Machine learning
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Thematic Paper 13.01.2023 What Artificial Intelligence reveals about share price reactions?

What AI reveals about stock prices?- this piece outlines research by Amundi on the usefulness of using AI in stock analysis and valuation.

More > 10 minutes
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Working Paper 13.01.2023 What do we Learn from a Machine Understanding News Content? Stock Market Reaction to News

Using textual data extracted by Causality Link platform from a large variety of news sources (news stories, call transcripts, broker research, etc.), we build aggregate news signals that take into account the tone, the tense and the prominence of various news statements about a given firm.

More > 10 minutes
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Working Paper 22.09.2022 Real-Time Macro Information and Bond Return Predictability: A Weighted Group Deep Learning Approach

This paper proposes a weighted group neural network model and reexamines whether treasury bond returns are predictable when real-time, instead of fully-revised, macro information is used.

More > 10 minutes
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Working Paper 1.07.2022 Credit Factor Investing with Machine Learning techniques

The most common models to assess asset returns are a linear combination of risk factors.

More > 10 minutes
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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
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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
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Working Paper 26.04.2021 Robo-Advising: Less AI and More XAI?
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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
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Working Paper 7.07.2020 Improving the Robustness of Trading Strategy Backtesting with Boltzmann Machines and Generative Adversarial Networks
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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
  • 60
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Working Paper 2.10.2019 Machine Learning Optimization Algorithms & Portfolio Allocation
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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
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