| 书目名称 | Nested Simulations: Theory and Application |
| 编辑 | Maximilian Klein |
| 视频video | |
| 丛书名称 | Mathematische Optimierung und Wirtschaftsmathematik | Mathematical Optimization and Economathematics |
| 图书封面 |  |
| 描述 | Maximilian Klein analyses nested Monte Carlo simulations for the approximation of conditional expected values. Thereby, the book deals with two general risk functional classes for conditional expected values, on the one hand the class of moment-based estimators (notable examples are the probability of a large loss or the lower partial moments) and on the other hand the class of quantile-based estimators. For both functional classes, the almost sure convergence of the respective estimator is proven and the underlying convergence speed is quantified. In particular, the class of quantile-based estimators has important practical consequences especially for life insurance companies since the Value-at-Risk falls into this class and thus covers the solvency capital requirement problem. Furthermore, a novel non parametric confidence interval method for quantiles is presented which takes the additional noise of the inner simulation into account.. |
| 出版日期 | Book 2024 |
| 关键词 | Almost Sure Convergence; Confidence Intervals; Nested Monte Carlo Simulation; Life Insurance; Solvency I |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-658-43853-1 |
| isbn_softcover | 978-3-658-43852-4 |
| isbn_ebook | 978-3-658-43853-1Series ISSN 2523-7926 Series E-ISSN 2523-7934 |
| issn_series | 2523-7926 |
| copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Fachmedien Wies |
发表于 2025-3-21 17:30:59
