I like the concept of decentralized prediction markets a lot but i have seen the shortcommings from decentralized prediction markets. Maybe you can help me understand with 2 real life examples how predyx would handle those better:
One good example would be what happened in polymarket.

Venezuela

The market was "who wins the venezuelan election" with the primary source "venezuelan official statement". So most participants betted Maduro Yes, because they expected it to be rigged. And the official statement was as expected: Maduro won. There was a catch though. The second source was "consensus of reporting". The market went through UMA multiple times and resulted in Maduro No.
How would you avoid this mess? Only a single source of truth?

Kennedy

Another example: "Will Kennedy withdraw from the presidential race by Friday" (The Friday he announced supporting the Trump campaign)
The market resolved to yes despite Kennedy repeatedly stating that he will only suspend his campaign while still running in the race. He made a deal to withdraw from the ballot in some states while still running in most states and even applying for new states. He also explained a way how he still can become president.

closing thoughts

Things like those destroyed trust in the platform and made people think twice if they are really betting the event or betting on betting the event.
So please explain for the two examples how you would avoid this problem. There is a lot of money at stake and actors from both positions (yes and no) will try to influence how the market resolves, also using scam tactics.
Disclaimer: We've used ChatGPT for grammatical corrections and formatting.
We totally understand the concerns raised from previous experiences with decentralized prediction markets. Let me address both examples and explain how PREDYX would handle them differently:
1. Venezuela Election Market
In the Polymarket example, confusion arose because there were conflicting sources of truth: "official statement" vs. "consensus of reporting." At PREDYX, we would avoid this by sticking to a single, clearly defined source of truth. For political events like elections, we would use one official source, such as the final certified results from the country’s electoral authority. This eliminates ambiguity and prevents scenarios where participants are confused by conflicting sources. If an event were difficult to verify or there were conflicting reports, we would consult trusted peer markets (e.g., Kalshi) and assess the best course of action.
In rare cases, if there's still too much uncertainty, we might cancel the market and refund users based on current share valuations to maintain trust.
2. Kennedy Campaign Withdrawal Market
In cases like Kennedy’s partial withdrawal, the phrasing of the market question is crucial. At PREDYX, we ensure that questions are framed in a way that can be objectively verified with clear criteria. In this case, the market could be phrased as “Will Kennedy completely drop out of the race?” with specific terms around what "withdrawal" means (e.g., removal from ballots in all states or an official public declaration of a full withdrawal). This removes the ambiguity and provides clarity, so the market can be fairly resolved.
3. 2024 U.S. Presidential Election Market (Trump Example)
To further demonstrate how we handle clear resolution criteria, consider this example:
Resolution Criteria:
The market will resolve to "Yes" if Donald J. Trump is officially declared the winner of the 2024 U.S. Presidential Election, certified by Congress based on the U.S. Electoral College results. The official verification will come from the U.S. Federal Election Commission (FEC). If Trump is not declared the winner by the FEC, the market will resolve to "No."
This approach guarantees that only one official source—in this case, the FEC—is used to verify the outcome, minimizing confusion and manipulation attempts.
Closing Thoughts
We understand the importance of trust and transparency in prediction markets, and that’s why we’ve designed PREDYX to avoid these pitfalls:
  • Clear resolution criteria for every market, based on a single, objective source of truth.
  • A centralized resolution team (for now) that evaluates ambiguous cases with caution and fairness.
  • The ability to cancel and refund markets in extreme, unverifiable cases to protect users.
By being precise with market phrasing and sticking to verifiable events, we aim to make PREDYX a reliable and trustworthy platform. We're also building a system that discourages manipulation by providing well-defined rules from the start.
Hope this has answered some of your concerns, please share your advice if you think there are better ways of handling such situations.
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This sounds nice, as long as the team is not invested in the bets it resolves. I do not suggest this is the case, i just want to highlight the contra of centralized resolving.
Regarding the cancelation of a market: would it be possible to refund at the individual price the participants entered the market? Otherwise it would not really be a refund but more like a forced liquidation at marketprice.
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I'm glad I could address some of your concerns! We're still a small team, and funnily enough, none of us have a real interest in betting ourselves—we just love creating markets. That’s what gets us excited! Internally, we even compete based on metrics like the number of traders, trading volume, and even market likes. It’s basically our version of Instagram!
As for market cancellations, we're still ironing out the details. To give you a better sense of our approach, we use the LMSR (Logarithmic Market Scoring Rule) algorithm for pricing and odds calculations. Unlike traditional crypto trading, where market makers and takers are abundant, prediction markets don’t work the same way. That’s why liquidity is crucial for market fluidity, and we’ll be injecting a significant amount of it ourselves to keep things moving.
In the event of a market cancellation, we’re planning to forfeit our injected liquidity to compensate traders. However, we also plan to allow external Liquidity Providers (LPs) to inject liquidity based on a fee-sharing model. Here’s where the dilemma lies: we can’t expect external LPs to forfeit their stake in case of a cancellation. This is a tricky situation, and it’s going to take us some time to finalize a fair and acceptable market cancellation policy.
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Thank you for the details, i understand the problem better now. Maybe you could put aside some yield from fees to an "insurance fund". This fund could be used to mitigate the impact on users in case of the cancellation of a market. This would only be possible if a cancellation is a rare case, otherwise the fund would never get to a decent level ;) All in all this is a problem to be addressed later on i guess.
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Thanks for suggesting the "insurance fund"! It’s a fantastic idea to create a pool to hedge against market cancellation risks. Cancellations should be rare, so having an insurance fund in place could actually be a smart and effective way to mitigate any potential impact. We’ll definitely be exploring how this could work in practice!
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Very interested in the answers to these two examples, too. I don't think there will be reassuring answers, but who knows :)
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Hey @south_korea_ln, I hope I was able to provide some reassurance with my responses. I’ve tried to be as transparent as possible! By the way, we’re the same team behind Triible (the Sportsbook on LN), though we’ve grown a bit in size since then. We’ve got some exciting updates coming for Triible—soon, it will offer fixed odds betting on prediction markets, effectively becoming a market maker for Predyx. Ultimately, Triible will evolve from a traditional Sportsbook into a SportsMarket, where all sports bets are backed by the market itself. Big things are on the horizon!
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