activity
20182020
most citedKalman filter demystified: from intuition to probabilistic graphical model to real case in financial markets

2 citations · 2 across the 3 of their papers we have counts for

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Showing 2019Show all

8 papers · 1 filter

q-fin.RM2019

Omega and Sharpe ratio

Eric Benhamou, Beatrice Guez, Nicolas Paris1

Omega ratio, defined as the probability-weighted ratio of gains over losses at a given level of expected return, has been advocated as a better performance indicator compared to Sh…

cs.LG2019

Variance Reduction in Actor Critic Methods (ACM)

Eric Benhamou

After presenting Actor Critic Methods (ACM), we show ACM are control variate estimators. Using the projection theorem, we prove that the Q and Advantage Actor Critic (A2C) methods…

q-fin.RM2019

Testing Sharpe ratio: luck or skill?

Eric Benhamou, David Saltiel, Beatrice Guez +1

Sharpe ratio (sometimes also referred to as information ratio) is widely used in asset management to compare and benchmark funds and asset managers. It computes the ratio of the (e…

cs.LG2019

NGO-GM: Natural Gradient Optimization for Graphical Models

Eric Benhamou, Jamal Atif, Rida Laraki +1

This paper deals with estimating model parameters in graphical models. We reformulate it as an information geometric optimization problem and introduce a natural gradient descent s…

cs.LG2019

Similarities between policy gradient methods (PGM) in Reinforcement learning (RL) and supervised learning (SL)

Eric Benhamou

Reinforcement learning (RL) is about sequential decision making and is traditionally opposed to supervised learning (SL) and unsupervised learning (USL). In RL, given the current s…

cs.LG2019

BCMA-ES II: revisiting Bayesian CMA-ES

Eric Benhamou, David Saltiel, Beatrice Guez +1

This paper revisits the Bayesian CMA-ES and provides updates for normal Wishart. It emphasizes the difference between a normal and normal inverse Wishart prior. After some computat…