Search Results for author: David Saltiel

Found 11 papers, 2 papers with code

Can ChatGPT Compute Trustworthy Sentiment Scores from Bloomberg Market Wraps?

no code implementations9 Jan 2024 Baptiste Lefort, Eric Benhamou, Jean-Jacques Ohana, David Saltiel, Beatrice Guez, Damien Challet

We used a dataset of daily Bloomberg Financial Market Summaries from 2010 to 2023, reposted on large financial media, to determine how global news headlines may affect stock market movements using ChatGPT and a two-stage prompt approach.

AAMDRL: Augmented Asset Management with Deep Reinforcement Learning

no code implementations30 Sep 2020 Eric Benhamou, David Saltiel, Sandrine Ungari, Abhishek Mukhopadhyay, Jamal Atif

Can an agent learn efficiently in a noisy and self adapting environment with sequential, non-stationary and non-homogeneous observations?

Asset Management reinforcement-learning +3

Bridging the gap between Markowitz planning and deep reinforcement learning

no code implementations30 Sep 2020 Eric Benhamou, David Saltiel, Sandrine Ungari, Abhishek Mukhopadhyay

While researchers in the asset management industry have mostly focused on techniques based on financial and risk planning techniques like Markowitz efficient frontier, minimum variance, maximum diversification or equal risk parity, in parallel, another community in machine learning has started working on reinforcement learning and more particularly deep reinforcement learning to solve other decision making problems for challenging task like autonomous driving, robot learning, and on a more conceptual side games solving like Go.

Asset Management Autonomous Driving +4

NGO-GM: Natural Gradient Optimization for Graphical Models

no code implementations14 May 2019 Eric Benhamou, Jamal Atif, Rida Laraki, David Saltiel

This paper deals with estimating model parameters in graphical models.

BCMA-ES II: revisiting Bayesian CMA-ES

no code implementations2 Apr 2019 Eric Benhamou, David Saltiel, Beatrice Guez, Nicolas Paris

We prove that the expected covariance should be lower in the normal Wishart prior model because of the convexity of the inverse.

BCMA-ES: A Bayesian approach to CMA-ES

no code implementations2 Apr 2019 Eric Benhamou, David Saltiel, Sebastien Verel, Fabien Teytaud

This paper introduces a novel theoretically sound approach for the celebrated CMA-ES algorithm.

Trade Selection with Supervised Learning and OCA

1 code implementation9 Dec 2018 David Saltiel, Eric Benhamou

We derive this new method using coordinate ascent optimization and using block variables.

feature selection

Feature selection with optimal coordinate ascent (OCA)

1 code implementation29 Nov 2018 David Saltiel, Eric Benhamou

OCA brings substantial differences and improvements compared to previous coordinate ascent feature selection method: we group variables into block and individual variables instead of a binary selection.

feature selection

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