Are Prediction Markets the New Binary Options?

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TU Research examines whether prediction markets are becoming an alternative to binary options. In the research scenario, 46% of binary options traders would consider switching at least some of their activity to prediction markets, while 44% perceive these contracts as safer than binary options. However, only 34% correctly calculate expected returns in a probability-based trading scenario, and 26% do not accurately track their trading performance. The findings highlight potential gaps between perceived safety, financial knowledge, and actual trading risks.

Prediction markets allow participants to trade contracts linked to future events, from cryptocurrency prices and economic indicators to sports and politics. Their growing popularity raises a familiar question: are these genuinely new financial instruments, or another form of binary-outcome speculation?

Like binary options, many prediction market contracts offer predetermined payouts based on whether an event occurs. However, prediction markets may use exchange-style pricing, allow positions to be sold before settlement, and cover a wider range of events.

Recent research from NBER, CEPR, and ESMA highlights the overlap between prediction markets, betting, and retail financial trading. While these products can aggregate useful information, they also raise concerns about trading profitability, probability literacy, and investor protection.

The research aims to answer key questions:

Are binary options traders ready to switch to prediction markets?
Do traders consider prediction markets trading or gambling?
How many participants believe they are profitable?
Do traders understand probability-based payouts?
Are short-term contracts encouraging speculative behavior?
Do traders check settlement rules before trading?
Are prediction markets perceived as safer than binary options?
What would encourage traders to switch products?

Findings

The research framework identifies several potential patterns:

Prediction markets may compete with binary options. Some 46% of binary options traders would consider switching at least part of their activity, while another 24% would use both products.
Trading and gambling perceptions overlap. A combined 38% classify prediction markets as both trading and betting, compared with 27% who primarily consider them financial trading.
Profitability remains uncertain for many participants. Only 24% describe themselves as profitable, while 32% report losses and 26% do not accurately track their results.
Probability literacy is limited. Just 34% correctly identify the expected return of a contract priced at its estimated probability of success.
Short-term trading is attractive. Some 42% prefer contracts resolving within one day, including 19% who favor outcomes within an hour.
Settlement rules are frequently overlooked. Only 29% read complete resolution criteria before almost every trade.
Prediction markets are perceived as safer. Some 44% consider them safer than binary options, although both can involve losing the entire amount committed.
Trading conditions influence switching decisions. Better prices, transparent settlement rules, and early exits are the leading reasons for considering prediction markets.

Risk warning: All investments carry risk, including potential capital loss. Economic fluctuations and market changes affect returns, and 40-50% of investors underperform benchmarks. Diversification helps but does not eliminate risks. Invest wisely and consult professional financial advisors.

Institutional validation

Institutional research suggests that prediction markets increasingly overlap with retail trading and betting, while raising familiar questions about profitability, financial knowledge, and investor protection.

The National Bureau of Economic Research (NBER) examined the convergence of prediction markets, sports betting, and retail options trading in its 2026 study, Retail Betting Markets. The researchers identified shared market structures and behavioral drivers, suggesting that the distinction between financial speculation and betting is becoming less clear.

The Centre for Economic Policy Research (CEPR) analyzed 588 million Polymarket trades worth $67 billion in Who Wins and Who Loses in Prediction Markets? (2026). The study found that the top 1% of profitable users captured 76.5% of profits earned by profitable participants. Successful traders were also more likely to provide liquidity through limit orders, indicating that execution and trading strategy matter alongside forecasting accuracy.

A separate NBER study by Eric Zitzewitz, published in October 2026, documented pricing inefficiencies in PredictIt, including overpricing of unlikely outcomes. The findings suggest that prediction market prices do not always accurately reflect event probabilities, particularly when trading restrictions limit arbitrage.

Regulatory concerns reinforce the comparison with binary options. In July 2026, the European Securities and Markets Authority (ESMA) clarified that event contracts qualifying as financial instruments can fall within existing national restrictions on binary options. This follows ESMA's 2018 investor protection measures, introduced in response to risks associated with binary payouts and retail speculation.

The central question is therefore whether retail traders understand the similarities and differences between these products, particularly when evaluating their financial risks.

Theoretical research

The similarities between prediction markets and binary options can be explained through expected value, probability judgment, and loss aversion.

Consider a prediction market YES contract priced at $0.70 that pays $1 if an event occurs. A successful trade generates a gross profit of $0.30, while an unsuccessful trade loses $0.70.

If the trader estimates a 70% probability of success, the expected profit before fees is:

Expected profit = (0.70 × $0.30) − (0.30 × $0.70) = $0.

The event is likely to happen, but the contract does not offer a positive expected return at that price.

Binary options involve a similar distinction between winning frequently and making money. For example, a contract paying an 80% net return on a successful trade requires a win rate above approximately 55.6% to break even before additional costs.

Behavioral finance helps explain why traders may overlook these calculations. In Prospect Theory, Kahneman and Tversky showed that individuals do not always evaluate gains and losses according to expected utility. Traders may therefore be attracted to low-priced contracts promising large percentage returns or overestimate their ability to predict short-term events.

The key difference is that some prediction markets allow participants to trade contracts before settlement, potentially offering greater flexibility than traditional broker-issued binary options. However, liquidity constraints, transaction costs, and unfavorable prices can still produce substantial losses. The theoretical issue is whether traders evaluate these differences or focus mainly on predicting outcomes correctly.

Survey data

The research examines how retail traders perceive prediction markets and whether they understand the financial characteristics that distinguish them from binary options.

Methodology

The study is designed around a structured online questionnaire using the CAWI methodology.

Sample composition: 1,200 retail traders and investors.
Coverage: North America, Europe, Asia, Latin America, Africa, and the Middle East.
Age: 18–60 years old.
Participation criteria: Individuals who have traded or invested in financial assets within the previous 12 months.
Research scope: Prediction markets, binary options, event contracts, and speculative trading behavior.

Research team

The study was conducted by our experts:

Anastasiia Chabaniuk (Author, TU research) – research design and interpretation.
Chinmay Soni (Fact-checker) – data validation and statistical verification.
Ciaran Ryan (Editor-in-Chief) – editorial and methodological supervision.
TU research team (Andrey Mastykin, Oleg Tkachenko) – data collection and analysis.

Are binary options traders ready to switch to prediction markets?

Respondents with binary options experience were asked whether they would consider using prediction markets instead.

Willingness to switch from binary options to prediction markets
Response	Share
Switch completely	18%
Move some trading activity	28%
Use both products	24%
Prefer binary options	17%
Do not know enough about prediction markets	13%

Insight: A combined 46% would consider switching at least some of their trading activity, while another 24% would use both products. This suggests that prediction markets could become an alternative for existing binary options traders rather than an entirely separate retail audience.

Are prediction markets trading, investing, or gambling?

Respondents were asked how they primarily classify prediction markets.

How retail traders classify prediction markets:

Combination of trading and betting – 38%;
Financial trading – 27%;
Gambling or betting – 19%;
Investing – 9%;
Forecasting tool – 5%;
Not sure – 2%;

Insight: The largest group, 38%, considers prediction markets a combination of trading and betting. The result illustrates the blurred distinction between these activities, consistent with the market convergence examined by NBER.

Who is actually making money on prediction markets?

Prediction market users were asked to assess their overall trading performance after fees.

Self-reported prediction market profitability
Trading outcome	Share
Consistently profitable	9%
Slightly profitable	15%
Approximately break-even	18%
Slightly unprofitable	21%
Significantly unprofitable	11%
Do not accurately track results	26%

Insight: Only 24% consider themselves profitable, while 32% report losses and 26% cannot accurately assess their performance. This raises questions about retail traders' ability to evaluate trading outcomes, particularly given the CEPR finding that prediction market profits are highly concentrated.

Can an 80% chance of winning still be a bad trade?

Respondents were presented with a YES contract costing $0.80 and paying $1 if the event occurs. They were told their independent estimate of the event's probability was 80%.

Understanding expected returns in prediction markets
Response	Share
Expected return is zero before fees – correct	34%
Profitable because the event is likely	31%
Profitable because the payout is $1	16%
Unprofitable because 80% is too risky	9%
Not sure	10%

Insight: Only 34% correctly identify the expected return. Another 47% incorrectly assume that a high probability or fixed payout makes the trade profitable. This illustrates why understanding probabilities is essential even when market prices contain useful forecasting information.

Are prediction markets encouraging short-term speculation?

Prediction market users were asked which contract duration they most frequently prefer.

Preferred prediction market contract duration:

Less than one hour – 19%;
One hour to one day – 23%;
Two to seven days – 25%;
More than one week to one month – 18%;
Longer than one month – 10%;
No preference – 5%.

Insight: Some 42% prefer contracts resolving within one day. This suggests that rapid outcomes are an important attraction, potentially appealing to traders familiar with short-term binary options. However, short duration alone does not establish excessive risk-taking.

Can traders predict correctly and still lose money?

Respondents were asked how frequently they review a contract's settlement rules before trading.

How traders review prediction market settlement rules
Behavior	Share
Read full criteria before almost every trade	29%
Usually review the main rules	25%
Rely mainly on the contract title	37%
Rarely check settlement rules	9%

Insight: Only 29% read the complete settlement criteria before almost every trade, while 46% rely mainly on contract titles or rarely check the rules. This may expose traders to unexpected outcomes when official settlement conditions differ from their assumptions.

Are prediction markets safer than binary options?

Respondents were asked to compare the financial risks of the two products.

Prediction Markets vs. Binary Options: Perceived Risk

Prediction markets are much safer – 16%;
Prediction markets are somewhat safer – 28%;
Risks are approximately similar – 31%;
Binary options are somewhat safer – 10%;
Binary options are much safer – 5%.
Not sure – 10%.

Insight: A combined 44% perceive prediction markets as safer than binary options, although both can involve losing the entire amount committed. The difference may reflect perceptions of transparency or market structure rather than an objective comparison of every contract.

What would persuade binary options traders to switch?

Respondents with binary options experience were asked which factor would most encourage them to use prediction markets.

Main reasons for considering prediction markets
Switching factor	Share
Better prices and lower costs	24%
Transparent settlement rules	21%
Ability to exit before settlement	18%
Wider selection of events	15%
Greater regulatory oversight	11%
Nothing	7%
Not sure	4%

Insight: Better prices and lower costs lead at 24%, followed by transparent settlement rules at 21% and early exits at 18%. This suggests that market structure and trading conditions may matter more than the novelty of event-based contracts.

Download the full PDF version of the TU research to access additional analysis, detailed survey data, and extended findings from our analytical team. The report includes complete methodology, charts, and behavioral insights referenced throughout the study.

Download PDF version

Practical implications for retail traders

Prediction markets can offer flexible ways to trade future events, but their risks should be evaluated as carefully as those of other speculative financial products.

Understand the payout structure. Calculate potential gains and losses before purchasing a contract. A high probability of success does not guarantee a profitable trade.
Compare prices with your own probability estimates. A contract may be correctly priced or overpriced even when the predicted event is likely to occur.
Review settlement rules. Check the event definition, official data sources, deadlines, and dispute procedures before trading.
Evaluate liquidity and fees. Bid-ask spreads, transaction costs, and limited market depth can significantly affect profitability.
Be cautious with short-term contracts. Rapid outcomes can encourage frequent trading without improving the likelihood of positive returns.
Track total profitability. Monitor realized gains, losses, and fees rather than relying only on the percentage of winning predictions.
Check regulatory protections. Prediction markets and binary options may be treated differently across jurisdictions, depending on the contract and applicable law.
Set limits on speculative capital. Defined maximum losses do not make a contract low-risk, particularly when trades are repeated frequently.

For traders who prefer to continue using binary options rather than switch to prediction markets, broker selection remains an important practical consideration. Trading conditions, payout rates, minimum deposits, and available instruments can vary significantly between providers. The table below compares binary options brokers to help readers evaluate these differences alongside the risks discussed in this research.

Top binary options brokers
	CloseOption	Capitalcore	Nadex	Pocket Option	QUOTEX
Foundation year	2013	2019	2009	2017	2019
Min. deposit	5	10	250	5	10
Min. Payout (%)	17	60		50	20
Max. Payout (%)	95	90	100	128	98
Withdrawal fee	0-100	Different	0-25 USD	0-0,5
Demo
Regulation		IFSA		MISA
TU overall score	7.83	6.51	3.84	9.05	8.6
Open an account	Go to broker Your capital is at risk.	Go to broker Your capital is at risk.	Study review	Go to broker Your capital is at risk.	Go to broker Your capital is at risk.

Data sources and methodology

National Bureau of Economic Research (2026). Retail Betting Markets.
Centre for Economic Policy Research (2026). Who Wins and Who Loses in Prediction Markets? Evidence from Polymarket.
National Bureau of Economic Research (2026). Limits to Arbitrage and Prediction Market Efficiency: The Case of PredictIt.
European Securities and Markets Authority (2026). ESMA Reminds Firms of Existing Rules and Obligations Under Binary Option Measures.
European Securities and Markets Authority (2018). ESMA Agrees to Prohibit Binary Options and Restrict CFDs to Protect Retail Investors.
European Securities and Markets Authority (2019). ESMA Ceases Renewal of Product Intervention Measure Relating to Binary Options.
Commodity Futures Trading Commission. Understanding Prediction Markets and Event Contracts.
Commodity Futures Trading Commission (2026). CFTC Staff Issues Prediction Markets Advisory.
Pew Research Center (2026). Prediction Markets' Trading Volume Doubled Between May and July, Largely Driven by Sports.
Kahneman, D., and Tversky, A. (1979). Prospect Theory: An Analysis of Decision under Risk.
Wolfers, J., and Zitzewitz, E. (2004). Prediction Markets.
Manski, C. F. (2006). Interpreting the Predictions of Prediction Markets.
Traders Union. Prediction Markets: The Basics.
Traders Union. Are Prediction Markets Legal or Gambling?
IdSurvey. CAWI Methodology.

Previous volumes in this series

Conclusion

Prediction markets are rapidly emerging as a competitive alternative to binary options, yet most retail traders struggle to fully grasp their risks and mechanics. The research reveals that while nearly half of binary options traders are open to switching, only a third accurately calculate expected returns and many overlook vital settlement rules. This disconnect between perceived safety and actual financial literacy poses significant challenges, as highlighted by the fact that 44 percent consider prediction markets safer despite similar potential for total losses. Ultimately, success depends not on confidently predicting outcomes but on understanding the true cost, structure, and probabilities behind each trade to avoid the costly pitfalls of misplaced optimism.

FAQs

What are the main risks associated with both prediction markets and binary options?

Both prediction markets and binary options can involve the risk of losing the entire amount committed to a trade. Although prediction markets are perceived by some as safer due to features like transparency or early exit options, both products require careful consideration of contract terms, pricing, trading fees, and the possibility of misjudging event probabilities.

How does trader profitability compare in prediction markets versus binary options?

According to the research, only 24% of prediction market users report being consistently or slightly profitable, with a similar dynamic seen in binary options trading where profitability is uncertain for many. Additionally, a large share of profits in prediction markets is concentrated among a small percentage of traders, highlighting the importance of strategy and execution in both markets.

What factors influence a trader’s decision to switch from binary options to prediction markets?

The leading factors for traders considering a move to prediction markets include better prices and lower costs, transparent settlement rules, and the ability to exit contracts before settlement. These structural differences are more influential in switching decisions than the novelty of prediction markets or their wider event coverage.

How important is understanding probability for success in prediction markets?

Understanding probability is crucial for success in prediction markets, as the expected return on a trade depends on whether the contract price accurately reflects the likelihood of an event. The research shows that many traders overestimate their chances of profitability when they do not properly calculate or interpret probabilities, which can lead to unexpected losses.

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Team that worked on the article

Anastasiia has 17 years of experience in finance and content marketing. She believes that the support of information and expert opinion is very important for the success of investors and new traders.

Learn about our editorial policies

Ciaran Ryan is a veteran financial journalist based in South Africa, where he covers cryptocurrency, mining, stock markets, and governance for Moneyweb. He also hosts the weekly Moneyweb Crypto Podcast.

Chinmay Soni is a financial analyst with more than 5 years of experience in working with stocks, Forex, derivatives, and other assets. As a founder of a boutique research firm and an active researcher, he covers various industries and fields, providing insights backed by statistical data.

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