What are Decentralized Prediction Markets?

Learn how decentralized prediction markets work and uncover their potential as a vital tool for both individuals and businesses alike.

TLDR

Decentralized Prediction Markets (DPMs) are the crystal ball of the digital age, disrupting the way we predict and bet on future events. Fueled by blockchain technology, DPMs liberate predictions from intermediaries, offering a fair, secure, and transparent arena where users predict outcomes and reap rewards. This article discusses how DPMs harness the power of collective intelligence in the ‘True Value of Decentralized Prediction Market’ section, driving accurate and insightful forecasts. Furthermore, the ‘How it Works’ section demonstrates how these markets function through a hypothetical scenario involving the U.S. Presidential Election, illustrating how users can make predictions and profit, based on event outcomes. While these innovative platforms confront regulatory, liquidity, security, and ethical challenges, their potential to redefine forecasting remains groundbreaking.

What is a Decentralized Prediction Market?

At its core, a Decentralized Prediction Market (DPM) is a digital platform where people can bet on the outcomes of future events without the need for a third party. If users correctly predict the outcomes of a future event, they can get financially rewarded. In DPMs, users have the ability to create their own ‘markets’ to make predictions on anything they want. Whether that be business, sports, weather, politics, etc. (where the majority of markets are binary, i.e. ‘Yes’ or ‘No’ outcomes).

Additionally, DPMs can be used by companies looking to gain insights into the probability of future events occurring, through crowdsourcing information. This information is often more accurate than individual or expert predictions, and is elaborated on in the ‘The True Value of Decentralized Prediction Markets — Forecasting’ section.

DPMs are powered by blockchain technology (see article for blockchain technology definition). Blockchain technology provides the foundation for creating transparent and secure prediction markets by using smart contracts.

Smart contracts are self-executing contracts with the terms of the agreement directly written into code. They automate the process of creating and settling prediction markets, ensuring that the outcomes are determined fairly and transparently.

Participants can interact with these smart contracts to place bets, make predictions, and receive payouts when the events occur. Never before have we had the ability to do this without Bookmaker third-parties (i.e. Bet365, FanDuel, DraftKings) skewing the odds to their benefit. As we’ve all heard before “the house always wins”. Smart contracts eliminate the need for “the house” to facilitate these transactions, as it’s all written in code.

When there is no centralized intermediary skewing the odds for their profit, this means betters can potentially earn higher payouts for each bet.

The below image breaks down an example of present-day odds and payout for the results of rolling a die. Technically, the probability for rolling an odd or even number on a die is 50/50. Naturally one would think that the payout for a bet on either an odd or even roll would be almost ‘2 to 1’ (i.e. 1.99 to 1).

However traditional Bookmakers today would usually offer odds of ‘1.9 to 1’ — reducing payout for users.

Example of present-day odds and payout breakdown for traditional Bookmakers

Traditional Bookmaker example— reducing payout for users to increase likelihood of profit for Third-party.

As seen below, the odds for users are increased (on average) as DPMs do not reduce odds to ensure profit for themselves. Therefore the payout for a bet on either an odd or even roll can be up to ‘1.99 to 1’.

Note — in this scenario, it is challenging to have the odds be a perfect ‘2 to 1’ payout as DPMs still need income to fund prediction settlement.

Example of odds and payout breakdown for DPMs

Example of odds and payout breakdown for DPMs — maximizing payout for users.

How it works

To illustrate how these markets work and how users can make predictions and profit, based on event outcomes, we’ll explore a hypothetical scenario surrounding the U.S. Presidential Election.

Event: The U.S. Presidential Election

Market Setup:

• On a DPM platform, a new market is created to predict the outcome of the U.S. presidential election, which has two major candidates: Candidate A and Candidate B.
• Two tokens are created in this market: “Candidate A Wins” and “Candidate B Wins.”
• Let’s assume the initial odds set by the market are as follows:

“Candidate A Wins” tokens are trading at $0.70.

“Candidate B Wins” tokens are trading at $0.30.

Betting and Trading:

• Based on the initial token prices, users believe that Candidate A has a 70% chance of winning and Candidate B has a 30% chance of winning.
• User 1 buys 10 “Candidate A Wins” tokens at $0.70 each, spending $7 in total.
• User 2 buys 10 “Candidate B Wins” tokens at $0.30 each, spending $3 in total.
• The market continues to trade with users adjusting their bets as more information becomes available.

Market Settlement:

• On Election Day, the smart contract ascertains that Candidate A has won the election.

Payouts:

• Regardless of who wins, the holder of the “correct outcome token” will receive $1 for every “correct outcome token” they own.
• Since “Candidate A Wins” tokens were trading at $0.70, users holding these tokens receive a payout of $1 for each token they hold. Payout of ‘1.43 to 1’.
• User 1, who bought 10 “Candidate A Wins” tokens receives $10 (10 tokens * $1 per token).
• User 2, who bought 10 “Candidate B Wins” tokens receives no payout because their prediction was incorrect.

In this simplified example, users who correctly predicted the election outcome received a payout of $1 for each token they held. The $1 per token payout structure means that if you correctly predict an event, you receive $1 for each token you hold for the winning outcome. This is a straightforward way to illustrate how DPMs work and how users can profit from accurate predictions.

Keep in mind that in real markets, token prices can fluctuate dynamically based on market sentiment and new information. For example, if a user bought 10,000 “Candidate A Wins” tokens at $0.70, this increase in demand would result in the price of that token increasing.

When demand goes up, so does the price.

So, let’s say the price of “Candidate A Wins” tokens goes up to $0.75 each. Now, if you want to buy these tokens, you’ll have to pay more — $0.75 instead of $0.70. This increase in price means that if you buy them now, your potential payout if Candidate A wins will be smaller because you paid more for each token. To be exact, if you bought “Candidate A Wins” tokens at the price of $0.75 each, the payout would be ‘1.33 to 1’

In real-world DPMs, it’s important to note two key pieces of information that will vary across different prediction markets:

1 — There are different ways of validating event results

Many prediction markets use either oracles, or a decentralized network to determine event outcomes accurately. Most platforms opt for oracles.

In Web3, an oracle is a trusted, third-party service or mechanism that provides external, real-world data or information to decentralized applications (dApps) and smart contracts on the blockchain. Oracles serve as bridges between blockchain networks and off-chain data sources, supplying the decentralized system with information from the external world. They help smart contracts access data related to weather, financial market prices, sports scores, real-time news, and any other information not inherently available on the blockchain. Oracles play a crucial role in enabling smart contracts to execute decisions based on real-time, accurate, and reliable data, ensuring these contracts interact effectively with the external environment.

Imagine an oracle as a weather station that provides real-time reliable weather updates. Just like a weather station collects current data about the temperature, humidity, and other weather conditions and broadcasts it to the public. Oracles in prediction markets gather data from various sources, such as official election websites or sports scoreboards and then securely broadcast this information to the blockchain. Just as you trust the weather station to provide you with the real-time weather, users in the prediction market rely on oracles to deliver accurate event results.

2 — Variable Payout Structure

While we used a $1 per token payout structure in this example for simplicity, not all prediction markets settle to this specific amount. Each market can have its own rules and payout structures. These distinctions are essential to understand when participating in or analyzing real DPMs.

The True Value of Decentralized Prediction Markets Forecasting

While there is inherent value in DPMs related to sports, the most significant value lies in leveraging collective intelligence to predict future events and derive insights. DPMs’ ability to crowdsource information on a global scale can enable policymakers and large companies to understand public sentiment regarding future events.

Remember we are talking about Decentralized Prediction Markets, not Decentralized Sportsbooks. There is no limit to what markets users can make predictions on. And the more users betting on a specific event outcome, the more likely they think that outcome will happen.

Moreover, the predictions in DPMs will reflect the public’s opinion, proportionate to their individual conviction or confidence in the likelihood of a particular outcome occurring (i.e. “Outcome X”). As users become more confident in “Outcome X”, they tend to wager higher amounts of money on “Outcome X.” This proportional relationship reflects the users’ confidence in their prediction and will be reflected by the price of tokens in a market.

The ability of DPMs to crowdsource predictions by aggregating opinions offers several advantages:

• Improved Prediction Accuracy: DPMs harness the collective knowledge and insights of a large and diverse group of participants. By aggregating the predictions and beliefs of many individuals, these markets can often provide more accurate and reliable forecasts than individual experts or centralized institutions.
• Improved Market Research and Insights: DPMs offer valuable insights into market sentiment, allowing businesses, analysts, and researchers to gauge public sentiment or expectations about future events. DPMs incentivize participants to reveal their true beliefs by allowing them to profit from accurate predictions. This can lead to efficient price discovery, where the market prices reflect the best available information because the more confident a user is in an outcome, the more that user will wager. It serves as a real-time data source for understanding trends, opinions, and potential outcomes.
• More Democratic Input: DPMs allow anyone to participate and express their opinions about future events, democratizing the forecasting process. Users can contribute their input, regardless of their background or expertise, contributing to the collective intelligence used in predicting events.

Vaidya, D. (2023)

These advantages are reiterated by multiple studies of centralized prediction markets.

Studies indicate that prediction markets outperform traditional forecasting methods like expert panels and political polls. For example, an internal prediction market at Best Buy was used to gather collective input from the employees on the floor (those closest to the customers) to predict gift card sales. The employees were incentivized with small gifts to participate.

The findings revealed that the collective average response from employees was highly accurate, with an accuracy rate of 99.5%. In contrast, the experts employed specifically for making predictions were less accurate, with an error margin of 5% (University of Minnesota Libraries Publishing, 2015).

Similarly, in a separate experiment predicting holiday sales, the collective prediction was highly precise, with a minuscule 0.1% deviation. Conversely, the accuracy of the experts in this instance was notably lower, with an error of 7% (University of Minnesota Libraries Publishing, 2015).

Now account for the fact that these studies are based on centralized prediction markets. As society will soon see, these advantages realized from centralized prediction markets are limited and may pale in comparison to the predictive powers that can be derived from DPMs.

In his book “The Wisdom of Crowds,” James Surowiecki outlines several criteria necessary for a crowd to be considered “smart” or effective at making accurate predictions and decisions (Surowiecki, J., 2004). These criteria include:

• Diversity: The crowd must consist of individuals with a wide range of backgrounds, knowledge, and perspectives. Diversity ensures that participants bring different pieces of information and insights to the table, increasing the likelihood of better decision-making.
• Decentralization: The crowd should not be subject to centralized control or influenced by a single authority. No one person or entity at the top should dictate the crowd’s answer. Decentralization allows for independent thinking and minimizes the risk of groupthink.
• Independence: Each participant in the crowd should make their judgments or predictions independently, focusing on their own information and analysis rather than being influenced by the opinions of others. Independence is crucial to maintaining the diversity of views.
• Collective Verdict: The crowd should provide a collective verdict that summarizes the opinions and predictions of the participants. The aggregation of individual insights into a collective judgment helps filter out individual biases and errors.

These criteria, when met, can lead to a “smart crowd” that is remarkably effective at making accurate forecasts, decisions, and predictions. Surowiecki’s work highlights the power of collective intelligence when harnessed correctly, emphasizing the importance of these criteria in various contexts, from prediction markets to business decision-making and problem-solving.

DPMs enable online ‘crowds’ to maximize these criteria to the fullest, as they are inherent to the DPM product and will only be strengthened as the product grows in popularity.

• The more users → the more decentralized the crowd will be.
• The more decentralized → the more diverse and independent the pool of users.

In addition to the above benefits, blockchain technology and smart contracts will allow DPMs to advance faster than centralized markets due to the inherent rapid iteration capabilities of the technology.

Other Advantages

DPMs offer diverse advantages beyond their primary function of forecasting. The below section outlines the added advantages provided by DPMs.

• Risk Management: Risk management stands as a pivotal advantage within DPMs. Users are empowered with a unique tool for hedging and mitigating risks associated with uncertain future events. By engaging in bets across various outcomes, users can strategically reduce their exposure to potential losses, an approach not commonly available in traditional investment models.

For example, A farmer in Australia heavily relies on adequate rainfall for a successful crop season. Concerned about potential drought conditions impacting the harvest, the farmer turns to a prediction market. By predicting a scenario with very low rainfall in the prediction market, the farmer hedges against the risk of drought.

If light rainfall occurs, and this affects the crops, the farmer receives compensation from the prediction market, helping offset the losses from the poor harvest. On the other hand, if there’s heavy rainfall leading to a successful harvest, the farmer might not win the prediction market bet but still benefits from a flourishing crop. This way, the farmer uses the prediction market to mitigate the risk of a failed harvest due to insufficient rainfall.

• Transparency and Trustlessness: The integration of blockchain technology in DPMs ensures an unparalleled level of transparency and trustlessness. Through the execution of smart contracts, these markets operate autonomously, guaranteeing fairness and accuracy without the need for central authority intervention. This high level of transparency not only fosters trust among participants but also significantly diminishes the likelihood of manipulation, thereby bolstering the credibility and integrity of the market.

These additional advantages further highlight the versatile and transformative nature of DPMs, demonstrating their broader relevance and impact beyond merely forecasting future events.

Disadvantages

DPMs present numerous promising opportunities but are also met with significant hurdles. Below outlines four of the primary challenges faced by DPMs. Understanding and resolving these challenges is vital for the progress of DPMs.

1. Liquidity Constraints: While popular predictions like Ethereum’s future price or NFL games garner substantial liquidity, niche or specific predictions struggle to attract enough participants. This scarcity in liquidity makes it difficult for significant bets to be placed, resulting in relatively smaller winnings. However, due to the decentralized and global nature of DPMs, liquidity can grow rapidly as their popularity increases.
2. Regulatory Concerns: There are concerns regarding regulatory compliance within DPMs. The use of private and permissionless technology could potentially enable money laundering, making regulatory clarity essential. Mainstream participation may be deterred until better regulatory frameworks and Know Your Customer (KYC) and Anti-Money Laundering (AML) solutions are implemented.
3. Smart Contract Security Risk: Placing bets on prediction markets involves storing funds in smart contracts until the event concludes. The longer funds remain on public smart contracts and the larger the fund pool becomes, the risk of hacking attempts grows significantly. As the Decentralized Finance (DeFi) space is still nascent, securing large pools of funds remains uncertain. To address this, robust security practices and insurance protocols are required to guarantee bettors’ deposits in case of a security breach.
4. Ethical Concerns: With the liberty of allowing users to create their own markets, comes the potential risk of markets being created on ethically questionable outcomes. This raises ethical dilemmas due to the potential profiting from misfortunes. This risk is something that DPMs must monitor and eliminate as the product develops.

Conclusion

In conclusion, Decentralized Prediction Markets (DPMs) offer an innovative and transformative platform that harnesses collective intelligence, powered by blockchain technology. These markets revolutionize the way insights are gathered and forecasts are made. By democratizing predictions and offering transparent, secure, and fair platforms for users, DPMs can significantly enhance forecasting accuracy and crowd-sourced decision-making.

Furthermore, these markets, free from the traditional centralized control of typical betting and forecasting platforms, empower individuals and organizations with the ability to predict and gain insights into a diverse range of events. As DPMs continue to expand and develop, they stand to benefit from even greater liquidity and global reach. Adequate oversight, can address regulatory and ethical concerns to position themselves as a significant force in forecasting and risk management, ensuring they remain a valuable tool for predicting future events.

References

Vaidya, D. (2023). Prediction Market. Wall Street Mojo. Retrieved from https://www.wallstreetmojo.com/prediction-market/

University of Minnesota Libraries Publishing. (2015). “Information Systems: A Manager’s Guide to Harnessing Technology”, in University of Minnesota Libraries Publishing. Retrieved from https://open.lib.umn.edu/informationsystems/chapter/7-7-prediction-markets-and-the-wisdom-of-crowds.

Surowiecki, J. (2004). “The Wisdom of Crowds”, in Doubleday; Anchor.