> 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
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buybacks. Discounts would have given users a small, predictable benefit, while the majority
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of fees were still destined for buybacks and redistribution. But as we refined the system, it
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became clear that discounts were a distraction. They cap user benefit at pennies on the
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dollar, while also draining strength from the treasury. The real compounding effect always
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came from the buybacks.

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By removing discounts entirely and channeling fees exclusively into buybacks and Spoils, the
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system became stronger, cleaner, and more reflexive. Every dollar of fees now works twice:
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first, by lifting the entire market cap through price impact on thin liquidity, and second, by
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handing Spoils to users at the lower pre-buyback price. It is the same phenomenon we saw
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during Hyperliquid’s airdrops: shallow liquidity meant every fee dollar pushed price
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disproportionately higher, while distributed tokens arrived already marked up in value.
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Jester’s model embraces that reflexivity — ensuring that both whales and smaller traders
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receive more net value than rebates could ever deliver.

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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.

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The result is a system that is not only fairer and more sustainable, but also places us in a
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credible position to scale to $1B and beyond.