Diese Arbeit analysiert Monte-Carlo-basierte Value-at-Risk-Methoden (VaR-Methoden) hinsichtlich Genauigkeit und Rechenaufwand.

In diesen Untersuchungen analysiert Assekurata die Plausibilität der Beispielrechungen von Lebensversicherungen. Sie stellen dar, welche Ablaufleistung der Kunde zum Vertragsende erwarten kann. Die Versicherungsvermittler nutzen die Beispielrechnungen als Vertriebsunterstützung vor dem...

Here we develop methods for e±cient pricing multidimensional discrete-time American and Bermudan options by using regression based algorithms together with a new approach towards constructing upper bounds for the price of the option...

This paper focuses on the robust Effcient Method of Moments (EMM) estimation of a general parametric stationary process and proposes a broad framework for constructing robust EMM statistics in this context. This extends the application field of robust statistics to very general time series...

Two different probability measures are of importance when calculating the risk of a large portfolio: the risk-neutral measure for pricing, and the real measure to project true earnings. When using Monte Carlo, the natural method is to conduct two different simulations, one in each probability...

In this paper we develop a structural equation model with latent variables in an ordinal setting which allows us to test broker-dealer predictive ability of financial market movements. We use a multivariate logit model in a latent factor framework, develop a tractable estimator based on a...

This paper concerns the pricing of American options with stochastic stopping time constraints expressed in terms of the states of a Markov process. Following the ideas of Menaldi, Robin, and Sun (1996) we transform the constrained into an unconstrained optimal stopping problem. The...

We study a test statistic based on the integrated squared difference between a kernel estimator of the copula density and a kernel smoothed estimator of the parametric copula density. We show for fixed smoothing parameters that the test is consistent and that the asymptotic properties are driven...

We introduce an adaptive importance sampling method for the loss distribution of credit portfolios based on the Robbins-Monro stochastic approximation procedure. After presenting the subtle construction of the algorithm, we apply our adaptive scheme for calculating the risk figures of a typical...

We propose a class of new robust GMM tests for endogenous structural breaks. The tests are based on supremum and average statistics derived from robust GMM estimators with a bounded influence function. They imply a bounded linearized asymptotic bias of size and power under local model...