A data envelopment analysis approach to portfolio selection: An application to the blue chip stocks in the Philippine Stock Exchange (2010-2019)

Due to the increasing complexity of investor behavior in emerging markets, there has been a growing interest in the application of Data Envelopment Analysis (DEA) as a non-parametric approach in portfolio optimization due to its flexibility in overcoming the limitations of the conventional Mean-Variance Portfolio (MVP) model. 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 under the 1-year holding period and underperforms the MVP under the 10-year holding period. Nevertheless, the DEA model is more versatile since it can incorporate other factors to reflect macroeconomic policy changes that affect the return and risk of a portfolio. The results of this study suggests that the proposed DEA cross-efficiency model can encourage more Filipinos to invest since it can provide an allocatively-efficient manner of selecting optimal stocks. 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