TITLE:
High-Order Portfolio Optimization Problem with Background Risk
AUTHORS:
Xiaolu Zhou
KEYWORDS:
Background Risk, Higher Moment, Genetic Algorithm
JOURNAL NAME:
Open Journal of Business and Management,
Vol.9 No.3,
April
2,
2021
ABSTRACT: After Markowitz proposed the mean-variance model, the research on
portfolio problems has been a hot topic for many investors. The research on portfolio
optimization is becoming more and more perfect. The investment theory changes
from second-order moment to high-order moment, and from single-stage to
multi-stage. More and more factors affecting portfolio optimization are taken
into consideration. In this
paper, a high-order portfolio optimization problem considering background risks
is studied. Firstly, an optimization model of high-order moments including
background risks is established, and the genetic algorithm is used to solve the
model. Finally, the effects of background risks and high-order moments on the
portfolio optimization model are analyzed empirically.