IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2307.09631.html
   My bibliography  Save this paper

Deep Reinforcement Learning for ESG financial portfolio management

Author

Listed:
  • Eduardo C. Garrido-Merch'an
  • Sol Mora-Figueroa-Cruz-Guzm'an
  • Mar'ia Coronado-Vaca

Abstract

This paper investigates the application of Deep Reinforcement Learning (DRL) for Environment, Social, and Governance (ESG) financial portfolio management, with a specific focus on the potential benefits of ESG score-based market regulation. We leveraged an Advantage Actor-Critic (A2C) agent and conducted our experiments using environments encoded within the OpenAI Gym, adapted from the FinRL platform. The study includes a comparative analysis of DRL agent performance under standard Dow Jones Industrial Average (DJIA) market conditions and a scenario where returns are regulated in line with company ESG scores. In the ESG-regulated market, grants were proportionally allotted to portfolios based on their returns and ESG scores, while taxes were assigned to portfolios below the mean ESG score of the index. The results intriguingly reveal that the DRL agent within the ESG-regulated market outperforms the standard DJIA market setup. Furthermore, we considered the inclusion of ESG variables in the agent state space, and compared this with scenarios where such data were excluded. This comparison adds to the understanding of the role of ESG factors in portfolio management decision-making. We also analyze the behaviour of the DRL agent in IBEX 35 and NASDAQ-100 indexes. Both the A2C and Proximal Policy Optimization (PPO) algorithms were applied to these additional markets, providing a broader perspective on the generalization of our findings. This work contributes to the evolving field of ESG investing, suggesting that market regulation based on ESG scoring can potentially improve DRL-based portfolio management, with significant implications for sustainable investing strategies.

Suggested Citation

  • Eduardo C. Garrido-Merch'an & Sol Mora-Figueroa-Cruz-Guzm'an & Mar'ia Coronado-Vaca, 2023. "Deep Reinforcement Learning for ESG financial portfolio management," Papers 2307.09631, arXiv.org.
  • Handle: RePEc:arx:papers:2307.09631
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2307.09631
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mark Rubinstein, 2002. "Markowitz's “Portfolio Selection”: A Fifty‐Year Retrospective," Journal of Finance, American Finance Association, vol. 57(3), pages 1041-1045, June.
    2. Florian Berg & Julian F Kölbel & Roberto Rigobon, 2022. "Aggregate Confusion: The Divergence of ESG Ratings [Corporate social responsibility and firm risk: theory and empirical evidence]," Review of Finance, European Finance Association, vol. 26(6), pages 1315-1344.
    3. Lars Kaiser & Jan Welters, 2019. "Risk-mitigating effect of ESG on momentum portfolios," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 20(5), pages 542-555, October.
    4. Shuo Sun & Rundong Wang & Bo An, 2021. "Reinforcement Learning for Quantitative Trading," Papers 2109.13851, arXiv.org.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhang, Chunqiang & Hao, Dayu & Gao, Lu & Xia, Fan & Zhang, Linlang, 2024. "Do ESG ratings improve capital market trading activities?," International Review of Economics & Finance, Elsevier, vol. 93(PA), pages 195-210.
    2. Allan, Grant & Eromenko, Igor & McGregor, Peter & Swales, Kim, 2011. "The regional electricity generation mix in Scotland: A portfolio selection approach incorporating marine technologies," Energy Policy, Elsevier, vol. 39(1), pages 6-22, January.
    3. Liu, Guangqiang & Zeng, Qing & Lei, Juan, 2022. "Dynamic risks from climate policy uncertainty: A case study for the natural gas market," Resources Policy, Elsevier, vol. 79(C).
    4. Scholz, Robert, 2023. "Unternehmensmitbestimmung und die sozialökologische Transformation: Zusammenhang zwischen Mitbestimmungsindex und ESG-Kriterien in börsennotierten Unternehmen," Mitbestimmungsreport 79, Hans-Böckler-Stiftung, Düsseldorf.
    5. Ferriani, Fabrizio, 2023. "Issuing bonds during the Covid-19 pandemic: Was there an ESG premium?," International Review of Financial Analysis, Elsevier, vol. 88(C).
    6. Cauthorn, Thomas & Dumrose, Maurice & Eckert, Julia & Klein, Christian & Zwergel, Bernhard, 2023. "Rating changes revisited: New evidence on short-term ESG momentum," Finance Research Letters, Elsevier, vol. 54(C).
    7. Danisman, Gamze Ozturk & Tarazi, Amine, 2024. "ESG activity and bank lending during financial crises," Journal of Financial Stability, Elsevier, vol. 70(C).
    8. Liu, Xiangqiang & Yang, Qingqing & Wei, Kai & Dai, Peng-Fei, 2024. "ESG rating disagreement and idiosyncratic return volatility: Evidence from China," Research in International Business and Finance, Elsevier, vol. 70(PB).
    9. Dunbar, Kwamie & Treku, Daniel & Sarnie, Robert & Hoover, Jack, 2023. "What does ESG risk premia tell us about mutual fund sustainability levels: A difference-in-differences analysis," Finance Research Letters, Elsevier, vol. 57(C).
    10. Wang, Jianli & Wang, Shaolin & Dong, Minghua & Wang, Hongxia, 2024. "ESG rating disagreement and stock returns: Evidence from China," International Review of Financial Analysis, Elsevier, vol. 91(C).
    11. Sanctuary, Mark & Lavenius, Axel & Parlato, Giorgio & Plue, Jan & Crona, Beatrice, 2024. "A study of green European equity fund portfolio allocations," Working Paper Series in Economics and Institutions of Innovation 499, Royal Institute of Technology, CESIS - Centre of Excellence for Science and Innovation Studies.
    12. Vu, Thanh Nam & Junttila, Juha-Pekka & Lehkonen, Heikki, 2024. "ESG news and long-run stock returns," Finance Research Letters, Elsevier, vol. 60(C).
    13. Asimakopoulos, Panagiotis & Asimakopoulos, Stylianos & Li, Xinyu, 2023. "The role of environmental, social, and governance rating on corporate debt structure," Journal of Corporate Finance, Elsevier, vol. 83(C).
    14. DiMaria, charles-henri, 2024. "ESG principles: the limits to green benchmarking," MPRA Paper 120410, University Library of Munich, Germany, revised 2024.
    15. Yu, Haixu & Liang, Chuanyu & Liu, Zhaohua & Wang, He, 2023. "News-based ESG sentiment and stock price crash risk," International Review of Financial Analysis, Elsevier, vol. 88(C).
    16. Alessi, Lucia & Battiston, Stefano, 2022. "Two sides of the same coin: Green Taxonomy alignment versus transition risk in financial portfolios," International Review of Financial Analysis, Elsevier, vol. 84(C).
    17. Ge, Xiaowen & Xue, Minggao & Cao, Ruiyi, 2024. "Do Chinese carbon-intensive stocks overreact to climate transition risk? Evidence from the COP26 news," International Review of Financial Analysis, Elsevier, vol. 94(C).
    18. Marohn, Marcel & Auer, Benjamin R., 2024. "A note on Steuer and Utz’s (2023) multi-objective optimization approach for generating sustainability-efficient fronts," European Journal of Operational Research, Elsevier, vol. 316(2), pages 792-797.
    19. Sascha Kolaric, 2024. "The impact of climate litigation and activism on stock prices: the case of oil and gas majors," Review of Managerial Science, Springer, vol. 18(11), pages 3141-3172, November.
    20. Zou, Jin & Yan, Jingzhou & Deng, Guoying, 2023. "ESG rating confusion and bond spreads," Economic Modelling, Elsevier, vol. 129(C).

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:2307.09631. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.