Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11861/6219
Title: Multi-objective portfolio optimization in stock market
Authors: Ding, Yuan 
Liu, Ou 
Yao, Yiwei 
Ir. Dr. CHAN Chi On 
Issue Date: 2017
Source: International Journal of Design, Analysis and Tools for Integrated Circuits and Systems, Oct. 2017, vol. 6(1), pp. 63-67.
Journal: International Journal of Design, Analysis and Tools for Integrated Circuits and Systems 
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.
Type: Other Article
URI: http://hdl.handle.net/20.500.11861/6219
ISSN: 2223--523X
Appears in Collections:Business Administration - Publication

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