We propose an optimization framework for market-making in a limit-order book, based on the theory of stochastic approximation. We consider a discrete-time variant of the Avellaneda-Stoikov model similar to its development in an article of Laruelle, Lehalle and Pagès in the context of optimal...

We propose a decomposition of algorithm's a priori performance, from which we sep- arate contributions came from different factors. We show that, in combining estimations on volume and price and always taking into account the price-impact effect, one is able to optimize the execution in a...