20 citations · 36 across the 9 of their papers we have counts for
9 papers
Robust Causal Discovery in Real-World Time Series with Power-Laws
Matteo Tusoni, Giuseppe Masi, Andrea Coletta +3
Exploring causal relationships in stochastic time series is a challenging yet crucial task with a vast range of applications, including finance, economics, neuroscience, and climat…
LOB-Based Deep Learning Models for Stock Price Trend Prediction: A Benchmark Study
Matteo Prata, Giuseppe Masi, Leonardo Berti +6
The recent advancements in Deep Learning (DL) research have notably influenced the finance sector. We examine the robustness and generalizability of fifteen state-of-the-art DL mod…
On the Constrained Time-Series Generation Problem
Andrea Coletta, Sriram Gopalakrishan, Daniel Borrajo +1
Synthetic time series are often used in practical applications to augment the historical time series dataset for better performance of machine learning algorithms, amplify the occu…
Conditional Generators for Limit Order Book Environments: Explainability, Challenges, and Robustness
Andrea Coletta, Joseph Jerome, Rahul Savani +1
Limit order books are a fundamental and widespread market mechanism. This paper investigates the use of conditional generative models for order book simulation. For developing a tr…
K-SHAP: Policy Clustering Algorithm for Anonymous Multi-Agent State-Action Pairs
Andrea Coletta, Svitlana Vyetrenko, Tucker Balch
Learning agent behaviors from observational data has shown to improve our understanding of their decision-making processes, advancing our ability to explain their interactions with…
A-UAV: Application-Aware Content and Network Optimization of Edge-Assisted UAV Systems
Andrea Coletta, Flavio Giorgi, Gaia Maselli +4
To perform advanced surveillance, Unmanned Aerial Vehicles (UAVs) require the execution of edge-assisted computer vision (CV) tasks. In multi-hop UAV networks, the successful trans…
Learning to simulate realistic limit order book markets from data as a World Agent
Andrea Coletta, Aymeric Moulin, Svitlana Vyetrenko +1
Multi-agent market simulators usually require careful calibration to emulate real markets, which includes the number and the type of agents. Poorly calibrated simulators can lead t…
Towards Realistic Market Simulations: a Generative Adversarial Networks Approach
Andrea Coletta, Matteo Prata, Michele Conti +5
Simulated environments are increasingly used by trading firms and investment banks to evaluate trading strategies before approaching real markets. Backtesting, a widely used approa…
My SIM is Leaking My Data: Exposing Self-Login Privacy Breaches in Smartphones
Andrea Coletta, Gaia Maselli, Mauro Piva +2
We expose a new security leak for smartphone users, which allows to stole user personal data by accessing the mobile operator user page when auto-login is employed. We show how any…