LAMSADE
Benhamou Éric
Doctorant
Publications
Articles
Benhamou É. (2018), Gram Charlier and Edgeworth expansion for sample variance, Theoretical Mathematics and Applications, vol. 8, n°4, p. 17-31
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., 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
Saltiel D., Benhamou É., Laraki R., Atif J. (2021), Trade Selection with Supervised Learning and Optimal Coordinate Ascent (OCA), in , elsevier, Berlin Heidelberg, Springer International Publishing, 1-15 p.
Benhamou É., Saltiel D., Ohana J-J., Atif J. (2021), House allocation with randomly generated preference lists, in , Piscataway, NJ, IEEE - Institute of Electrical and Electronics Engineers, 10050 - 10057 p.
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., Saltiel D., Verel S. (2020), Bayesian CMA-ES: a new approach, in , elsevier, New York, NY, ACM - Association for Computing Machinery, 203-204 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), Regime change detection with GBDT and Shapley values, 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., 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., Ohana J., Saltiel D., Guez B. (2021), Detecting crisis event with Gradient Boosting Decision Trees, 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 E., Atif J., Laraki R., Saltiel D. (2020), NGO-GM: Natural Gradient Optimization for Graphical Models, 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), Bridging the gap between Markowitz planning and deep reinforcement learning, Paris, Preprint Lamsade
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.
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. (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., 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., 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.