most citedMachine Learning Optimization Algorithms & Portfolio Allocation

7 citations · 15 across the 5 of their papers we have counts for

collaborators

5 papers

q-fin.PM20204 cited

Measuring and Managing Carbon Risk in Investment Portfolios

Théo Roncalli, Théo Le Guenedal, Frédéric Lepetit +2

This article studies the impact of carbon risk on stock pricing. To address this, we consider the seminal approach of Görgen \textsl{et al.} (2019), who proposed estimating the car…

cs.LG20201 cited

Improving the Robustness of Trading Strategy Backtesting with Boltzmann Machines and Generative Adversarial Networks

Edmond Lezmi, Jules Roche, Thierry Roncalli +1

This article explores the use of machine learning models to build a market generator. The underlying idea is to simulate artificial multi-dimensional financial time series, whose s…

q-fin.PM20197 cited

Machine Learning Optimization Algorithms & Portfolio Allocation

Sarah Perrin, Thierry Roncalli

Portfolio optimization emerged with the seminal paper of Markowitz (1952). The original mean-variance framework is appealing because it is very efficient from a computational point…

q-fin.PM20193 cited

Financial Applications of Gaussian Processes and Bayesian Optimization

Joan Gonzalvez, Edmond Lezmi, Thierry Roncalli +1

In the last five years, the financial industry has been impacted by the emergence of digitalization and machine learning. In this article, we explore two methods that have undergon…

q-fin.PM2019

Constrained Risk Budgeting Portfolios: Theory, Algorithms, Applications & Puzzles

Jean-Charles Richard, Thierry Roncalli

This article develops the theory of risk budgeting portfolios, when we would like to impose weight constraints. It appears that the mathematical problem is more complex than the tr…