S2E4: Polymarket - Liquidity Rewards: Getting Started

Описание: In this episode, I walk through the process of building a liquidity-providing bot for Polymarket to earn automated rewards.

I discussed the mechanics of how Polymarket’s liquidity rewards program works, specifically focusing on the exponential reward curve and the importance of maintaining a tight spread near the midpoint. Throughout the stream, I used an AI-assisted coding workflow to build a TypeScript-based bot from scratch, covering everything from setting up a Gnosis Safe authenticated client to handling market-making logic.

I also shared a transparent look at the risks involved, including a live demonstration of where my strategy went wrong. I analyzed a "rekt" moment where the bot chased a crashing price and lost money due to adverse selection. To wrap up, I detailed the necessary fixes for the next iteration, such as inventory-aware pricing, threshold-based rebalancing, and tracking cost basis to avoid selling at a loss just to maintain liquidity.

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All links: https://linktr.ee/ali_run
Trader repo: https://github.com/Alirun/polymarket-...
Framework repo: https://github.com/Alirun/stream-fram...

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00:00:00 - Introduction and objective: Building a Polymarket bot
00:05:12 - Reviewing Polymarket’s liquidity reward mechanics
00:18:45 - Setting up the TypeScript project with AI assistance
00:32:10 - Authenticating with Gnosis Safe and API keys
00:47:30 - Fetching market data and identifying reward eligibility
01:02:15 - Implementing the core market-making logic
01:15:40 - Running the bot live: First orders on the book
01:30:25 - Analyzing the "Rekt" moment: Losing money live
01:42:10 - Post-mortem: Why the bot chased the price down
01:50:05 - Planning improvements: Inventory awareness and rebalancing
01:55:18 - Closing thoughts and goals for Episode 5