ESG Scoring System Construction: Portfolio Investment Based on Machine Learning

Research Article
Open access

ESG Scoring System Construction: Portfolio Investment Based on Machine Learning

Yulin Dong 1*
  • 1 Shanghai University of Finance and Economics, Shanghai 200433, China    
  • *corresponding author EvelinaDong@gmail.com
Published on 21 March 2023 | https://doi.org/10.54254/2754-1169/3/2022829
AEMPS Vol.3
ISSN (Print): 2754-1177
ISSN (Online): 2754-1169
ISBN (Print): 978-1-915371-15-7
ISBN (Online): 978-1-915371-16-4

Abstract

The majority of existing ESG rating systems in the Chinese market are based on categorical classification ratings, and as a result of the voluntary disclosure system, rating data provided by rating organizations is occasionally absent or delayed. This article employs natural language processing (NLP) to extract keywords such as green, clean, renewable, poverty alleviation, and moral from the financial reports of CSI 300 constituent companies, and then counts their corresponding frequencies in order to construct percentage ESG ratings that address the discontinuity, imprecision, and time lag inherent in the original ratings. This article employs a self-normalized neural network (SNN) to develop a multi factor model based on the suggested ESG ratings and then conducts sector neutral hierarchical back-testing to compare the proposed rating to the traditional ratings. The results indicate that the model generated using the ESG ratings developed in this research yields a higher rate of return than the model built using traditional ESG ratings, and the model constructed without an ESG factor. This may be because deriving ESG ratings directly from financial statements eliminates the risk of corporate falsification or whitewashing of accounts. This work adds to the body of knowledge by proposing a novel approach to constructing an ESG scoring system and incorporating it into portfolio investments to maximize returns.

Keywords:

Neural Network, ESG Investment, Natural Language Processing (NLP), Multi Factor Investment

Dong,Y. (2023). ESG Scoring System Construction: Portfolio Investment Based on Machine Learning. Advances in Economics, Management and Political Sciences,3,517-525.
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References

[1]. Rockness J, Schlachter P, Rockness H: Hazardous waste disposal, corporate disclosure, and financial performance in the chemical industry. Advances In Public Interest Accounting, 1.1986(1041-7060), 167-191(1986).

[2]. Jaggi, B., & Freedman, M.: An examination of the impact of pollution performance on eco-nomic and market performance: pulp and paper firms. Journal of business finance & account-ing, 19(5), 697-713 (1992).

[3]. Ziegler, A., Schröder, M., & Rennings, K.: The effect of environmental and social perfor-mance on the stock performance of European corporations. Environmental and Resource Eco-nomics, 37(4), 661-680 (2007).

[4]. Walley, N., & Whitehead, B.: It’s not easy being green. Reader in Business and the Environ-ment, 36(81), 4 (1994).

[5]. Gray, R., Kouhy, R., & Lavers, S.: Corporate social and environmental reporting: a review of the literature and a longitudinal study of UK disclosure. Accounting, Auditing & Accountabil-ity Journal (1995).

[6]. Hart, S. L., & Ahuja, G.: Does it pay to be green? An empirical examination of the relation-ship between emission reduction and firm performance. Business strategy and the Environ-ment, 5(1), 30-37 (1996).

[7]. Telle, K.: “It pays to be green”–a premature conclusion. Environmental and Resource Econom-ics, 35(3), 195-220 (2006).

[8]. Wen, S.B., & Fang, W.: Qiyie Shehui zeren yu Caiwu jixiao guanxi de shizheng yanjiu: Liyi xiangguanzhe shijiao de mianban shuju fenxi [An empirical study of the relationship between corporate social responsibility and financial performance: a panel data analysis from stake-holder perspectives]. Zhongguo gongye jingji, 10, 150-160 (2008).

[9]. Lv, J., & Jiao, S.Y.: Huanjing pilu, Huanjing jixiao he caiwu jixiao guanxi de shizheng yanjiu [An empirical study of the relationship between environmental disclosure, performance, and financial performance]. Shanxi caijing daxue xuebao, 1, 109-116 (2011).

[10]. Wang, B., & Zhao, Y.P.: Qiye huanjing jixiao yu caiwu jixiao xiangguanxing shizheng yanjiu [An empirical study on the correlation between corporate environmental and financial perfor-mance: Based on panel data of listed companies from 2006 to 2010]. Caikuai tongxun, 36, 50-52 (2012).

[11]. Hu, Q.Y.: Shangshi gongsi huanjing jixiao yu caiwu jixiao de xiangguanxing yanjiu [Study on the correlation between environmental and financial performance of listed companies]. Zhongguo rengou ziyuan yu huanjing, 6, 23-32 (2012).

[12]. Ye, C.G., & Qiu, L., & Zhang, L.J.: Gongsi zhili jiegou, neibu kongzhi zhiliang yu qiye caiwu jixiao [Corporate Governance Structure, Internal Control Quality and Corporate Financial Per-formance]. Shengji yanjiu, 2,104-112 (2016).

[13]. Yu, H.X., & Wang, Q.H.: Shiyou qiye huanjing jixiao pingjia zhibiao tixi goujian [Construc-tion of environmental performance evaluation index system for oil enterprises]. Shidai jing-mao, 27, 16-17 (2020).

[14]. Wang, W.Y., & Jia, Z.X.: Huanjing jixiao yu caiwu jixiao guanxi hangye bijiao yanjiu [Indus-try Study on the Relationship between Environmental and Financial Performance: Based on Data from Listed Companies in the Paper, Chemical, and Extractive Industries]. Kuaiji zhiyou, 11, 79-84 (2020).

[15]. Fisher, I. E., Garnsey, M. R., & Hughes, M. E.: Natural language processing in accounting, auditing and finance: A synthesis of the literature with a roadmap for future research. Intelli-gent Systems in Accounting, Finance and Management, 23(3), 157-214 (2016).

[16]. China Alliance of Social Value Investment (CASVI), China Asset Management Co. (China AMC): White Paper on ESG Development and Innovation in China 2021 (2021).

[17]. Nalini, R.: Optimal Portfolio construction using Sharpe’s Single Index Model-A study of se-lected stocks from BSE. International Journal of Advanced Research in Management and So-cial Sciences, 3(12), 72-93 (2014).

[18]. Klambauer, G., Unterthiner, T., Mayr, A., & Hochreiter, S.: Self-normalizing neural networks. Advances in neural information processing systems, 30 (2017).


Cite this article

Dong,Y. (2023). ESG Scoring System Construction: Portfolio Investment Based on Machine Learning. Advances in Economics, Management and Political Sciences,3,517-525.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 6th International Conference on Economic Management and Green Development (ICEMGD 2022), Part Ⅰ

ISBN:978-1-915371-15-7(Print) / 978-1-915371-16-4(Online)
Editor:Javier Cifuentes-Faura, Canh Thien Dang
Conference website: https://www.icemgd.org/
Conference date: 6 August 2022
Series: Advances in Economics, Management and Political Sciences
Volume number: Vol.3
ISSN:2754-1169(Print) / 2754-1177(Online)

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References

[1]. Rockness J, Schlachter P, Rockness H: Hazardous waste disposal, corporate disclosure, and financial performance in the chemical industry. Advances In Public Interest Accounting, 1.1986(1041-7060), 167-191(1986).

[2]. Jaggi, B., & Freedman, M.: An examination of the impact of pollution performance on eco-nomic and market performance: pulp and paper firms. Journal of business finance & account-ing, 19(5), 697-713 (1992).

[3]. Ziegler, A., Schröder, M., & Rennings, K.: The effect of environmental and social perfor-mance on the stock performance of European corporations. Environmental and Resource Eco-nomics, 37(4), 661-680 (2007).

[4]. Walley, N., & Whitehead, B.: It’s not easy being green. Reader in Business and the Environ-ment, 36(81), 4 (1994).

[5]. Gray, R., Kouhy, R., & Lavers, S.: Corporate social and environmental reporting: a review of the literature and a longitudinal study of UK disclosure. Accounting, Auditing & Accountabil-ity Journal (1995).

[6]. Hart, S. L., & Ahuja, G.: Does it pay to be green? An empirical examination of the relation-ship between emission reduction and firm performance. Business strategy and the Environ-ment, 5(1), 30-37 (1996).

[7]. Telle, K.: “It pays to be green”–a premature conclusion. Environmental and Resource Econom-ics, 35(3), 195-220 (2006).

[8]. Wen, S.B., & Fang, W.: Qiyie Shehui zeren yu Caiwu jixiao guanxi de shizheng yanjiu: Liyi xiangguanzhe shijiao de mianban shuju fenxi [An empirical study of the relationship between corporate social responsibility and financial performance: a panel data analysis from stake-holder perspectives]. Zhongguo gongye jingji, 10, 150-160 (2008).

[9]. Lv, J., & Jiao, S.Y.: Huanjing pilu, Huanjing jixiao he caiwu jixiao guanxi de shizheng yanjiu [An empirical study of the relationship between environmental disclosure, performance, and financial performance]. Shanxi caijing daxue xuebao, 1, 109-116 (2011).

[10]. Wang, B., & Zhao, Y.P.: Qiye huanjing jixiao yu caiwu jixiao xiangguanxing shizheng yanjiu [An empirical study on the correlation between corporate environmental and financial perfor-mance: Based on panel data of listed companies from 2006 to 2010]. Caikuai tongxun, 36, 50-52 (2012).

[11]. Hu, Q.Y.: Shangshi gongsi huanjing jixiao yu caiwu jixiao de xiangguanxing yanjiu [Study on the correlation between environmental and financial performance of listed companies]. Zhongguo rengou ziyuan yu huanjing, 6, 23-32 (2012).

[12]. Ye, C.G., & Qiu, L., & Zhang, L.J.: Gongsi zhili jiegou, neibu kongzhi zhiliang yu qiye caiwu jixiao [Corporate Governance Structure, Internal Control Quality and Corporate Financial Per-formance]. Shengji yanjiu, 2,104-112 (2016).

[13]. Yu, H.X., & Wang, Q.H.: Shiyou qiye huanjing jixiao pingjia zhibiao tixi goujian [Construc-tion of environmental performance evaluation index system for oil enterprises]. Shidai jing-mao, 27, 16-17 (2020).

[14]. Wang, W.Y., & Jia, Z.X.: Huanjing jixiao yu caiwu jixiao guanxi hangye bijiao yanjiu [Indus-try Study on the Relationship between Environmental and Financial Performance: Based on Data from Listed Companies in the Paper, Chemical, and Extractive Industries]. Kuaiji zhiyou, 11, 79-84 (2020).

[15]. Fisher, I. E., Garnsey, M. R., & Hughes, M. E.: Natural language processing in accounting, auditing and finance: A synthesis of the literature with a roadmap for future research. Intelli-gent Systems in Accounting, Finance and Management, 23(3), 157-214 (2016).

[16]. China Alliance of Social Value Investment (CASVI), China Asset Management Co. (China AMC): White Paper on ESG Development and Innovation in China 2021 (2021).

[17]. Nalini, R.: Optimal Portfolio construction using Sharpe’s Single Index Model-A study of se-lected stocks from BSE. International Journal of Advanced Research in Management and So-cial Sciences, 3(12), 72-93 (2014).

[18]. Klambauer, G., Unterthiner, T., Mayr, A., & Hochreiter, S.: Self-normalizing neural networks. Advances in neural information processing systems, 30 (2017).