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.
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