%0 Journal Article
%T High-Order Portfolio Optimization Problem with Background Risk
%A Xiaolu Zhou
%J Open Journal of Business and Management
%P 981-989
%@ 2329-3292
%D 2021
%I Scientific Research Publishing
%R 10.4236/ojbm.2021.93052
%X <span style=\"font-family:Verdana;\">After Markowitz proposed the mean-variance model, the research on
portfolio problems has been a hot topic for many investors.</span><span style=\"font-family:&quot;\"> </span><span style=\"font-family:Verdana;\">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.</span><span style=\"font-family:&quot;\"> </span><span style=\"font-family:Verdana;\">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.</span>
%K Background Risk
%K Higher Moment
%K Genetic Algorithm
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=108233