In this blog post series, we will present an analysis based on a reinforcement learning (RL) technique to address the problem of optimized trade execution in financial markets. We will then compare the performance of our model with the outcomes of the LIST Smart Order strategy.

Before starting to describe our reinforcement learning model for optimal execution, let us introduce a few elements which might be helpful to better understand some passages of the following posts.

In this blog post, we will present in detail the characteristics of our reinforcement learning model to approach the optimal execution problem.

In this blog post, we will present a preliminary analysis to test the performance of the NFK model against a naive strategy that we have called Surrogate Smart Order.

In this last episode of the series, we will present an extended analysis to test the performance of the NFK model against the LIST Smart Order strategy.