Catálogo de publicaciones - libros

We consider Markov-modulated risk reserves which can be invested into a stock index following a geometric Brownian motion. Within a special class of investment policies we identify one which maximizes the adjustment coefficient. A comparison to the compound Poisson case is also given.

This paper considers the optimal selection of portfolios for utility maximizing investors under a shortfall risk constraint for a financial market model with partial information on the drift parameter. It is known that without risk constraint the distribution of the optimal terminal wealth often is quite skew. In spite of its maximum expected utility there are high probabilities for values of the terminal wealth falling short a prescribed benchmark. This is an undesirable and unacceptable property e.g. from the viewpoint of a pension fund manager. While imposing a strict restriction to portfolio values above a benchmark leads to considerable decrease in the portfolio’s expected utility, it seems to be reasonable to allow shortfall and to restrict only some shortfall risk measure.

This is an expository paper to promote the potential of OR (Operations Research) for simulation. Three applications will therefore be presented which include call centers, check-in at airports, and performance bounds for production lines. The results indicate that (classical and new) OR results might still be most fruitful if not necessary for practical simulation and its optimization.

A multistage stochastic programming problem can be introduced as a finite system of parametric one-stage optimization problems with an inner type of dependence and mathematical (mostly conditional) expectation in objective functions of the individual problems (for more details see e.g. [1], [3], [8]). The constraints sets can depend on the “underlying” probability measure.

This paper describes the features of a multistage ALM recourse model in light of the recent pension reform in the Netherlands. The main results are explicit modeling of indexation decisions and modeling of new regulatory rules.

Since the 1960s qualitative problem structuring methods have evolved mainly in the UK from traditional operational research, which are called „soft OR“. These methods focus on generating understanding of systems as a whole, on improving systems, and on personal learning. System dynamics has similar goals; therefore, it might be useful to combine it with soft OR. Some examples of combinations exist; however, these are mainly anecdotal. Thus, systematic research promises new insights and knowledge about the useful combination of soft OR and system dynamics in practice and theory. This has often been asked for but has not yet been established. In this paper a characterization of system dynamics is presented that can be used to find potential combinations of system dynamics and soft OR. More precisely, a framework designed by [11] for mapping methods is described. This framework characterizes methods along two dimensions: four steps of intervention processes and three domains, in which problem situations manifest: social, personal, and material world. System dynamics is mapped and thus characterized by this framework. On the one hand, the mapping highlights the strengths of system dynamics; on the other hand, it shows possibilities for useful combinations with soft OR. With this study, further steps to a systematic research of combinations between system dynamics and soft OR are undertaken. Based on the method characterization of system dynamics and soft OR, proposals for concrete combinations can be derived and contextual factors for successful combinations can be investigated.