# polymarket-kernel
Ultra-low latency computational core for Polymarket market making, based on the Logit Jump-Diffusion framework and an Avellaneda-Stoikov adaptation in logit space.
## Overview
`polymarket-kernel` implements a unified stochastic kernel for prediction markets where probabilities are transformed into log-odds and processed with vectorized math.
The crate is designed for:
- HFT backtesting engines
- live market-making bots
- inventory-aware quoting across large market batches
It exposes an FFI-safe Rust API backed by a C SIMD kernel.
Source paper:
- [Toward Black-Scholes for Prediction Markets (Shaw & Dalen, 2025)](https://arxiv.org/pdf/2510.15205)
## Features
- SoA (Structure of Arrays) layout for contiguous memory access and SIMD-friendly loads
- AVX-512 vectorized quote engine for batch processing
- Custom AVX-512 `log1p` approximation to avoid scalar fallback in spread computation
- Fast sigmoid approximation for `x -> p` mapping in hot paths
- Inventory-aware Avellaneda-Stoikov quoting in logit space
- Zero allocations in the hot path (pre-allocated input/output buffers)
- Numerically safe clamping for stable `logit`/`sigmoid` evaluation
## Quick Start
Install:
```bash
cargo add polymarket-kernel
```
Call `calculate_quotes_logit` with SoA input slices:
```rust
use polymarket_kernel::calculate_quotes_logit;
fn main() {
// SoA inputs for N markets.
let x_t = vec![0.15, -0.35, 0.90, -1.20];
let q_t = vec![10.0, -6.0, 3.0, 0.0];
let sigma_b = vec![0.22, 0.18, 0.30, 0.15];
let gamma = vec![0.08, 0.08, 0.08, 0.08];
let tau = vec![0.50, 0.50, 0.50, 0.50];
let k = vec![1.40, 1.25, 1.10, 1.80];
// Pre-allocated outputs (no hot-path allocation inside the kernel).
let mut bid_p = vec![0.0; x_t.len()];
let mut ask_p = vec![0.0; x_t.len()];
calculate_quotes_logit(
&x_t,
&q_t,
&sigma_b,
&gamma,
&tau,
&k,
&mut bid_p,
&mut ask_p,
);
for i in 0..x_t.len() {
println!("market {i}: bid={:.6}, ask={:.6}", bid_p[i], ask_p[i]);
}
}
```
## License
MIT