Nested Simulations: Theory and Application - Maximilian Klein
-35% koodilla BOOKS
Toimitus 12-18 arkipäivässä
30 päivän palautusoikeus
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. Fo ... Täydellinen kuvaus
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Kuvaus
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.
Lisätietoja
| Kirjoittaja | Maximilian Klein |
|---|---|
| Julkaisija | Springer Fachmedien Wiesbaden |
| Series | Mathematische Optimierung und Wirtschaftsmathematik | Mathematical Optimization and Economathematics |
| Julkaisuvuosi | 2024 |
| Kannen tyyppi | Pehmeäkantinen |
| EAN | 9783658438524 |