lo Norm sparse portfolio optimisation using proximal spectral gradient method on Malaysian stock market
In this paper, we introduce a modified norm-constraint mean-variance portfolio selection method. First, we use the Augmented Lagrangian method (ALM) to convert the objective function to an unconstrained objective function. Then, we apply the proximal spectral gradient method (PSG) onto the unconstra...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | en |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2025
|
| Online Access: | http://journalarticle.ukm.my/25314/1/ST%2024.pdf http://journalarticle.ukm.my/25314/ https://www.ukm.my/jsm/english_journals/vol54num2_2025/contentsVol54num2_2025.html |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1834522791441858560 |
|---|---|
| author | Choon, Kevin Liang Yew Wai, Kuan Wong Hong, Seng Sim Yong, Kheng Goh Wei, Yeing Pan Shin, Zhu Sim |
| author_facet | Choon, Kevin Liang Yew Wai, Kuan Wong Hong, Seng Sim Yong, Kheng Goh Wei, Yeing Pan Shin, Zhu Sim |
| author_sort | Choon, Kevin Liang Yew |
| building | Tun Sri Lanang Library |
| collection | Institutional Repository |
| content_provider | Universiti Kebangsaan Malaysia |
| content_source | UKM Journal Article Repository |
| continent | Asia |
| country | Malaysia |
| description | In this paper, we introduce a modified norm-constraint mean-variance portfolio selection method. First, we use the Augmented Lagrangian method (ALM) to convert the objective function to an unconstrained objective function. Then, we apply the proximal spectral gradient method (PSG) onto the unconstrained objective function to find an optimal sparse portfolio. This novel sparse portfolio optimization procedure encourages sparsity in the entire portfolio using – norm. The PSG utilizes a multiple damping gradient (MDG) method to solve the smooth terms of the function. The step size is computed using the Lipschitz constant. Also, PSG uses the iterative thresholding method (ITH) to solve – norm and induce the sparsity of the portfolio. The performance of the PSG is illustrated by its application on the Malaysian stock market. It is found that PSG’s sparse portfolio outperforms the equal weightage portfolio when the initial portfolio size is around 100 stocks and is prefiltered using the Sharpe ratio or the coefficient of variation. |
| format | Article |
| id | my-ukm.journal.25314 |
| institution | Universiti Kebangsaan Malaysia |
| language | en |
| publishDate | 2025 |
| publisher | Penerbit Universiti Kebangsaan Malaysia |
| record_format | eprints |
| spelling | my-ukm.journal.253142025-05-29T04:26:33Z http://journalarticle.ukm.my/25314/ lo Norm sparse portfolio optimisation using proximal spectral gradient method on Malaysian stock market Choon, Kevin Liang Yew Wai, Kuan Wong Hong, Seng Sim Yong, Kheng Goh Wei, Yeing Pan Shin, Zhu Sim In this paper, we introduce a modified norm-constraint mean-variance portfolio selection method. First, we use the Augmented Lagrangian method (ALM) to convert the objective function to an unconstrained objective function. Then, we apply the proximal spectral gradient method (PSG) onto the unconstrained objective function to find an optimal sparse portfolio. This novel sparse portfolio optimization procedure encourages sparsity in the entire portfolio using – norm. The PSG utilizes a multiple damping gradient (MDG) method to solve the smooth terms of the function. The step size is computed using the Lipschitz constant. Also, PSG uses the iterative thresholding method (ITH) to solve – norm and induce the sparsity of the portfolio. The performance of the PSG is illustrated by its application on the Malaysian stock market. It is found that PSG’s sparse portfolio outperforms the equal weightage portfolio when the initial portfolio size is around 100 stocks and is prefiltered using the Sharpe ratio or the coefficient of variation. Penerbit Universiti Kebangsaan Malaysia 2025 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/25314/1/ST%2024.pdf Choon, Kevin Liang Yew and Wai, Kuan Wong and Hong, Seng Sim and Yong, Kheng Goh and Wei, Yeing Pan and Shin, Zhu Sim (2025) lo Norm sparse portfolio optimisation using proximal spectral gradient method on Malaysian stock market. Sains Malaysiana, 54 (2). pp. 601-609. ISSN 0126-6039 https://www.ukm.my/jsm/english_journals/vol54num2_2025/contentsVol54num2_2025.html |
| spellingShingle | Choon, Kevin Liang Yew Wai, Kuan Wong Hong, Seng Sim Yong, Kheng Goh Wei, Yeing Pan Shin, Zhu Sim lo Norm sparse portfolio optimisation using proximal spectral gradient method on Malaysian stock market |
| title | lo Norm sparse portfolio optimisation using proximal spectral gradient method on Malaysian stock market |
| title_full | lo Norm sparse portfolio optimisation using proximal spectral gradient method on Malaysian stock market |
| title_fullStr | lo Norm sparse portfolio optimisation using proximal spectral gradient method on Malaysian stock market |
| title_full_unstemmed | lo Norm sparse portfolio optimisation using proximal spectral gradient method on Malaysian stock market |
| title_short | lo Norm sparse portfolio optimisation using proximal spectral gradient method on Malaysian stock market |
| title_sort | lo norm sparse portfolio optimisation using proximal spectral gradient method on malaysian stock market |
| url | http://journalarticle.ukm.my/25314/1/ST%2024.pdf http://journalarticle.ukm.my/25314/ https://www.ukm.my/jsm/english_journals/vol54num2_2025/contentsVol54num2_2025.html |
| url_provider | http://journalarticle.ukm.my/ |