activity
20242026
collaborators

5 papers

q-fin.CP2026

Time-Inhomogeneous Volatility Aversion for Financial Applications of Reinforcement Learning

Federico Cacciamani, Roberto Daluiso, Marco Pinciroli +2

In finance, sequential decision problems are often faced, for which reinforcement learning (RL) emerges as a promising tool for optimisation without the need of analytical tractabi…

q-fin.TR2025

Reinforcement Learning in Queue-Reactive Models: Application to Optimal Execution

Tomas Espana, Yadh Hafsi, Fabrizio Lillo +1

We investigate the use of Reinforcement Learning for the optimal execution of meta-orders, where the objective is to execute incrementally large orders while minimizing implementat…

q-fin.TR2025

Optimal Execution with Reinforcement Learning

Yadh Hafsi, Edoardo Vittori

This study investigates the development of an optimal execution strategy through reinforcement learning, aiming to determine the most effective approach for traders to buy and sell…

cs.CE2025

Leveraging LLMS for Top-Down Sector Allocation In Automated Trading

Ryan Quek Wei Heng, Edoardo Vittori, Keane Ong +3

This paper introduces a methodology leveraging Large Language Models (LLMs) for sector-level portfolio allocation through systematic analysis of macroeconomic conditions and market…

q-fin.TR2024

Exploiting Risk-Aversion and Size-dependent fees in FX Trading with Fitted Natural Actor-Critic

Vito Alessandro Monaco, Antonio Riva, Luca Sabbioni +5

In recent years, the popularity of artificial intelligence has surged due to its widespread application in various fields. The financial sector has harnessed its advantages for mul…