# High resolution microprice estimates from limit orderbook data using hyperdimensional vector Tsetlin Machines

arXiv: https://arxiv.org/abs/2411.13594 · HTML: https://mlsanity.com/paper/2411.13594/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 9 references that are in the map.
- First posted on arXiv 18 Nov 2024.

## Built on by (most cited first, 1 of 1)

- [Macroeconomic Message Passing for Anticipating Foreign Exchange Regime Changes: A Deep Logical Learning Approach using Graph Tsetlin Machines](https://mlsanity.com/paper/2607.06719/) (2026)

## Abstract (arXiv)

We propose an error-correcting model for the microprice, a high-frequency estimator of future prices given higher order information of imbalances in the orderbook. The model takes into account a current microprice estimate given the spread and best bid to ask imbalance, and adjusts the microprice based on recent dynamics of higher price rank imbalances. We introduce a computationally fast estimator using a recently proposed hyperdimensional vector Tsetlin machine framework and demonstrate empirically that this estimator can provide a robust estimate of future prices in the orderbook.