Abstract
Portfolio selection problem introduced by Markowitz has been one of the most important research fields in modern finance. In this paper, we propose a model (least squares support vector machines (LSSVM)-mean-variance) for the portfolio management based on LSSVM. To verify the reliability of LSSVM-mean-variance model, we conduct an empirical research and design an algorithm to illustrate the performance of the model by using the historical data from Shanghai stock exchange. The numerical results show that the proposed model is useful when compared with the traditional Markowitz model. Comparing the efficient frontier and total wealth of both models, our model can provide a more measurable standard of judgment when investors do their investment.
| Original language | English |
|---|---|
| Article number | 4189683 |
| Journal | Mathematical Problems in Engineering |
| Volume | 2019 |
| DOIs | |
| Publication status | Published - 2019 Jan 1 |
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ASJC Scopus subject areas
- Mathematics(all)
- Engineering(all)
Cite this
Applying Least Squares Support Vector Machines to Mean-Variance Portfolio Analysis. / Wang, Jian; Kim, Junseok.
In: Mathematical Problems in Engineering, Vol. 2019, 4189683, 01.01.2019.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - Applying Least Squares Support Vector Machines to Mean-Variance Portfolio Analysis
AU - Wang, Jian
AU - Kim, Junseok
PY - 2019/1/1
Y1 - 2019/1/1
N2 - Portfolio selection problem introduced by Markowitz has been one of the most important research fields in modern finance. In this paper, we propose a model (least squares support vector machines (LSSVM)-mean-variance) for the portfolio management based on LSSVM. To verify the reliability of LSSVM-mean-variance model, we conduct an empirical research and design an algorithm to illustrate the performance of the model by using the historical data from Shanghai stock exchange. The numerical results show that the proposed model is useful when compared with the traditional Markowitz model. Comparing the efficient frontier and total wealth of both models, our model can provide a more measurable standard of judgment when investors do their investment.
AB - Portfolio selection problem introduced by Markowitz has been one of the most important research fields in modern finance. In this paper, we propose a model (least squares support vector machines (LSSVM)-mean-variance) for the portfolio management based on LSSVM. To verify the reliability of LSSVM-mean-variance model, we conduct an empirical research and design an algorithm to illustrate the performance of the model by using the historical data from Shanghai stock exchange. The numerical results show that the proposed model is useful when compared with the traditional Markowitz model. Comparing the efficient frontier and total wealth of both models, our model can provide a more measurable standard of judgment when investors do their investment.
UR - http://www.scopus.com/inward/record.url?scp=85069037170&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85069037170&partnerID=8YFLogxK
U2 - 10.1155/2019/4189683
DO - 10.1155/2019/4189683
M3 - Article
AN - SCOPUS:85069037170
VL - 2019
JO - Mathematical Problems in Engineering
JF - Mathematical Problems in Engineering
SN - 1024-123X
M1 - 4189683
ER -