Master's Oral Thesis Defense: "Adaptive Optimal Market Making Strategy with Inventory Liquidation Cost"

Abstract: We find a general form of the optimal market making strategy for high-frequency market maker (HFM) in a discrete-time Limit Order Book (LOB). In our model, the optimal market making strategy is adaptive depending on the arrival of Market Order (MO) in the previous time intervals. We introduce a penalization on end-of-day stock inventory to prevent the HFM from holding too much inventory overnight. We provide a method to make each placement of Limit Orders (LO) dependent on previous information in the same trading day and prove the admissibility of the optimal market making strategy under some general assumptions. The empirical study shows the performance of the optimal strategy varies according to the method we use to make the strategy adaptive, but they all outperform the non-adaptive strategy and those which place LOs at fixed distance from the midprice.

Host: Jose Figueroa-Lopez