A Data Envelopment Analysis Approach to Portfolio Selection: An Application to the Blue Chip Stocks in the Philippine Stock Exchange (2010-2019)
There has been a growing interest in the application of data envelopment analysis (DEA) as a nonparametric approach in portfolio optimization due to its flexibility in overcoming the limitations of the conventional mean-variance portfolio (MVP) model. Therefore, this study aims to validate the alloc...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | text |
| Published: |
Animo Repository
2021
|
| Subjects: | |
| Online Access: | https://animorepository.dlsu.edu.ph/res_aki/15 https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1010&context=res_aki |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | De La Salle University |
| Summary: | There has been a growing interest in the application of data envelopment analysis (DEA) as a nonparametric approach in portfolio optimization due to its flexibility in overcoming the limitations of the conventional mean-variance portfolio (MVP) model. Therefore, this study aims to validate the allocative efficiency of the DEA cross-efficiency model using blue chip stocks in the Philippine Stock Exchange from 2010 to 2019. This study finds that the proposed model is able to distinguish a unique set of best-performing stocks across each holding period and outperforms the MVP more consistently. The results of this study suggest that the proposed DEA cross-efficiency model can encourage more Filipinos to invest because it can provide an allocatively-efficient manner of selecting optimal stocks and incorporate other factors that affect the return and risk of a portfolio. Finally, this study suggests that future studies can examine this model using the entire Philippine stock market with an alternative set of criteria that affect stock returns and, ultimately, the stock’s performance. |
|---|