TY - JOUR T1 - A Markov-Driven Portfolio Execution Strategy with Market Impact JO - Numerical Mathematics: Theory, Methods and Applications VL - 4 SP - 701 EP - 728 PY - 2018 DA - 2018/06 SN - 11 DO - http://doi.org/10.4208/nmtma.2018.s02 UR - https://global-sci.org/intro/article_detail/nmtma/12468.html KW - AB -

In this paper, we propose a framework for studying optimal agency execution strategies in a Limit Order Book (LOB) under a Markov-modulated market environment. The Almgren-Chriss's market impact model [1] is extended to a more general situation where multiple venues are available for investors to submit trades. Under the assumption of risk-neutrality, a compact recursive formula is derived, using the value iterative method, to calculate the optimal agency execution strategy. The original optimal control problem is then converted to a constrained quadratic optimization problem, which can be solved by using the Quadratic Programming (QP) approach. Numerical examples are given to illustrate the efficiency and effective of our proposed methods.