In modern finance, social investment portfolios have attracted the attention of researchers, investors, and practitioners. Regarding the long-term nature of this investment, the selection of the portfolios for a single period should be reconsidered as an online portfolio selection which focuses on the allocation of portfolios over multiple periods to maximize the expected growth rate of the portfolio. Besides common factors such as return on investment, many investors are willing to invest in assets complying with sustainability requirements. This study develops an online portfolio selection strategy that considers Environmental, Social, and Governance factors in addition to return and risk. Due to the diversity of constructed portfolios, different assets are first clustered based on their mutual information. The clustering model is selected through a comparison between four different clustering models. Then, a novel pattern-matching approach is implemented on the clustered assets that not only considers the amount of profitability of previous windows but also finds the optimal length and number of windows. After predicting the last groups of windows based on the pattern-matching, superior assets in terms of return and Sharpe ratio in each cluster are chosen, and the final portfolios are established regarding two scenarios; (i) a mean-variance strategy, and (ii) a developed mean-variance strategy which considers Environmental, Social, and Governance factors besides return and risk. The presented approaches are compared with several well-known benchmarks on four different datasets (i.e. 100 selective assets from S&P 500 index, S&P 500, Nikkei 225, and Dow Jones). The results indicate the superiority of the approach based on a simple mean-variance strategy over others in metrics such as Sharpe Ratio and Deflated Sharpe. Approaches containing Environmental, Social, and Governance factors also show not only profit and less volatility but the highest deflated Sharpe ratio, which can be considered as an excellent opportunity for investors to have responsible investing and have a better edge than the market.

(2024). A novel online portfolio selection approach based on pattern matching and ESG factors [journal article - articolo]. In OMEGA. Retrieved from https://hdl.handle.net/10446/290465

A novel online portfolio selection approach based on pattern matching and ESG factors

Barak, Sasan;
2024-01-01

Abstract

In modern finance, social investment portfolios have attracted the attention of researchers, investors, and practitioners. Regarding the long-term nature of this investment, the selection of the portfolios for a single period should be reconsidered as an online portfolio selection which focuses on the allocation of portfolios over multiple periods to maximize the expected growth rate of the portfolio. Besides common factors such as return on investment, many investors are willing to invest in assets complying with sustainability requirements. This study develops an online portfolio selection strategy that considers Environmental, Social, and Governance factors in addition to return and risk. Due to the diversity of constructed portfolios, different assets are first clustered based on their mutual information. The clustering model is selected through a comparison between four different clustering models. Then, a novel pattern-matching approach is implemented on the clustered assets that not only considers the amount of profitability of previous windows but also finds the optimal length and number of windows. After predicting the last groups of windows based on the pattern-matching, superior assets in terms of return and Sharpe ratio in each cluster are chosen, and the final portfolios are established regarding two scenarios; (i) a mean-variance strategy, and (ii) a developed mean-variance strategy which considers Environmental, Social, and Governance factors besides return and risk. The presented approaches are compared with several well-known benchmarks on four different datasets (i.e. 100 selective assets from S&P 500 index, S&P 500, Nikkei 225, and Dow Jones). The results indicate the superiority of the approach based on a simple mean-variance strategy over others in metrics such as Sharpe Ratio and Deflated Sharpe. Approaches containing Environmental, Social, and Governance factors also show not only profit and less volatility but the highest deflated Sharpe ratio, which can be considered as an excellent opportunity for investors to have responsible investing and have a better edge than the market.
articolo
2024
Fereydooni, Ali; Barak, Sasan; Asaad Sajadi, Seyed Mehrzad
(2024). A novel online portfolio selection approach based on pattern matching and ESG factors [journal article - articolo]. In OMEGA. Retrieved from https://hdl.handle.net/10446/290465
File allegato/i alla scheda:
File Dimensione del file Formato  
1-s2.0-S0305048323001391-main.pdf

Solo gestori di archivio

Versione: publisher's version - versione editoriale
Licenza: Licenza default Aisberg
Dimensione del file 9.18 MB
Formato Adobe PDF
9.18 MB Adobe PDF   Visualizza/Apri
Pubblicazioni consigliate

Aisberg ©2008 Servizi bibliotecari, Università degli studi di Bergamo | Terms of use/Condizioni di utilizzo

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/290465
Citazioni
  • Scopus 5
  • ???jsp.display-item.citation.isi??? 5
social impact