8 citations · 16 across the 6 of their papers we have counts for
8 papers
Self-organised criticality in high frequency finance: the case of flash crashes
Jeremy D. Turiel, Tomaso Aste
With the rise of computing and artificial intelligence, advanced modeling and forecasting has been applied to High Frequency markets. A crucial element of solid production modeling…
Heterogenous criticality in high frequency finance: a phase transition in flash crashes
Jeremy Turiel, Tomaso Aste
Flash crashes in financial markets have become increasingly important attracting attention from financial regulators, market makers as well as from the media and the broader audien…
Deep Reinforcement Learning for Active High Frequency Trading
Antonio Briola, Jeremy Turiel, Riccardo Marcaccioli +2
We introduce the first end-to-end Deep Reinforcement Learning (DRL) based framework for active high frequency trading in the stock market. We train DRL agents to trade one unit of…
Simplicial persistence of financial markets: filtering, generative processes and portfolio risk
Jeremy D. Turiel, Paolo Barucca, Tomaso Aste
We introduce simplicial persistence, a measure of time evolution of network motifs in subsequent temporal layers. We observe long memory in the evolution of structures from correla…
Deep Learning modeling of Limit Order Book: a comparative perspective
Antonio Briola, Jeremy Turiel, Tomaso Aste
The present work addresses theoretical and practical questions in the domain of Deep Learning for High Frequency Trading. State-of-the-art models such as Random models, Logistic Re…
Wisdom of Crowds Detects COVID-19 Severity Ahead of Officially Available Data
Jeremy Turiel, Delmiro Fernandez-Reyes, Tomaso Aste
During the unfolding of a crisis, it is crucial to determine its severity, yet access to reliable data is challenging. We investigate the relation between geolocated Tweet Intensit…
Sector Neutral Portfolios: Long memory motifs persistence in market structure dynamics
Jeremy Turiel, Tomaso Aste
We study soft persistence (existence in subsequent temporal layers of motifs from the initial layer) of motif structures in Triangulated Maximally Filtered Graphs (TMFG) generated…
P2P Loan acceptance and default prediction with Artificial Intelligence
Jeremy D. Turiel, Tomaso Aste
Logistic Regression and Support Vector Machine algorithms, together with Linear and Non-Linear Deep Neural Networks, are applied to lending data in order to replicate lender accept…