> For the complete documentation index, see [llms.txt](https://jester.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://jester.gitbook.io/docs/tokenomics/favour.md). # Favour ## Preface When we first designed Jester’s reward model, our plan was to combine fee discounts with \ buybacks. Discounts would have given users a small, predictable benefit, while the majority \ of fees were still destined for buybacks and redistribution. But as we refined the system, it \ became clear that discounts were a distraction. They cap user benefit at pennies on the \ dollar, while also draining strength from the treasury. The real compounding effect always \ came from the buybacks. \ By removing discounts entirely and channeling fees exclusively into buybacks and Spoils, the \ system became stronger, cleaner, and more reflexive. Every dollar of fees now works twice: \ first, by lifting the entire market cap through price impact on thin liquidity, and second, by \ handing Spoils to users at the lower pre-buyback price. It is the same phenomenon we saw \ during Hyperliquid’s airdrops: shallow liquidity meant every fee dollar pushed price \ disproportionately higher, while distributed tokens arrived already marked up in value. \ Jester’s model embraces that reflexivity — ensuring that both whales and smaller traders \ receive more net value than rebates could ever deliver. \ At today’s depth (Sept 8, 2025; $5.2m market cap, $522k liquidity split into $261k base-side WETH and $261k JEST), a purely mathematical AMM model suggests that \~$3.36m in cumulative base-side buybacks *could* move price enough to imply a $1B market cap. This example assumes static liquidity and is provided only to illustrate the reflexive effect of buybacks in thin pools. It is not a projection or guarantee of future outcomes. \ The result is a system that is not only fairer and more sustainable, but also places us in a \ credible position to scale to $1B and beyond. --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter: ``` GET https://jester.gitbook.io/docs/tokenomics/favour.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.