TY - JOUR
T1 - A Markov-Driven Portfolio Execution Strategy with Market Impact
AU - Qingqing Yang, Wai-Ki Ching, Tak-Kuen Siu & Zhiwen Zhang
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 - <p style="text-align: justify;">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&#39;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.</p>