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Schlütter, S., Fianu, E., Gründl, H. Responsible investments in life insurers’ optimal portfolios under solvency constraints. Zeitschrift für die gesamte Versicherungswissenschaft, 112(1), 53-81. https://doi.org/10.3790/zverswiss.2023.03.Schluetter.etal
Schlütter, Sebastian; Fianu, Emmanuel Senyo and Gründl, Helmut "Responsible investments in life insurers’ optimal portfolios under solvency constraints" Zeitschrift für die gesamte Versicherungswissenschaft 112.1, 2023, 53-81. https://doi.org/10.3790/zverswiss.2023.03.Schluetter.etal
Schlütter, Sebastian/Fianu, Emmanuel Senyo/Gründl, Helmut (2023): Responsible investments in life insurers’ optimal portfolios under solvency constraints, in: Zeitschrift für die gesamte Versicherungswissenschaft, vol. 112, iss. 1, 53-81, [online] https://doi.org/10.3790/zverswiss.2023.03.Schluetter.etal

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Responsible investments in life insurers’ optimal portfolios under solvency constraints

Schlütter, Sebastian | Fianu, Emmanuel Senyo | Gründl, Helmut

Zeitschrift für die gesamte Versicherungswissenschaft, Vol. 112 (2023), Iss. 1 : pp. 53–81

Additional Information

Article Details

Author Details

Prof. Dr. Sebastian Schlütter, Professur für Quantitative Methoden, Fachbereich Wirtschaft, Hochschule Mainz, Lucy-Hillebrand-Str. 2, 55128 Mainz, Fellow am International Center for Insurance Regulation, Goethe-Universität Frankfurt am Main

Dr. Emmanuel Senyo Fianu, Fachbereich Wirtschaft, Hochschule Mainz, Lucy-Hillebrand-Str. 2, 55128 Mainz, Gastforscher am International Center for Insurance Regulation, Goethe-Universität Frankfurt am Main

Prof. Dr. Helmut Gründl, International Center for Insurance Regulation, Goethe-Universität Frankfurt am Main

References

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  46. Ballestero, E./Bravo, M./Pérez-Gladish, B./Arenas-Parra, M./Pla-Santamaria, D. (2012): ‘Socially responsible investment: A multicriteria approach to portfolio selection combining ethical and financial objectives’, European Journal of Operational Research 216(2), 487–494.  Google Scholar
  47. Bannier, C. E./Bofinger, Y./Rock, B. (2019): Doing safe by doing good: Esg investing and corporate social responsibility in the US and Europe, Technical report, CFS Working Paper Series.  Google Scholar
  48. Berdin, E./Gründl, H. (2015): ‘The effects of a low interest rate environment on life insurers’, The Geneva Papers on Risk and Insurance – Issues and Practice 40(3), 385–415.  Google Scholar
  49. Bilbao-Terol, A./Arenas-Parra, M./Cañal-Fernández, V. (2012): ‘Selection of socially responsible portfolios using goal programming and fuzzy technology’, Information Sciences 189, 110–125.  Google Scholar
  50. Bilbao-Terol, A./Arenas-Parra, M./Cañal-Fernández, V./Bilbao-Terol, C. (2013): ‘Selection of socially responsible portfolios using hedonic prices’, Journal of Business Ethics 115(3), 515–529.  Google Scholar
  51. Bohnert, A./Gatzert, N./Jorgensen, P. L. (2015): ‘On the management of life insurance company risk by strategic choice of product mix, investment strategy and surplus appropriation schemes’, Insurance: Mathematics and Economics 60, 83–97.  Google Scholar
  52. Braun, A./Schmeiser, H./Schreiber, F. (2017): ‘Portfolio optimization under Solvency II: Implicit constraints imposed by the market risk standard formula’, Journal of Risk and Insurance 84(1), 177–207.  Google Scholar
  53. Braun, A./Schmeiser, H./Schreiber, F. (2018): ‘Return on risk-adjusted capital under Solvency II: Implications for the asset management of insurance companies’, The Geneva Papers on Risk and Insurance – Issues and Practice 43(3), 456–472.  Google Scholar
  54. Busch, T./Friede, G. (2018): ‘The robustness of the corporate social and financial performance relation: A second-order meta-analysis’, Corporate Social Responsibility and Environmental Management 25(4), 583–608.  Google Scholar
  55. Cabello, J. M./Ruiz, F./Pérez-Gladish, B./Méndez-Rodríguez, P. (2014): ‘Synthetic indicators of mutual funds’ environmental responsibility: An application of the reference point method’, European Journal of Operational Research 236(1), 313–325.  Google Scholar
  56. Calvo, C./Ivorra, C./Liern, V. (2016): ‘Fuzzy portfolio selection with non-financial goals: exploring the efficient frontier’, Annals of Operations Research 245(1), 31–46.  Google Scholar
  57. Cerqueti, R./Ciciretti, R./Dalò, A./Nicolosi, M. (2021): ‘Esg investing: A chance to reduce systemic risk’, Journal of Financial Stability 54, 100887.  Google Scholar
  58. Chaiyapo, N./Phewchean, N. (2017), ‘An application of Ornstein-Uhlenbeck process to commodity pricing in thailand’, Advances in Difference Equations 2017(1), 1–10.  Google Scholar
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  60. Duffie, D./Singleton, K. J. (1999): ‘Modeling term structures of defaultable bonds’, The Review of Financial Studies 12(4), 687–720.  Google Scholar
  61. Eckert, J./Gatzert, N./Martin, M. (2016): ‘Valuation and risk assessment of participating life insurance in the presence of credit risk’, Insurance: Mathematics and Economics 71, 382–393.  Google Scholar
  62. Fischer, K./Schlütter, S. (2015): ‘Optimal investment strategies for insurance companies when capital requirements are imposed by a standard formula’, Geneva Risk and Insurance Review 40(1), 15–40.  Google Scholar
  63. Friede, G./Busch, T./Bassen, A. (2015): ‘Esg and financial performance: aggregated evidence from more than 2000 empirical studies’, Journal of Sustainable Finance & Investment 5(4), 210–233.  Google Scholar
  64. Gasser, S. M./Rammerstorfer, M./Weinmayer, K. (2017): ‘Markowitz revisited: Social portfolio engineering’, European Journal of Operational Research 258(3), 1181–1190.  Google Scholar
  65. Gatzert, N. (2008): ‘Asset management and surplus distribution strategies in life insurance: An examination with respect to risk pricing and risk measurement’, Insurance: Mathematics and Economics 42(2), 839–849.  Google Scholar
  66. Gatzert, N./Martin, M. (2012): ‘Quantifying credit and market risk under Solvency II: Standard approach versus internal model’, Insurance: Mathematics and Economics 51(3), 649–666.  Google Scholar
  67. Gourieroux, C./Laurent, J.-P./Scaillet, O. (2000): ‘Sensitivity analysis of values at risk’, Journal of Empirical Finance 7(3–4), 225–245.  Google Scholar
  68. Hart, O. D./Jaffee, D. M. (1974): ‘On the application of portfolio theory to depository financial intermediaries’, The Review of Economic Studies 41(1), 129–147.  Google Scholar
  69. Huang, H.-C./Lee, Y.-T. (2010): ‘Optimal asset allocation for a general portfolio of life insurance policies’, Insurance: Mathematics and Economics 46(2), 271–280.  Google Scholar
  70. Jakubik, P./Uguz, S. (2021): ‘Impact of green bond policies on insurers: evidence from the European equity market’, Journal of Economics and Finance 45(2), 381–393.  Google Scholar
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  74. Markowitz, H. M. (1952): ‘Portfolio selection’, Journal of Finance 7(1), 77–91.  Google Scholar
  75. Nanda, V./Wu, W./Zhou, X. A. (2019): ‘Investment commonality across insurance companies: Fire sale risk and corporate yield spreads’, Journal of Financial and Quantitative Analysis 54(6), 2543–2574.  Google Scholar
  76. Nofsinger, J./Varma, A. (2014): ‘Socially responsible funds and market crises’, Journal of Banking & Finance 48, 180–193.  Google Scholar
  77. Oksendal, B. (2003): ‘Stochastic differential equations, Fifth Edition’.  Google Scholar
  78. Pedersen, L. H./Fitzgibbons, S./Pomorski, L. (2021): ‘Responsible investing: The ESG-efficient frontier’, Journal of Financial Economics 142(2), 572–597.  Google Scholar
  79. Polbennikov, S./Desclée, A./Dynkin, L./Maitra, A. (2016), ‘Esg ratings and performance of corporate bonds’, The Journal of Fixed Income 26(1), 21–41.  Google Scholar
  80. Rockafellar, R. T./Uryasev, S. (2000): ‘Optimization of conditional value-at-risk’, Journal of Risk 2, 21–42.  Google Scholar
  81. Rockafellar, R. T./Uryasev, S. (2002): ‘Conditional value-at-risk for general loss distributions’, Journal of Banking & Finance 26(7), 1443–1471.  Google Scholar
  82. Smith, W. (2010): ‘On the simulation and estimation of the mean-reverting Ornstein-Uhlenbeck process’, Commodities Markets and Modelling.  Google Scholar
  83. Utz, S./Wimmer, M./Hirschberger, M./Steuer, R. E. (2014): ‘Tri-criterion inverse portfolio optimization with application to socially responsible mutual funds’, European Journal of Operational Research 234(2), 491–498.  Google Scholar
  84. van den Berg, T. (2011): ‘Calibrating the Ornstein-Uhlenbeck (Vasicek) model’, Web page http://www.sitmo.com/article/calibrating-the-ornstein-uhlenbeck-model/. View date October 24th, 2021.  Google Scholar
  85. Vo, N. N./He, X./Liu, S./Xu, G. (2019): ‘Deep learning for decision making and the optimization of socially responsible investments and portfolio’, Decision Support Systems 124, 113097.  Google Scholar
  86. von Wallis, M./Klein, C. (2015): ‘Ethical requirement and financial interest: a literature review on socially responsible investing’, Business Research 8(1), 61–98.  Google Scholar
  87. Weber, S. (2018): ‘Solvency II, or how to sweep the downside risk under the carpet’, Insurance: Mathematics and Economics 82, 191–200.  Google Scholar
  88. Zhu, S./Fukushima, M. (2009): ‘Worst-case conditional value-at-risk with application to robust portfolio management’, Operations Research 57(5), 1155–1168.  Google Scholar

Abstract

Socially responsible investing (SRI) continues to gain momentum in the financial market space for various reasons, starting with the looming effect of climate change and the drive toward a net-zero economy. Existing SRI approaches have included environmental, social, and governance (ESG) criteria as a further dimension to portfolio selection. But, these approaches focus on classical investors and do not account for specific aspects of insurance companies. In this paper, we consider the stock selection problem of life insurance companies. In addition to stock risk, our model set-up includes other important market risk categories of insurers, namely interest rate risk and credit risk. In line with common standards in insurance solvency regulation, such as Solvency II, we measure risk using the solvency ratio, i. e. the ratio of the insurer’s market-based equity capital to the Value-at-Risk of all modeled risk categories. As a consequence, we employ a modification of Markowitz’s Portfolio Selection Theory by choosing the “solvency ratio” as a downside risk measure to obtain a feasible set of optimal portfolios in a three-dimensional (risk, return, and ESG) capital allocation plane. We find that for a given solvency ratio, stock portfolios with a moderate ESG level can lead to a higher expected return than those with a low ESG level. A highly ambitious ESG level, however, reduces the expected return. Because of the specific nature of a life insurer’s business model, the impact of the ESG level on the expected return of life insurers can substantially differ from the corresponding impact for classical investors.