6 papers
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…
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…
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…
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…
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…
Option Hedging with Risk Averse Reinforcement Learning
Edoardo Vittori, Michele Trapletti, Marcello Restelli
In this paper we show how risk-averse reinforcement learning can be used to hedge options. We apply a state-of-the-art risk-averse algorithm: Trust Region Volatility Optimization (…