| Rank | Author | Strategy | Avg Edge |
|---|---|---|---|
| Rank | Author | Strategy | Avg Edge |
|---|---|---|---|
In this competition, you don’t just set fees — you control the entire swap function. Given reserves and an input amount, your strategy decides how much to output.
Write a Rust program that computes swap outputs and adapts to market conditions. Your code is compiled to BPF and scored over 1000 simulations with randomized parameters. Find the starter code here.
Volatility, retail flow, normalizer fees, and normalizer liquidity all vary across simulations — your strategy must adapt to conditions it can't see in advance.
Strategies ranked by average edge
| Rank | Author | Strategy | Avg Edge | Attempts |
|---|---|---|---|---|
| #1 | @demirelo | floors.finance | +491.74 | 1 |
| #2 | @basedfk | CLIZA.ai | +488.72 | 1 |
| #3 | @ChrisBerma65415 | Damp K50 A450 | +486.62 | 2 |
| #4 | @deligong | VolAdaptV1 | +482.99 | 9 |
| #5 | @kkuehlz | category.xyz | +477.43 | 4 |
| #6 | @josusanmartin | v1 | +477.34 | 5 |
| #7 | @0xQTpie | coolmathgames.com | +460.40 | 3 |
| #8 | @slashdowntown | Tiered Fee AMM Final | +460.03 | 2 |
| #9 | @egornomic | >-->(|:) | +458.88 | 3 |
| #10 | @bqbrady | SlopFi | +457.55 | 12 |