5 papers
Data-Driven Measures of High-Frequency Trading
Gbenga Ibikunle, Ben Moews, Dmitriy Muravyev +1
We introduce data-driven measures of high-frequency trading (HFT) that distinguish between liquidity-supplying and liquidity-demanding strategies. We train machine learning models…
DeXposure-FM: A Time-series, Graph Foundation Model for Credit Exposures and Stability on Decentralized Financial Networks
Aijie Shu, Wenbin Wu, Gbenga Ibikunle +1
Credit exposure in Decentralized Finance (DeFi) is often implicit and token-mediated, creating a dense web of inter-protocol dependencies. Thus, a shock to one token may result in…
Data-driven measures of high-frequency trading
G. Ibikunle, B. Moews, D. Muravyev +1
High-frequency trading (HFT) accounts for almost half of equity trading volume, yet it is not identified in public data. We develop novel data-driven measures of HFT activity that…
Minimal Batch Adaptive Learning Policy Engine for Real-Time Mid-Price Forecasting in High-Frequency Trading
Adamantios Ntakaris, Gbenga Ibikunle
High-frequency trading (HFT) has transformed modern financial markets, making reliable short-term price forecasting models essential. In this study, we present a novel approach to…
Online High-Frequency Trading Stock Forecasting with Automated Feature Clustering and Radial Basis Function Neural Networks
Adamantios Ntakaris, Gbenga Ibikunle
This study presents an autonomous experimental machine learning protocol for high-frequency trading (HFT) stock price forecasting that involves a dual competitive feature importanc…