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Multi-objective portfolio optimization in stock market
Author(s)
Date Issued
2017
ISSN
2223--523X
Citation
International Journal of Design, Analysis and Tools for Integrated Circuits and Systems, Oct. 2017, vol. 6(1), pp. 63-67.
Type
Other Article
Abstract
Portfolio optimization is an important research area
in finance, because most investors would like to diversify their
investments by holding a portfolio rather than investing in a single
stock to earn a higher rate of return and to reduce risk.
Multi-objective portfolio optimization can achieve an optimal
portfolio which generates the highest rate of return with lowest
risk. This paper proposes a new approach to portfolio
construction, including stock selection and stock allocation. The
approach then is tested using stock price data and other financial
information of 113 stocks over a one-year period. K-means
clustering is applied on this dataset in order to categorize data into
several groups to finally identify a pool of potential stocks.
Finally, we construct the efficient frontier of optimal portfolios
using both the single-objective and multi-objective approaches and
compare the results.
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