Original Title: How to Gauge if a Prediction Market Is Worth It

Original Author: Marvellous

Original Translation: AididiaoJP, Foresight News

Introduction:

A prediction market is a trading platform where participants bet on the outcome of future events, becoming increasingly popular in the cryptocurrency and financial sectors.

However, not all prediction markets are the same. Assessing whether a specific platform is "worth it" to invest your time or money depends on a comprehensive consideration of the following three key factors:

· Its market design

· Economic environment

· Relevant user factors

These factors are crucial in determining whether a prediction market can provide accurate predictions, sufficient liquidity, and a trustworthy trading experience.

Market Design: Structure, Mechanisms, and Clarity

The concept of market design explores the structure and operation of a prediction market, including trading mechanisms, contract rules, and outcome determination methods. A good design must align incentives and ensure the market's smooth operation:

Trading Mechanisms:

Prediction markets use different mechanisms to match trades. Some, like @Polymarket and @Kalshi, use order books, while others like @ZeitgeistPM employ an automated market maker model, such as LMSR.

Model Overview:

· Order Book: Efficient in high liquidity but performs poorly in markets with low liquidity.

· Constant Product Market Maker (CPMM, x*y=k): Simple but experiences high slippage in extreme cases.

· Logarithmic Market Scoring Rule (LMSR): Limited loss and standardized probability, but sensitive to parameters.

· Dynamic LMSR (DLMSR) or pm-AMM: A new model addressing liquidity and slippage issues.

Contract Types and Clarity:

A well-designed market must have clearly defined contracts and outcome determination criteria. Contracts are typically binary options (yes/no outcomes, payment of $1 if the event occurs) but can also be multi-outcome or scalar contracts (payment based on numerical outcome changes).

Please note: The wording of the question must be unambiguous, and the result must be verifiable. Research has shown that having a "question with clear determinants and a well-defined outcome" is a key factor in effective prediction markets.

This is because if the market question is vague or the outcome is subjective, traders will lack confidence, fearing that their stake will not receive a fair determination.

Result Determination and Oracle:

The design must ensure that people trust the way results are determined. Therefore, traditional prediction markets rely on platform operators or third parties to declare results and pay out rewards, while the crypto space's prediction markets use oracles to input real-world outcomes into smart contracts.

For example, @Polymarket utilizes @UMAprotocol to provide real-world data for market settlement.

A robust resolution mechanism can prevent disputes and manipulation, thus upholding market integrity. Therefore, when evaluating a platform, please consider:

· Does it have a reliable oracle or arbitrator?

· Is it prone to disputes? If so, how are they handled?

Cost and Technical Design:

High transaction costs or a slow system can stifle platform usability.

Recall the early days of decentralized markets, such as Augur (launched as a pioneer on Ethereum in 2018), but users faced high gas fees, low liquidity, and a poor user experience, hindering their mainstream adoption.

Therefore, you should consider which chain the product is deployed on, for example, @GroovyMarket_ launching on @SeiNetwork, @Polymarket on @0xPolygon, @triadfi on @solana.

These platforms I mentioned have one thing in common: the chain they are built on ensures lower transaction fees and faster transaction speeds.

They also achieve this by simplifying the user interface. For example, Polymarket is built on Polygon (an Ethereum sidechain) and uses a USD stablecoin for transactions, providing a fast and stable trading experience, shielding users from the volatile cryptocurrency prices. It also charges 0% transaction fees, making transactions frictionless. Such design choices greatly enhance usability compared to first-generation platforms.

Furthermore, you also need to assess the fees charged by these platforms (market creation fee, transaction fee, deposit/withdrawal fee, settlement fee, etc.).

In conclusion, if the design of a prediction market can provide a clear and fair structure: an efficient trading mechanism with sufficient liquidity, transparent rules, and trustworthy outcome determination, then it is worthwhile.

A poorly designed market (slow transactions, unclear rules, or untrustworthy outcomes) may be directly rejected by the market.

Economic Factors: Liquidity, Pricing, and Incentives

I believe that every excellent design needs an economic model to succeed because key economic factors will determine whether a prediction market can effectively aggregate information and properly reward participants.

Liquidity and Market Depth:

The concept of liquidity explains the need for active trading and funds in the market so that traders can buy and sell at a fair price without experiencing significant slippage.

Over the long term, sufficient liquidity is absolutely crucial.

Research has found that the effectiveness of a prediction market depends on "sufficient market liquidity" and a large number of traders. If only a few people trade, prices may fluctuate wildly or remain stagnant, failing to reflect true probabilities. Therefore, a balance needs to be struck.

Look for platforms with high trading volume or liquidity pools. For example, Polymarket has become the largest decentralized prediction market, accounting for about 94% of total market trading volume in 2024, handling over $8.4 billion in bets, despite new challengers emerging this year.

Such immense liquidity (especially during major events like the U.S. elections) means that its odds have enough market depth support, making it more difficult for any single user to manipulate the price.

Near-Efficient Pricing (Information Aggregation):

The core idea of a prediction market is that market prices reveal the collective belief of the crowd about the event's probability. Therefore, when the economic mechanism is sound, i.e., when many well-informed traders with funds participate, the market price becomes a highly accurate prediction.

In fact, well-functioning markets outperform opinion polls. Remember:

· The Iowa Electronic Market's election predictions beat professional polling firms in 74% of cases.

· Google's internal prediction market made more accurate predictions than company experts.

However, if market liquidity is low or dominated by uninformed bets, the price may not be as reliable.

Therefore, it is always important to consider the platform's track record:

· Has the platform correctly predicted outcomes when other forecasters failed?

It is noteworthy that during the 2024 US election, Polymarket's odds were closely watched, outperforming even traditional polls and attracting the attention of figures like Elon Musk. This is an important area to consider.

Incentive Alignment:

Economic design should also cover how traders are rewarded and the cost of participation. Low or zero fees are a huge advantage, as high fees can hinder frequent trading or arbitrage, behaviors that help maintain price accuracy.

Platforms like Polymarket do not charge transaction fees, and some other markets even subsidize participation through token rewards or yields. Additionally, some markets may reward information discovery, such as offering prizes or reputation to the best predictors, to encourage knowledgeable participation.

A healthy prediction market economy will make it profitable for traders to correct mispriced odds, so attempts to manipulate the price are usually self-correcting. For example, if someone irrationally bets, others have an economic incentive to take the opposite stance to push the price back to a rational level. If a market is very small, a wealthy manipulator may temporarily affect the odds, so scale becomes important again.

Risk and Regulatory Costs:

Another economic consideration is the risk involved, not just the risk of a failed bet, but also counterparty risk and regulatory risk. In crypto prediction markets, smart contract security is crucial (as funds are held by code).

On centralized platforms, you rely on the company's solvency and integrity.

Please note that regulatory crackdowns can bring costs at any time. For example, after settling with the US Commodity Futures Trading Commission (CFTC) and being fined $1.4 million, Polymarket had to geographically block US users as its operation involved unregulated event markets.

During this period of excluding US users, liquidity in certain markets reportedly decreased. Similarly, some countries completely ban prediction markets.

By the end of 2024, France, Singapore, and Thailand had all blocked access to Polymarket. In reality, these factors can have economic implications for a platform (reducing its user base or forcing it to incur compliance costs).

Therefore, a "worthwhile" market should have a stable legal foundation or contingency plan. Otherwise, participants will face the economic risk of sudden closure or inability to withdraw funds.

In essence, the economics of a prediction market must ensure there are enough stakeholders and frictionless transactions. The best markets will have ample participation, low transaction costs, and mechanisms to incentivize accurate predictions.

User and Community Factors: Engagement, Trust, and Experience

Anyway, I like to consider user-related factors, essentially the human side of the market, because the effectiveness of a prediction market depends on its users and their surrounding community.

Therefore, key points to evaluate include:

Scale of Participation:

Prediction markets rely on scale. The more individuals participate, the more effective they are. A large and active user base means diverse information and viewpoints are brought to the table.

Diversity of viewpoints is crucial

If all traders have a unanimous view (or collude), the market cannot aggregate independent information. Therefore, it is important to focus on the following metrics:

· Number of active users

· Amount staked

· Open interest in contracts, and so on

Overall, a platform with thousands of actively engaged traders is much more robust than one with only a few users. Actively engaged participants with diverse informational backgrounds are a key driver of prediction market accuracy.

For example, Augur is fully decentralized, but its early version had very few active users, which, despite its technological novelty, limited its effectiveness.

In contrast, Polymarket has achieved critical mass of users by offering markets on popular topics (elections, sports, cryptocurrency prices) and making onboarding easy (global, no KYC, simple web interface). This scale of participation greatly enhances the "wisdom of the crowd" effect.

User Experience and Accessibility:

Even for crypto-native users, user experience is crucial. Platforms that are overly complex or require intricate wallet setups will deter users.

Focus on emerging prediction markets that prioritize a smooth onboarding experience, as a clean interface, informative charts, and clear odds display will attract more users, thereby enhancing market quality.

On the other hand, tedious processes (such as needing to manually acquire and stake a specific token to participate in betting, or dealing with long wait times for transaction finality) may make traders feel that the market is not worth the effort to participate in.

Therefore, always consider the ease of use of a platform.

· Can you easily deposit funds?

· Does it support mobile devices?

· If an issue arises, is there customer support or community assistance?

Reputation and Community Trust:

Since real money is involved, trust is crucial. Trust can come from transparency (open-source code, audited contracts, or reputable backers) or from a track record of fair operations.

Therefore, check whether the platform has any history of scandals or failure to pay events. Community-operated and decentralized markets like Polymarket seem trustless, while other markets like Kalshi establish trust through full regulation and compliance; as we saw in 2024, Kalshi became the first CFTC-regulated exchange to offer legal event contracts in the U.S., even winning a lawsuit over offering election betting.

This regulatory stamp of approval instills credibility and reassures users that they can trust the platform to operate within legal boundaries.

Meanwhile, platforms operating in the gray area are red flags. You're either decentralized with audited code or fully regulated.

User Incentives and Behavior:

Another human factor is the reason for user participation. Are they casual bettors, profit-seeking traders, or risk-hedging domain experts? I believe markets with a strong predictor community may yield better insights.

A platform's culture, whether it feels more like a gambling atmosphere or a serious prediction tool, will affect its suitability for your purpose. When deciding if a prediction market is worth using, assess the community:

· Is it active and serious?

· Do they have opposing views?

The presence of "actively engaged participants with diverse information" is a key factor for a prediction market's success.

I believe a constructive community will support markets that are meaningful and correctly adjudicated, while a poorly managed community may indulge in ill-defined markets.

In conclusion, user factors boil down to quantity and quality of participants. Therefore, a platform with a large, diverse, and actively engaged user base that has earned their trust is more likely to provide a valuable experience.

If a market has almost no users or community, then regardless of the technology behind it, you may want to steer clear. After all, a prediction market is a form of crowdsourcing, which means that without a "crowd," there is nothing to participate in.

Final Summary:

When evaluating a prediction market, always go back to three core considerations:

· Market Design

· Economic Viability

· User Factors

A prediction market with a sound mechanism, sufficient liquidity, and a vibrant, trustworthy community platform is more likely to provide value in profitable trading opportunities and accurate predictions.

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