIt has historically focused primarily on political events and elections, and its importance extends beyond its trading activity. Initially, it operated under a CFTC no-action framework connected to an academic research arrangement, and it became a prominent source of market-based probabilities for political outcomes and an important subject of research into the predictive value of markets. PredictIt originally operated under a CFTC no-action framework established in 2014 for Victoria University of Wellington’s not-for-profit event-contract market. The CFTC withdrew PredictIt’s original 2014 no-action letter in August 2022. Litigation ensued, and in July 2025, a federal district court vacated the CFTC’s withdrawal letters, effectively restoring the 2014 no-action relief. The CFTC’s own current staff-letter database now describes a 2025 amendment to CFTC Letter 14-130 and explicitly says that Victoria University operates the market under the trade name PredictIt. These events illustrates the difficulties of fitting prediction markets into existing distinctions between gambling, financial derivatives, and academic experimentation.
- Robinhood
This mainstream US retail brokerage has incorporated event contracts alongside it´s more conventional offerings. Robinhood entered prediction markets in 2024 and launched a dedicated prediction-markets hub in 2025. Its significance lies in bringing event contracts into a conventional retail brokerage environment rather than operating primarily as a specialist prediction-market platform. Robinhood offers contracts through CFTC-regulated venues including KalshiEX, ForecastEx, and Rothera. In Q2 2026, its event-contract business generated $156 million in revenue, illustrating the growing importance of prediction markets within mainstream retail trading.
- Augur
Augur is one of the earliest major decentralized prediction-market protocols and one of the first significant applications built on Ethereum. It was designed around the idea that users should be able to create and trade prediction markets without relying on a centralized operator to hold funds or determine the outcome of a market. The project began in 2015 and launched on Ethereum mainnet in 2018. What has made Augur particularly important is its approach to market resolution. Rather than having a company decide whether an event occurred, Augur used an economic oracle system in which holders of its native REP token reported and disputed outcomes. Participants had an incentive to report what they believed to be the true outcome because incorrect reports could result in economic losses. In sufficiently serious disputes, the protocol could ultimately fork into separate “universes” representing competing outcomes. This made Augur an important early experiment in combining prediction markets, smart contracts, and decentralized oracles. Its significance therefore extends beyond betting. The underlying problem it attempted to solve was how information about real-world events could be brought onto a blockchain without relying entirely on a centralized authority.
- Opinion
Opinion is a crypto-native prediction-market platform developed by Opinion Labs. It is designed as an on-chain prediction exchange where users can trade contracts on real-world events. The platform has a particular emphasis on macroeconomic and financial events, including interest-rate decisions, economic indicators, crypto markets, and other global events, although its current market offering also includes fields such as sports, esports, politics, business, and technology.
From a trading perspective, Opinion is notable because it uses a central limit order book (CLOB) rather than relying solely on an automated market maker. Users can place market or limit orders, while the order book displays bids, asks and the spread. This makes the platform structurally closer to a conventional financial exchange than to a sportsbook. Traders can provide liquidity with resting limit orders, take liquidity from existing orders, and manage positions as prices change. - Manifold Markets
Manifold Markets is primarily an experimental/social prediction-market platform. Its markets use play money rather than real-money wagering.
Manifold Markets is a user-created prediction-market platform where anyone can create markets on almost any question. Users trade Mana (Ṁ), an in-platform play-money currency. Market prices are intended to represent the community’s collective estimate of the probability of an event. Markets cover an unusually broad range of subjects, including politics, technology, science, sports, AI, economics, and even highly personal or humorous questions.