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0 sats \ 1 reply \ @0xIlmari 29 Jan \ parent \ on: 🚀 We’re Back Online! 🎉 oracle
Don't you think this should be put out somewhere in the documentation instead of coaxed out of you in here?
In an ordinary market, participants trade only with each other and no trade can happen unless someone puts up a limit order first and becomes a maker. Impact of a market order on price can be easily estimated by studying how deep it would penetrate the order book. In a prediction market, the price IS then the probability.
You instead decided on an opaque system where contracts can magically come into existence based on unknown rules and there is no price (and therefore probability) discovery.
If you want to attract traders and market makers (maybe you don't) instead of just gamblers, then what the platform does and how exactly it decides prices should be sufficiently documented so that anyone could reproduce the price estimations (I don't even see pricing requests in the API so it must be baked into your obfuscated JS).
And I don't mean the liquidity_bot. You can operate whatever bots on your own platform as long as they are equal participants to your customers. But what the platform itself is doing should be known.
Thanks for pointing this out! Our pricing is based on the Logarithmic Market Scoring Rule (LMSR), which dynamically adjusts prices based on demand. Here’s why we use LMSR instead of a traditional order book:
1. Transparency & Simplicity: LMSR eliminates the need for manual bids/offers, making it easier for users to participate without worrying about matching opposing trades.
2. Liquidity Assurance: Even in low-activity markets, LMSR guarantees liquidity by algorithmically setting prices, so there’s always a trade opportunity.
3. Efficient Pricing: Prices are directly tied to demand. As more shares are bought (e.g., “YES”), their price rises, and the opposing shares (e.g., “NO”) become cheaper, maintaining balance.
That said, we’re actively working on adding detailed documentation and transparent pricing formulas to help users better understand and even replicate these mechanics programmatically. Stay tuned for the API updates!
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