Asymptotics of sums of lognormal random variables with Gaussian copula

Citations

Cited by:

1. Zdravko I. Botev & Robert Salomone & Daniel Mackinlay, 2019. "Fast and accurate computation of the distribution of sums of dependent log-normals," Annals of Operations Research, Springer, vol. 280(1), pages 19-46, September.
2. Søren Asmussen & José Blanchet & Sandeep Juneja & Leonardo Rojas-Nandayapa, 2011. "Efficient simulation of tail probabilities of sums of correlated lognormals," Annals of Operations Research, Springer, vol. 189(1), pages 5-23, September.
3. Denys Pommeret & Laurence Reboul, 2019. "Approximating the Probability Density Function of a Transformation of Random Variables," Methodology and Computing in Applied Probability, Springer, vol. 21(2), pages 633-645, June.
4. Serguei Foss & Andrew Richards, 2010. "On Sums of Conditionally Independent Subexponential Random Variables," Mathematics of Operations Research, INFORMS, vol. 35(1), pages 102-119, February.
5. Das, Bikramjit & Fasen-Hartmann, Vicky, 2024. "On heavy-tailed risks under Gaussian copula: The effects of marginal transformation," Journal of Multivariate Analysis, Elsevier, vol. 202(C).
6. Rodrigues, G.S. & Prangle, D. & Sisson, S.A., 2018. "Recalibration: A post-processing method for approximate Bayesian computation," Computational Statistics & Data Analysis, Elsevier, vol. 126(C), pages 53-66.
7. Asimit, Alexandru V. & Furman, Edward & Tang, Qihe & Vernic, Raluca, 2011. "Asymptotics for risk capital allocations based on Conditional Tail Expectation," Insurance: Mathematics and Economics, Elsevier, vol. 49(3), pages 310-324.
8. Jo, Wooseok & Lee, Seung Jun, 2024. "Human reliability evaluation method covering operator action timing for dynamic probabilistic safety assessment," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
9. Alouini Mohamed-Slim & Ben Rached Nadhir & Kammoun Abla & Tempone Raul, 2018. "On the efficient simulation of the left-tail of the sum of correlated log-normal variates," Monte Carlo Methods and Applications, De Gruyter, vol. 24(2), pages 101-115, June.
10. Ibragimov, Rustam & Prokhorov, Artem, 2016. "Heavy tails and copulas: Limits of diversification revisited," Economics Letters, Elsevier, vol. 149(C), pages 102-107.
11. Pirjol, Dan & Zhu, Lingjiong, 2016. "Discrete sums of geometric Brownian motions, annuities and Asian options," Insurance: Mathematics and Economics, Elsevier, vol. 70(C), pages 19-37.
12. Coqueret, Guillaume, 2014. "Second order risk aggregation with the Bernstein copula," Insurance: Mathematics and Economics, Elsevier, vol. 58(C), pages 150-158.
13. Furman, Edward & Hackmann, Daniel & Kuznetsov, Alexey, 2020. "On log-normal convolutions: An analytical–numerical method with applications to economic capital determination," Insurance: Mathematics and Economics, Elsevier, vol. 90(C), pages 120-134.
14. Jaap Geluk & Qihe Tang, 2009. "Asymptotic Tail Probabilities of Sums of Dependent Subexponential Random Variables," Journal of Theoretical Probability, Springer, vol. 22(4), pages 871-882, December.
15. Jochen Ranger & Christoph König & Benjamin W. Domingue & Jörg-Tobias Kuhn & Andreas Frey, 2024. "A Multidimensional Partially Compensatory Response Time Model on Basis of the Log-Normal Distribution," Journal of Educational and Behavioral Statistics, , vol. 49(3), pages 431-464, June.
16. Bikramjit Das & Vicky Fasen-Hartmann, 2023. "On heavy-tailed risks under Gaussian copula: the effects of marginal transformation," Papers 2304.05004, arXiv.org.
17. Boyle, Phelim & Jiang, Ruihong, 2023. "A note on portfolios of averages of lognormal variables," Insurance: Mathematics and Economics, Elsevier, vol. 112(C), pages 97-109.
18. Fulghieri, Paolo & Hackbarth, Dirk & Garcia, Diego, 2015. "Asymmetric information, security design, and the pecking (dis)order," CEPR Discussion Papers 10660, C.E.P.R. Discussion Papers.
19. Peter Tankov, 2014. "Tails of weakly dependent random vectors," Papers 1402.4683, arXiv.org, revised Jan 2016.
20. Archil Gulisashvili & Peter Tankov, 2014. "Implied volatility of basket options at extreme strikes," Papers 1406.0394, arXiv.org.
21. Thelwall, Mike, 2016. "The precision of the arithmetic mean, geometric mean and percentiles for citation data: An experimental simulation modelling approach," Journal of Informetrics, Elsevier, vol. 10(1), pages 110-123.
22. Paolo Fulghieri & Diego García & Dirk Hackbarth, 2020. "Asymmetric Information and the Pecking (Dis)Order," Review of Finance, European Finance Association, vol. 24(5), pages 961-996.
23. Yuan, Jun & Ng, Szu Hui & Sou, Weng Sut, 2016. "Uncertainty quantification of CO2 emission reduction for maritime shipping," Energy Policy, Elsevier, vol. 88(C), pages 113-130.
24. Xiaoou Li & Jingchen Liu & Gongjun Xu, 2016. "On the Tail Probabilities of Aggregated Lognormal Random Fields with Small Noise," Mathematics of Operations Research, INFORMS, vol. 41(1), pages 236-246, February.
25. Dan Pirjol & Lingjiong Zhu, 2016. "Discrete Sums of Geometric Brownian Motions, Annuities and Asian Options," Papers 1609.07558, arXiv.org.
26. Archil Gulisashvili & Peter Tankov, 2013. "Tail behavior of sums and differences of log-normal random variables," Papers 1309.3057, arXiv.org, revised Jan 2016.
27. Jiang, Tao & Gao, Qingwu & Wang, Yuebao, 2014. "Max-sum equivalence of conditionally dependent random variables," Statistics & Probability Letters, Elsevier, vol. 84(C), pages 60-66.
28. Søren Asmussen & Jens Ledet Jensen & Leonardo Rojas-Nandayapa, 2016. "Exponential Family Techniques for the Lognormal Left Tail," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 43(3), pages 774-787, September.