Trading

Enhancing Trading Strategy Robustness through Anomaly Detection

This project explores the use of anomaly detection techniques, such as One-Class SVM, to identify the conditions under which algorithmic trading strategies are likely to succeed, ensuring their applicability and extending the approach to portfolio-wide strategy optimization.

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JDSE 2022

The Junior Conference on DataScience and Engeneering 2022 (JDSE) took place on september 15-16, on the Polytechnique campus (Palaiseau).

Hugo Thimonier has the opportunity to present “TracInAD: Measuring Influence for Anomaly Detection” to the audience.

Marc Velay won the best poster contest with his poster about “Robustness Analysis of Deep RL for Portfolio Selection”.

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Autoencoders for trading

Predictive models based on autoencoders.

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Temporal Point Processes

Machine learning applied to Hawkes processes.

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