A robo-advisory framework for Islamic and Environmental, Social and Governance (ESG) compliance – A benchmark study on the S&P 500 stock index
Total Views: 480
DOI:
https://doi.org/10.33102/jmifr.v19i1.408Keywords:
Artificial intelligence, ESG compliance, Shariah compliance, S&P 500Abstract
The last decade has brought a revolution in the financial sector, enabling more individuals and institutions to access the stock market. Islamic finance has similarly gained considerable interest from the growing Muslim population that is looking for Shariah-compliant investment options. Furthermore, a growing number of investors are looking for investment options that are environmentally sustainable and adhere to ethical values. While there are various Shariah advisory services, these services differ widely in their assessments of whether a company is Shariah-compliant. Given the cost of these services, it is typically only available for large institutional investors. The objective of this article is to address the challenges of providing individualized Shariah-compliant investment services automatically while providing a comparison with Environmental, Social and Governance (ESG) compliance to assist both investors who are seeking Shariah and ESG compliant investments. Hence, the study presents a new unsupervised learning framework for the determination of Shariah compliance and evaluates it with ESG compliance. The framework first filters the companies based on whether they have any exclusionary activities and then performs a clustering approach in order to classify them into compliant and non-compliant stocks. The framework was evaluated on the S&P 500 stock index and delivered acceptable and reasonable classifications. This Robo-Shariah advisor framework allows automatized real-time Shariah compliance evaluation based on a data-driven approach. The practical implication of this new framework is the enablement of objective, data-driven Shariah-compliant investment recommendations that can be easily integrated with Shariah expert information. The social implication is the empowerment of retail investors in being able to easily set up their own Shariah-compliant portfolio.
Downloads
References
Abu Seman, J., Jamil, N. N., & Mohd Hashim, A. J. (2021). Development of integrated Islamic finance-based index of financial inclusion using zakat and cash waqf: A preliminary study in Malaysia . The Journal of Muamalat and Islamic Finance Research, 18(2), 73-95. https://doi.org/10.33102/jmifr.v18i2.370
Ahmad, N., Hashim, N. H., & Abd Rahim, S. (2020). Is sukuk market efficient? Evidence from the Malaysian sukuk market. The Journal of Muamalat and Islamic Finance Research, 17(2), 32-43. https://doi.org/10.33102/jmifr.v17i2.292
Alam, M. M., Akbar, C. S., Shahriar, S. M., & Elahi, M. M. (2017). The Islamic Shariah principles for investment in stock market. Qualitative Research in Financial Markets, 9(2), 132-146. https://doi.org/10.1108/QRFM-09-2016-0029
Amel-Zadeh, A., & Serafeim, G. (2018). Why and how investors use ESG information: Evidence from a global survey. Financial Analysts Journal, 74(3), 87-103.
Askari, H., Iqbal, Z., Krichene, N., & Mirakhor, A. (2012). Risk sharing in finance: The Islamic finance alternative. John Wiley.
Broadstock, D. C., Chan, K., Cheng, L. T., & Wang, X. (2021). The role of ESG performance during times of financial crisis: Evidence from COVID-19 in China. Finance research letters, 101716.
Dye, J., McKinnon, M., & Van der Byl, C. (2021). Green gaps: Firm ESG disclosure and Financial institutions’ reporting requirements. Journal of Sustainability Research. https://doi.org/10.20900/jsr20210006
El-Komi, M., & Croson, R. (2013). Experiments in Islamic microfinance. Journal of Economic Behavior & Organization, 95, 252-269. https://doi.org/10.1016/j.jebo.2012.08.009
Emerson, S., Kennedy, R., O'Shea, L., & O'Brien, J. (2019). Trends and applications of machine learning in quantitative finance. 8th international conference on economics and finance research (ICEFR 2019).
Harikumar, S., & Surya, P. V. (2015). K-medoid clustering for heterogeneous datasets. Procedia Computer Science, 70, 226-237. https://doi.org/10.1016/j.procs.2015.10.077
Hassan, H. (2017). Crowdfunding from an Islamic finance perspective. Kuala Lumpur: ISRA - Thomson Reuters Islamic Commercial Law Report 2017.
Kotsantonis, S., Pinney, C., & Serafeim, G. (2016). ESG integration in investment management: Myths and realities. Journal of Applied Corporate Finance, 28(2), 10-16.
Lettau, M., & Madhavan, A. (2018). Exchange-traded funds 101 for economists. Journal of Economic Perspectives, 32(1), 135-154. DOI: 10.1257/jep.32.1.135
Likas, A., Vlassis, N., & Verbeek, J. J. (2003). The global k-means clustering algorithm. Pattern Recognition, 36(2), 451-461. https://doi.org/10.1016/S0031-3203(02)00060-2
Mawdudi, S. (2011). First principles of Islamic economics. Leicestershire: The Islamic Foundation.
Mohamed, H., & Ali, H. (2018). Blockchain, Fintech, and Islamic finance: Building the future in the new Islamic digital economy. Berlin: Walter de Gruyter Gmbh & Co KG.
Moisseron, J. -Y., Moschetto, B. -L., & Teulon, F. (2015). Islamic finance: A review of the literature. International Business & Economics Research Journal , 14(5), 745-762. https://doi.org/10.19030/iber.v14i5.9375
O'Leary, L., & Hauman, M. (2020). Regulatory implications of ESG investment. Journal of Financial Transformation, 163-171.
S&P Dow Jones Indices. (2021, December 30). S&P 500 Shariah. Retrieved from https://www.spglobal.com/spdji/en/indices/equity/sp-500-shariah-index/#overview
Schoon, N. (2008). Islamic finance–an overview. European Business Organization Law Review , 621-635.
SESRIC. (2021). OIC Economic Outlook 2021. Ankara, Turkey: Organization of Islamic Cooperation.
Published
How to Cite
Issue
Section
Copyright (c) 2022 Klemens Katterbauer, Philippe Moschetta
This work is licensed under a Creative Commons Attribution 4.0 International License.