Predicting Price Movements in High-Frequency Financial Data with Spiking Neural Networks

By Brian Ezinwoke, Oliver Rhodes

Published 2025-12-05

Everscope rating

1280.1

Relevance to quantitative trading

9 / 10

Implementation complexity

8 / 10

Reproducibility

3 / 5

About this paper

Methodology: STDP-trained Spiking Neural Networks with Bayesian Optimization. Problem types: Time Series Forecasting, Classification, Anomaly Detection, Algorithmic Execution, Optimization.

arXiv:2512.05868 · Paper rankings

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