Connections between ESG and systemic risk based on dynamic stock return connectedness in the US

Authors

DOI:

https://doi.org/10.14267/VEZTUD.2024.01.02

Keywords:

ESG, systemic risk, risk management, connectednes

Abstract

In this study, the number and direction of dynamic return connections have been analysed within and between portfolios with different ESG (Environmental, Social, Governance) scores to determine their exposure to systemic risk. The number of significant pairwise Granger causality connections were counted between 2012 and 2019 on the portfolios of NASDAQ and NYSE using one-year, weekly rolling windows. According to the results of the current empirical research, the return of high ESG portfolios determines the return of low ESG portfolios. Low ESG performers are also more interconnected than companies with high ESG scores and thus more exposed to systemic risk; this low-ESG interconnectedness accelerates further as market volatility increases. Overall, investors can reduce exposure to systemic risk by applying a responsible mindset to their investment decisions. Application of the methods and findings of this study could be integrated into the regulatory risk management and portfolio diversification practices of individual or institutional asset managers.

Downloads

Download data is not yet available.

Author Biography

Martin Márkus, Corvinus University of Budapest

PhD student

References

Abdennadher, E., & Hellara, S. (2018). Causality and contagion in emerging stock markets. Borsa Istanbul Review, 18(4), 300-311. https://doi.org/10.1016/j.bir.2018.07.001

Acharya, V.V., Pedersen, L.H., Philippon, T., & Richardson, M. (2017). Measuring systemic risk. The Review of Financial Studies, 30(1), 2-47. https://doi.org/10.1093/rfs/hhw088

Akhtaruzzaman, M., Boubaker, S., & Umar, Z. (2021). COVID–19 media coverage and ESG leader indices. Finance Research Letters, 45(March), 102170. https://doi.org/10.1016/j.frl.2021.102170

Balboa, M., López-Espinosa, G., & Rubia, A. (2015). Granger causality and systemic risk. Finance Research Letters, 15, 49-58. https://doi.org/10.1016/j.frl.2015.08.003

Barber, B.M., & Lyon, J.D. (1997). Firm size, book‐to‐market ratio, and security returns: A holdout sample of financial firms. The Journal of Finance, 52(2), 875-883. https://doi.org/10.1111/j.1540-6261.1997.tb04826.x

Benoit, S., Colletaz, G., Hurlin, C., & Pérignon, C. (2013). A theoretical and empirical comparison of systemic risk measures. HEC Paris Research Paper No. FIN2014-1030. http://dx.doi.org/10.2139/ssrn.1973950

Bianconi, M., Hua, X., & Tan, C.M. (2015). Determinants of systemic risk and information dissemination. International Review of Economics & Finance, 38(July), 352-368. https://doi.org/10.1016/j.iref.2015.03.010

Billio, M., Getmansky, M., Lo, A.W., & Pelizzon, L. (2012). Econometric measures of connectedness and systemic risk in the finance and insurance sectors. Journal of Financial Economics, 104(3), 535-559. https://doi.org/10.1016/j.jfineco.2011.12.010

Bisias, D., Flood, M., Lo, A.W., & Valavanis, S. (2012). A survey of systemic risk analytics. Annual Review of Financial Economics, 4(1), 255-296. https://doi.org/10.1146/annurev-financial-110311-101754

Bissoondoyal-Bheenick, E., Do, H., Hu, X., & Zhong, A. (2020). Learning from SARS: Return and Volatility Connectedness in COVID-19. Finance Research Letters, 41(July), 101796. https://doi.org/10.1016/j.frl.2020.101796

Broadstock, D.C., Chan, K., Luis, T.W.C., & Xiaowei W. (2020). The role of ESG performance during times of financial crisis: Evidence from COVID-19 in China. Finance Research Letters, 38(January), 101716. https://doi.org/10.1016/j.frl.2020.101716

Chen, Y., & Lin, B. (2022). Quantifying the extreme spillovers on worldwide ESG leaders’ equity. International Review of Financial Analysis, 84(Nov), 102425. https://doi.org/10.1016/j.irfa.2022.102425

Crespi, F., & Migliavacca, M. (2020). The determinants of ESG rating in the financial industry: the same old story or a different tale? Sustainability, 12(16), 6398. https://doi.org/10.3390/su12166398

Csillag B., & Neszveda G. (2020). A gazdasági várakozások hatása a tőzsdei momentumstratégiára. Közgazdasági Szemle, 67(11), 1093-1111. http://dx.doi.org/10.18414/KSZ.2020.11.1093

De Nicolo, G., & Kwast, M.L. (2002). Systemic risk and financial consolidation: Are they related? Journal of Banking & Finance, 26(5), 861-880. https://doi.org/10.1016/S0378-4266(02)00211-X

Demers, E., Jurian H., Philip J., & Baruch L. (2021). ESG Didn’t Immunize Stocks During the COVID-19 Crisis, But Investments in Intangible Assets Did. Journal of Business Finance & Accounting, 48(3-4), 433-462. https://doi.org/10.1111/jbfa.12523

Diebold, F.X., & Yilmaz, K (2012). Better to Give to Receive: Forcast Based Measurement of Volatility Spillovers. International Journal of Forecasting, 28(1), 57-66. https://doi.org/10.1016/j.ijforecast.2011.02.006

EBA (2019). EBA action plan on sustainable finance. https://www.eba.europa.eu/sites/default/documents/files/document_library/EBA%20Action%20plan%20on%20sustainable%20finance.pdf

Fama, E.F., & French, K.R. (1992). The cross‐section of expected stock returns. The Journal of Finance, 47(2), 427-465. https://doi.org/10.1111/j.1540-6261.1992.tb04398.x

Folger-Laronde, Z., Pashang, S., Feor, L., & ElAlfy, A. (2020). ESG ratings and financial performance of exchange-traded funds during the COVID-19 pandemic. Journal of Sustainable Finance & Investment, 12(2), 490-496. https://doi.org/10.1080/20430795.2020.1782814

Granger, C.W.J. (1969). Investigating Causal Relations by Econometric Models and Cross-spectral Methods. Econometrica, 37(3), 424-438. https://doi.org/10.2307/1912791

Hoepner, A. G. F., Oikonomou, I., Sautner, Z., Starks, L.T., & Zhou, X. (2019). ESG Shareholder Engagement and Downside Risk. Finance Working Paper, 671/2020. http://dx.doi.org/10.2139/ssrn.2874252

Hoje, J., & Haejung, N. (2012). Does CSR Reduce Firm Risk? Evidence from Controversial Industry Sectors. Journal of Business Ethics, 110(4), 441-456. http://dx.doi.org/10.1007/s10551-012-1492-2

Hong, Y., Liu, Y., & Wang, S. (2009). Granger causality in risk and detection of extreme risk spillover between financial markets. Journal of Econometrics, 150(2), 271-287. https://doi.org/10.1016/j.jeconom.2008.12.013

Hyunjoo, K. (2010). Dynamic causal linkages between the US stock market and the stock market of Eastern Asian economies. Cesis Electronic Working Paper Series. Paper No. 236. https://swopec.hhs.se/cesisp/abs/cesisp0236.htm

Le, T., Martin, F., & Nguyen, D. (2018). Dynamic connectedness of global currencies: A conditional Granger-causality approach. HAL. https://hal.science/hal01806733

Lindner, B., Auret, L., Bauer, M., & Groenewald, J.W. (2019). Comparative analysis of Granger causality and transfer entropy to present a decision flow for the application of oscillation diagnosis. Journal of Process Control, 79, 72-84. https://doi.org/10.1016/j.jprocont.2019.04.005

Magyar Nemzeti Bank (2022). A Magyar Nemzeti Bank 10/2022. (VIII.2.) számú ajánlása. https://www.mnb.hu/letoltes/10-2022-zold-ajanlas.pdf

Mérő B., Nagy O., & Neszveda G. (2019). Új faktorok tesztelése az empirikus eszközárazásban. SZIGMA Matematikai-Közgazdasági Folyóirat, 50(4), 263–281. https://journals.lib.pte.hu/index.php/szigma/article/view/3197/3001

Merton, R.C. (2014). Measuring the Connectedness of the Financial System: Implications for Risk Management. Asian Development Review, 31(1), 186–210. http://dx.doi.org/10.1162/ADEV_A_00026

MSCI (2022). ESG Investing. https://www.msci.com/our-solutions/esg-investing

Neszveda G. (2018). A kiszámíthatatlanság fokozatainak szerepe a közgazdaságtanban. Köz-gazdaság – Review of Economic Theory and Policy, 13(4), 103-111. http://dx.doi.org/10.14267/RETP2018.04.18

Neszveda G., & Vágó Á. (2021). A likviditásnyújtás kereskedési stratégiájának hozamvizsgálata a magyar részvénypiacon. Közgazdasági Szemle, 68(7-8), 794-814. http://dx.doi.org/10.18414/Ksz.2021.7-8.794

Peng, Y., Weidong, C., Wei, P., & Guanyi, Y. (2019). Spillover effect and Granger causality investigation between China’s stock market and international oil market: A dynamic multiscale approach. Journal of Computational and Applied Mathematics, 367(March), 112460. https://doi.org/10.1016/j.cam.2019.112460

Perneger, T.V. (1998). What’s wrong with Bonferroni adjustments. BMJ, 316(7139), 1236-1238. https://doi.org/10.1136/bmj.316.7139.1236

Policy Uncertainty (2022). Economic Policy Uncertainty. https://www.policyuncertainty.com/methodology.html

Refinitiv (2022). Environmental, Social and Governance Scores. https://www.refinitiv.com/content/dam/marketing/en_us/documents/methodology/refinitiv-esg-scores-methodology.pdf

Remmer, S., Hinze, A.K., & Hardeck, I. (2016). Impact of ESG factors on firm risk in Europe. Journal of Business Economics, 86(April), 867-904. https://doi.org/10.1007/s11573-016-0819-3

Said, S.E., & Dickey, D.A. (1984). Testing for unit roots in autoregressive-moving average models of unknown order. Biometrika, 71(3), 599-607. https://doi.org/10.1093/biomet/71.3.599

Shaik, M., & Rehman, M.Z. (2022). The Dynamic Volatility Connectedness of Major Environmental, Social, and Governance (ESG) Stock Indices: Evidence Based on DCC-GARCH Model. Asia-Pacific Financial Markets, 30, 231-246. https://doi.org/10.1007/s10690-022-09393-5

Shiller, R.J. (2015). Irrational exuberance. Princeton University Press. https://doi.org/10.1515/9781400865536

Shrivastava, P., & Zsolnai, L. (2020). Business and Society in the Anthropocene. In Wasieleski, D.M., & Weber, J. (Eds.), Sustainability (Business and Society 360, Vol. 4) (pp. 3-15). Emerald Publishing Limited. https://doi.org/10.1108/S2514-175920200000004002

Singh, A. (2022). COVID‐19 and ESG preferences: Corporate bonds versus equities. International Review of Finance, 22(2), 298-307. https://doi.org/10.1111/irfi.12351

Singh, A., Patel, R., & Singh, H. (2022). Recalibration of priorities: Investor preference and Russia-Ukraine conflict. Finance Research Letters, 50, 103294. https://doi.org/10.1016/j.frl.2022.103294

Tetlock, P.C. (2007). Giving content to investor sentiment: The role of media in the stock market. The Journal of Finance, 62(3), 1139-1168. https://doi.org/10.1111/j.1540-6261.2007.01232.x

Umar, Z., Kenourgios, D., & Papathanasiou, S. (2020). The static and dynamic connectedness of environmental, social, and governance investments: International evidence. Economic Modelling, 93(December), 112-124. https://doi.org/10.1016/j.econmod.2020.08.007

US SIF. (2021). US SIF: The Forum for Sustainable and Responsible Investment. Report on US Sustainable and Impact Investing Trends 2020. https://www.ussif.org/files/US%20SIF%20Trends%20Report%202020%20Executive%20Summary.pdf

US SIF. (2019). US SIF: The Forum for Sustainable and Responsible Investment. Report on US Sustainable and Impact Investing Trends 2018. https://www.ussif.org/files/US%20SIF%20Trends%20Report%202020%20Executive%20Summary.pdf

US SIF. (2021). US SIF Foundation. 2020 Report on US Sustainable and Impact Investing Trends. https://www.ussif.org/files/Trends/2020_Trends_Highlights_OnePager.pdf

Downloads

Published

2024-01-15

How to Cite

Márkus, M. (2024). Connections between ESG and systemic risk based on dynamic stock return connectedness in the US. Vezetéstudomány Budapest Management Review, 55(1), 16–26. https://doi.org/10.14267/VEZTUD.2024.01.02

Issue

Section

Studies and Articles