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Bridging the gap between Markowitz planning and deep reinforcement learning
While researchers in the asset management industry have mostly focused o...
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Detecting and adapting to crisis pattern with context based Deep Reinforcement Learning
Deep reinforcement learning (DRL) has reached super human levels in comp...
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Variance Reduction in Actor Critic Methods (ACM)
After presenting Actor Critic Methods (ACM), we show ACM are control var...
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NGO-GM: Natural Gradient Optimization for Graphical Models
This paper deals with estimating model parameters in graphical models. W...
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Similarities between policy gradient methods (PGM) in Reinforcement learning (RL) and supervised learning (SL)
Reinforcement learning (RL) is about sequential decision making and is t...
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BCMA-ES II: revisiting Bayesian CMA-ES
This paper revisits the Bayesian CMA-ES and provides updates for normal ...
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BCMA-ES: A Bayesian approach to CMA-ES
This paper introduces a novel theoretically sound approach for the celeb...
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A discrete version of CMA-ES
Modern machine learning uses more and more advanced optimization techniq...
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Trade Selection with Supervised Learning and OCA
In recent years, state-of-the-art methods for supervised learning have e...
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Feature selection with optimal coordinate ascent (OCA)
In machine learning, Feature Selection (FS) is a major part of efficient...
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Kalman filter demystified: from intuition to probabilistic graphical model to real case in financial markets
In this paper, we revisit the Kalman filter theory. After giving the int...
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Gram Charlier and Edgeworth expansion for sample variance
In this paper, we derive a valid Edgeworth expansions for the Bessel cor...
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T-statistic for Autoregressive process
In this paper, we discuss the distribution of the t-statistic under the ...
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A few properties of sample variance
A basic result is that the sample variance for i.i.d. observations is an...
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Seven proofs of the Pearson Chi-squared independence test and its graphical interpretation
This paper revisits the Pearson Chi-squared independence test. After pre...
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Connecting Sharpe ratio and Student t-statistic, and beyond
Sharpe ratio is widely used in asset management to compare and benchmark...
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Incremental Sharpe and other performance ratios
We present a new methodology of computing incremental contribution for p...
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