Curriculum vitae

Dernières publications

Articles

Benhamou É., Guez B., Paris N. (2018), Three remarkable properties of the Normal distribution for simple variance, Theoretical Mathematics and Applications, vol. 8, n°4, p. 1-15

Benhamou É., Guez B. (2018), Incremental Sharpe and other performance ratios, Journal of Statistical and Econometric Methods, vol. 7, n°4, p. 19-37

Benhamou É. (2018), Gram Charlier and Edgeworth expansion for sample variance, Theoretical Mathematics and Applications, vol. 8, n°4, p. 17-31

Benhamou É., Gobet E., Miri M. (2010), Time Dependent Heston Model, SIAM Journal on Financial Mathematics, vol. 1, n°1, p. 289-325

Benhamou É., Gobet E., Miri M. (2009), Smart expansion and fast calibration for jump diffusions, Finance and Stochastics, vol. 13, n°4, p. 563-589

Communications avec actes

Benhamou É., Saltiel D., Ohana J-J., Atif J., Laraki R. (2020), Deep Reinforcement Learning (DRL) for portfolio allocatio, in Dong, Yuxiao; Ifrim, Georgiana; Mladenić, Dunja, Springer, 527-531 p.

Benhamou É., Serval T. (2000), On the Competition between ECNs, Stock Markets and Market Makers, in Kurt Bauknecht, Sanjay Kumar Madria, Günther Pernul, Electronic Commerce and Web Technologies: 1st International Conference, EC-Web 2000, Springer, 291-300 p.

Communications sans actes

Beji C., Benhamou É., Bon M., Yger F., Atif J. (2020), Estimating Individual Treatment Effects throughCausal Populations Identification, 28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN 2020), Brugges, Belgique

Prépublications / Cahiers de recherche

Benhamou É., Ohana J., Saltiel D., Guez B. (2021), Detecting crisis event with Gradient Boosting Decision Trees, Paris, Preprint Lamsade

Benhamou É., Ohana J., Saltiel D., Guez B. (2021), Regime change detection with GBDT and Shapley values, Paris, Preprint Lamsade

Benhamou É., Saltiel D., Tabachnik S., Wong S., Chareyron F. (2021), Distinguish the indistinguishable: a Deep Reinforcement Learning approach for volatility targeting models, Paris, Preprint Lamsade

Ohana J., Ohana S., Benhamou É., Saltiel D., Guez B. (2021), Shapley values for LightGBM model applied to regime detection, Paris, Preprint Lamsade

Benhamou É. (2021), Distribution and statistics of the Sharpe Ratio, Paris, Preprint Lamsade

Ohana J., Benhamou É., Saltiel D., Guez B. (2021), Is the Covid equity bubble rational? A machine learning answer, Paris, Preprint Lamsade

Benhamou É., Saltiel D., Laraki R., Atif J. (2020), BCMA-ES: a conjugate prior Bayesian optimization view, Paris, Preprint Lamsade

Benhamou É., Saltiel D., Ungari S., Mukhopadhyay A. (2020), Time your hedge with Deep Reinforcement Learning, Paris, Preprint Lamsade

Benhamou É., Saltiel D., Ungari S., Mukhopadhyay A., Atif J. (2020), AAMDRL: Augmented Asset Management with Deep Reinforcement Learning, Paris, Preprint Lamsade

Benhamou É., Saltiel D., Ungari S., Mukhopadhyay A. (2020), Bridging the gap between Markowitz planning and deep reinforcement learning, Paris, Preprint Lamsade

Benhamou E., Atif J., Laraki R., Saltiel D. (2020), NGO-GM: Natural Gradient Optimization for Graphical Models, Paris, Preprint Lamsade

Saltiel D., Benhamou É. (2019), Sélection efficace de variables par montée par coordonnée avec garanties théoriques, Paris, Preprint Lamsade

Saltiel D., Benhamou É. (2019), Feature selection with optimal coordinate ascent (OCA), Paris, Preprint Lamsade, 15 p.

Benhamou É., Atif J., Laraki R. (2019), A short note on the operator norm upper bound for sub-Gaussian tailed random matrices, Paris, Preprint Lamsade, 12 p.

Benhamou É., Melot V. (2018), Seven proofs of the Pearson Chi-squared independence test and its graphical interpretation, Paris, Preprint Lamsade, 22 p.

Benhamou É. (2018), A few properties of sample variance, Paris, Preprint Lamsade, 15 p.

Saltiel D., Benhamou É. (2018), Trade Selection with Supervised Learning and OCA, Paris, Preprint Lamsade, 8 p.

Benhamou É. (2018), T-statistic for Autoregressive process, Paris, Preprint Lamsade, 24 p.

Benhamou É. (2018), Kalman filter demystified: from intuition to probabilistic graphical model to real case in financial markets, Paris, Preprint Lamsade, 45 p.

Benhamou É., Atif J., Laraki R., Laraki R. (2018), A new approach to learning in Dynamic Bayesian Networks (DBNs), Paris, Preprint Lamsade, 17 p.

Benhamou É., Atif J., Laraki R. (2018), A discrete version of CMA-ES, Paris, Preprint Lamsade, 13 p.

Benhamou É. (2018), Connecting Sharpe ratio and Student t-statistic, and beyond, Paris, Preprint Lamsade, 23 p.

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