Application of data clustering and machine learning in variable annuity valuation

Citations

Cited by:

1. Seyed Amir Hejazi & Kenneth R. Jackson, 2016. "A Neural Network Approach to Efficient Valuation of Large Portfolios of Variable Annuities," Papers 1606.07831, arXiv.org.
2. Guojun Gan & Emiliano A. Valdez, 2018. "Nested Stochastic Valuation of Large Variable Annuity Portfolios: Monte Carlo Simulation and Synthetic Datasets," Data, MDPI, vol. 3(3), pages 1-21, September.
3. Emilia Lorenzo & Gabriella Piscopo & Marilena Sibillo & Roberto Tizzano, 2021. "Reverse mortgages through artificial intelligence: new opportunities for the actuaries," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 23-35, June.
4. Ludovic Goudenège & Andrea Molent & Antonino Zanette, 2021. "Gaussian process regression for pricing variable annuities with stochastic volatility and interest rate," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 44(1), pages 57-72, June.
5. Gan, Guojun & Valdez, Emiliano A., 2017. "Modeling partial Greeks of variable annuities with dependence," Insurance: Mathematics and Economics, Elsevier, vol. 76(C), pages 118-134.
6. Wang, Gu & Zou, Bin, 2021. "Optimal fee structure of variable annuities," Insurance: Mathematics and Economics, Elsevier, vol. 101(PB), pages 587-601.
7. Seyed Amir Hejazi & Kenneth R. Jackson & Guojun Gan, 2017. "A Spatial Interpolation Framework for Efficient Valuation of Large Portfolios of Variable Annuities," Papers 1701.04134, arXiv.org.
8. Thorsten Moenig, 2021. "Efficient valuation of variable annuity portfolios with dynamic programming," Journal of Risk & Insurance, The American Risk and Insurance Association, vol. 88(4), pages 1023-1055, December.
9. Carbonneau, Alexandre, 2021. "Deep hedging of long-term financial derivatives," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 327-340.
10. Alexandre Carbonneau, 2020. "Deep Hedging of Long-Term Financial Derivatives," Papers 2007.15128, arXiv.org.
11. Riley Jones & Adriana Ocejo, 2019. "Assessing Guaranteed Minimum Income Benefits and Rationality of Exercising Reset Options in Variable," Papers 1911.06123, arXiv.org.
12. Lin, X. Sheldon & Yang, Shuai, 2020. "Fast and efficient nested simulation for large variable annuity portfolios: A surrogate modeling approach," Insurance: Mathematics and Economics, Elsevier, vol. 91(C), pages 85-103.
13. Massimo Costabile & Fabio Viviano, 2021. "Modeling the Future Value Distribution of a Life Insurance Portfolio," Risks, MDPI, vol. 9(10), pages 1-17, October.
14. Shuang Yin & Guojun Gan & Emiliano A. Valdez & Jeyaraj Vadiveloo, 2021. "Applications of Clustering with Mixed Type Data in Life Insurance," Risks, MDPI, vol. 9(3), pages 1-19, March.
15. Seyed Amir Hejazi & Kenneth R. Jackson, 2016. "Efficient Valuation of SCR via a Neural Network Approach," Papers 1610.01946, arXiv.org.
16. Huang, Yiming & Mamon, Rogemar & Xiong, Heng, 2022. "Valuing guaranteed minimum accumulation benefits by a change of numéraire approach," Insurance: Mathematics and Economics, Elsevier, vol. 103(C), pages 1-26.
17. Huang, H. & Milevsky, M.A. & Salisbury, T.S., 2014. "Optimal initiation of a GLWB in a variable annuity: No Arbitrage approach," Insurance: Mathematics and Economics, Elsevier, vol. 56(C), pages 102-111.
    • H. Huang & M. A. Milevsky & T. S. Salisbury, 2013. "Optimal initiation of a GLWB in a variable annuity: no arbitrage approach," Papers 1304.1821, arXiv.org.
18. Xu, Wei & Chen, Yuehuan & Coleman, Conrad & Coleman, Thomas F., 2018. "Moment matching machine learning methods for risk management of large variable annuity portfolios," Journal of Economic Dynamics and Control, Elsevier, vol. 87(C), pages 1-20.
19. Guojun Gan, 2018. "Valuation of Large Variable Annuity Portfolios Using Linear Models with Interactions," Risks, MDPI, vol. 6(3), pages 1-19, July.
20. Gweon, Hyukjun & Li, Shu, 2021. "Batch mode active learning framework and its application on valuing large variable annuity portfolios," Insurance: Mathematics and Economics, Elsevier, vol. 99(C), pages 105-115.
21. Ludovic Gouden`ege & Andrea Molent & Antonino Zanette, 2019. "Gaussian Process Regression for Pricing Variable Annuities with Stochastic Volatility and Interest Rate," Papers 1903.00369, arXiv.org, revised Jul 2019.
22. Li, Yuying & Forsyth, Peter A., 2019. "A data-driven neural network approach to optimal asset allocation for target based defined contribution pension plans," Insurance: Mathematics and Economics, Elsevier, vol. 86(C), pages 189-204.
23. Gan Guojun & Valdez Emiliano A., 2017. "Valuation of large variable annuity portfolios: Monte Carlo simulation and synthetic datasets," Dependence Modeling, De Gruyter, vol. 5(1), pages 354-374, December.
24. Hejazi, Seyed Amir & Jackson, Kenneth R., 2016. "A neural network approach to efficient valuation of large portfolios of variable annuities," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 169-181.
25. Gan, Guojun & Lin, X. Sheldon, 2015. "Valuation of large variable annuity portfolios under nested simulation: A functional data approach," Insurance: Mathematics and Economics, Elsevier, vol. 62(C), pages 138-150.
26. Daniel Doyle & Chris Groendyke, 2018. "Using Neural Networks to Price and Hedge Variable Annuity Guarantees," Risks, MDPI, vol. 7(1), pages 1-19, December.
27. Wing Fung Chong & Haoen Cui & Yuxuan Li, 2021. "Pseudo-Model-Free Hedging for Variable Annuities via Deep Reinforcement Learning," Papers 2107.03340, arXiv.org, revised Oct 2022.
28. Emer Owens & Barry Sheehan & Martin Mullins & Martin Cunneen & Juliane Ressel & German Castignani, 2022. "Explainable Artificial Intelligence (XAI) in Insurance," Risks, MDPI, vol. 10(12), pages 1-50, December.
29. Runhuan Feng & Peng Li, 2021. "Sample Recycling Method -- A New Approach to Efficient Nested Monte Carlo Simulations," Papers 2106.06028, arXiv.org.