126 citations · 146 across the 6 of their papers we have counts for
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q-fin.CP2024
Data-driven measures of high-frequency trading
G. Ibikunle, B. Moews, D. Muravyev +1
Public data do not identify high-frequency trading (HFT), and standard proxies do not separate liquidity-supplying from liquidity-demanding strategies. We overcome this measurement…
q-fin.CP2020★ 20 cited
Predictive intraday correlations in stable and volatile market environments: Evidence from deep learning
Ben Moews, Gbenga Ibikunle
Standard methods and theories in finance can be ill-equipped to capture highly non-linear interactions in financial prediction problems based on large-scale datasets, with deep lea…
q-fin.CP2018★ 126 cited
Lagged correlation-based deep learning for directional trend change prediction in financial time series
Ben Moews, J. Michael Herrmann, Gbenga Ibikunle
Trend change prediction in complex systems with a large number of noisy time series is a problem with many applications for real-world phenomena, with stock markets as a notoriousl…