@Article{NMTMA-11-701,
author = {Qingqing Yang, Wai-Ki Ching, Tak-Kuen Siu and Zhiwen Zhang},
title = {A Markov-Driven Portfolio Execution Strategy with Market Impact},
journal = {Numerical Mathematics: Theory, Methods and Applications},
year = {2018},
volume = {11},
number = {4},
pages = {701--728},
abstract = {<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>},
issn = {2079-7338},
doi = {https://doi.org/10.4208/nmtma.2018.s02},
url = {http://global-sci.org/intro/article_detail/nmtma/12468.html}
}