Sliipy

Every time Polymarket's server crashes, my MM strategy loses money (especially in sports markets), and it happens every month. This feeling really sucks. 🥲

Cut all those big KOLs who were promoting for free, did you have to be so ruthless about it...couldn't you have given them something?

Trading Volume can reflect the "quality" of price trends—price changes during high Trading Volume periods are more valuable for reference compared to low Trading Volume periods. High Trading Volume usually represents a consensus among a large number of market participants. From this perspective, to reflect the true probability of an event, a prediction market must first address the Liquidity issue and expand the market size, while most markets on Polymarket have not achieved this effect.

Open Source a copy of the current active market information of polymarket ( market and event ) Snapshot, the database uses SQLite3👇:

(1/2) The Bellman-Ford Algorithm can efficiently capture arbitrage opportunities by finding negative cycles: 👇
In the graph where the edges represent exchange rates, if the product of the exchange rates in a cycle is >1, it indicates the presence of arbitrage opportunities (, meaning the amount of currency increases after going around the cycle ). If the edges are represented as the negative logarithm of the exchange rates, it can equivalently and more simply be stated as "if a cycle is a negative cycle, it indicates the presence of arbitrage opportunities." At this point, the Bellman-Ford al

Quickly build quantitative strategy backtesting with MCP, which includes multiple strategies and is highly automated. It looks very interesting, and those who are interested can give it a try👇:

Quickly build strategy backtesting MCP, with built-in multiple strategies and high automation👇:

An event that has a "0 probability" in reality is often overestimated in the prediction market, possibly at 1%, 2%, or even 5%. The low point of probability in the prediction market depends on the expected "annualized" return of the arbitrageur. When the annualized return is too low, savvy arbitrageurs will become the counterparty of less savvy arbitrageurs—buying the Yes on impossible events at a low price. This is also a less obvious arbitrage path in the prediction market.

Share a polymarket subgraph resource, including service providers and usage tutorials👇:
🌟If you haven't used Subgraph, here is a brief introduction:
What is a subgraph? In simple terms, it is indexing on-chain data that is poorly readable for humans into human-readable data, and it allows users to access data efficiently through GraphQL queries (similar to SQL).
Originally, you would need to individually fetch on-chain events from the polymarket chain, filter the events, and then parse the ABI to extract the fields. With Subgraph, you can obtain the parsed data through a simple query, greatl

Haven't learned about Uniswap V3 yet? Here's a comprehensive collection of resources for learning UNI V3, covering everything from tutorials to projects in one place 👇:

#web3军火库# Share a Go language quantitative resource library, including but not limited to statistical tools, rate limiters, order book implementation, machine learning libraries, trading and backtesting tools, charts, web crawlers, sentiment analysis tools, and other resources.