Machine learning

Working-paper.jpg
Working Paper 1.12.2021 Graph Neural Networks for Asset Management

In this research article, Amundi Quantitative Research explores the use of graph theory and neural networks in asset management.

More > 10 minutes
  • PDF
Working-paper.jpg
Working Paper 7.06.2021 Robo-Advising for Small Investors: Evidence from Employee Savings Plans

We study the introduction of robo-advising on a large representative sample of Employees Saving Plans. The robo-advisor proposes a portfolio allocation and alerts investors if their allocation gets too far from the target, while investors remain free to follow or ignore the advices.

More > 10 minutes
  • PDF
Working-paper.jpg
Working Paper 26.04.2021 Robo-Advising: Less AI and More XAI?
19

We start by considering some of the key reasons behind the academic and industry interest in robo-advisors. We discuss how robo-advice could potentially address some fundamental problems in investors’ decision making as well as in traditional financial advice.

More > 10 minutes
  • PDF
  • 19
Working-paper.jpg
Working Paper 7.07.2020 Improving the Robustness of Trading Strategy Backtesting with Boltzmann Machines and Generative Adversarial Networks
60

In this article, we explore generative models in order to build a market generator. The underlying idea is to simulate artificial multi-dimensional financial time series, whose statistical properties are the same as those observed in the financial markets.

More > 10 minutes
  • PDF
  • 60
Working-paper.jpg
Working Paper 2.10.2019 Machine Learning Optimization Algorithms & Portfolio Allocation
30

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 of view.

More > 10 minutes
  • PDF
  • 30
Working-paper.jpg
Working Paper 11.03.2019 Financial Applications of Gaussian Processes and Bayesian Optimization
25

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 undergone rapid development in recent years: Gaussian processes and Bayesian optimization.

More > 10 minutes
  • PDF
  • 25

Get in touch with us

Our online help service is available to answer your question.

My personal information

If you have a question about our company or one of our products, please complete the form to get in touch. Please do not mention your account numbers or critical data in this form.

Civility*
CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.

(*) Required fields
All our job offers (Permanent and temporary position, Internship, Apprenticeship or VIE) are available on our dedicated website: https://jobs.amundi.com.

Register and apply directly online.

Amundi on Twitter