Can Regulation Affect the Solvency of Insurers? New Evidence from European Insurers
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DOI: 10.1007/s11294-023-09867-w
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- James Ming Chen, 2021. "An Introduction to Machine Learning for Panel Data," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 27(1), pages 1-16, February.
- Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020. "Empirical Asset Pricing via Machine Learning," Review of Finance, European Finance Association, vol. 33(5), pages 2223-2273.
- repec:eme:jrfpps:v:14:y:2013:i:2:p:303-314 is not listed on IDEAS
- Danielsson, Jon & James, Kevin R. & Valenzuela, Marcela & Zer, Ilknur, 2016.
"Model risk of risk models,"
Journal of Financial Stability, Elsevier, vol. 23(C), pages 79-91.
- Danielsson, Jon & James, Kevin R. & Valenzuela, Marcela & Zer, Ilknur, 2014. "Model risk of risk models," LSE Research Online Documents on Economics 59296, London School of Economics and Political Science, LSE Library.
- Danielsson, Jon & James, Kevin R. & Valenzuela, Marcela & Zer, Ilknur, 2016. "Model risk of risk models," LSE Research Online Documents on Economics 66365, London School of Economics and Political Science, LSE Library.
- Jón Daníelsson & Kevin James & Marcela Valenzuela & Ilknur Zer, 2014. "Model Risk of Risk Models," Finance and Economics Discussion Series 2014-34, Board of Governors of the Federal Reserve System (U.S.).
- Martin Leo & Suneel Sharma & K. Maddulety, 2019. "Machine Learning in Banking Risk Management: A Literature Review," Risks, MDPI, vol. 7(1), pages 1-22, March.
- Shihao Gu & Bryan Kelly & Dacheng Xiu, 2020.
"Empirical Asset Pricing via Machine Learning,"
The Review of Financial Studies, Society for Financial Studies, vol. 33(5), pages 2223-2273.
- Shihao Gu & Bryan Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," NBER Working Papers 25398, National Bureau of Economic Research, Inc.
- Shihao Gu & Bryan T. Kelly & Dacheng Xiu, 2018. "Empirical Asset Pricing via Machine Learning," Swiss Finance Institute Research Paper Series 18-71, Swiss Finance Institute.
- Mathias Bärtl & Simone Krummaker, 2020. "Prediction of Claims in Export Credit Finance: A Comparison of Four Machine Learning Techniques," Risks, MDPI, vol. 8(1), pages 1-27, March.
- Sendhil Mullainathan & Jann Spiess, 2017. "Machine Learning: An Applied Econometric Approach," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 87-106, Spring.
- T. Joji Rao & Krishan K. Pandey, 2013. "A study on factors influencing claims in general insurance business in India," Journal of Risk Finance, Emerald Group Publishing Limited, vol. 14(3), pages 303-314, May.
- T. Joji Rao & Krishan K. Pandey, 2013. "A study on factors influencing claims in general insurance business in India," Journal of Risk Finance, Emerald Group Publishing, vol. 14(3), pages 303-314, May.
- Loisel, Stéphane & Piette, Pierrick & Tsai, Cheng-Hsien Jason, 2021. "Applying Economic Measures To Lapse Risk Management With Machine Learning Approaches," ASTIN Bulletin, Cambridge University Press, vol. 51(3), pages 839-871, September.
- Kexing Ding & Baruch Lev & Xuan Peng & Ting Sun & Miklos A. Vasarhelyi, 2020. "Machine learning improves accounting estimates: evidence from insurance payments," Review of Accounting Studies, Springer, vol. 25(3), pages 1098-1134, September.
- Filippo Curti & Ibrahim Ergen & Minh Le & Marco Migueis & Rob T. Stewart, 2016. "Benchmarking Operational Risk Models," Finance and Economics Discussion Series 2016-070, Board of Governors of the Federal Reserve System (U.S.).
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Keywords
Insurance companies; Solvency; Machine learning; LASSO regression;All these keywords.
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