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#### Erscheinungsjahr

- 2009 (2) (entfernen)

#### Dokumenttyp

- Dissertation (2) (entfernen)

#### Schlagworte

- Extrapolation (2) (entfernen)

#### Fachbereich / Organisatorische Einheit

This thesis deals with the application of binomial option pricing in a single-asset Black-Scholes market and its extension to multi-dimensional situations. Although the binomial approach is, in principle, an efficient method for lower dimensional valuation problems, there are at least two main problems regarding its application: Firstly, traded options often exhibit discontinuities, so that the Berry- Esséen inequality is in general tight; i.e. conventional tree methods converge no faster than with order 1/sqrt(N). Furthermore, they suffer from an irregular convergence behaviour that impedes the possibility to achieve a higher order of convergence via extrapolation methods. Secondly, in multi-asset markets conventional tree construction methods cannot ensure well-defined transition probabilities for arbitrary correlation structures between the assets. As a major aim of this thesis, we present two approaches to get binomial trees into shape in order to overcome the main problems in applications; the optimal drift model for the valuation of single-asset options and the decoupling approach to multi-dimensional option pricing. The new valuation methods are embedded into a self-contained survey of binomial option pricing, which focuses on the convergence behaviour of binomial trees. The optimal drift model is a new one-dimensional binomial scheme that can lead to convergence of order o(1/N) by exploiting the specific structure of the valuation problem under consideration. As a consequence, it has the potential to outperform benchmark algorithms. The decoupling approach is presented as a universal construction method for multi-dimensional trees. The corresponding trees are well-defined for an arbitrary correlation structure of the underlying assets. In addition, they yield a more regular convergence behaviour. In fact, the sawtooth effect can even vanish completely, so that extrapolation can be applied.

In engineering and science, a multitude of problems exhibit an inherently geometric nature. The computational assessment of such problems requires an adequate representation by means of data structures and processing algorithms. One of the most widely adopted and recognized spatial data structures is the Delaunay triangulation which has its canonical dual in the Voronoi diagram. While the Voronoi diagram provides a simple and elegant framework to model spatial proximity, the core of which is the concept of natural neighbors, the Delaunay triangulation provides robust and efficient access to it. This combination explains the immense popularity of Voronoi- and Delaunay-based methods in all areas of science and engineering. This thesis addresses aspects from a variety of applications that share their affinity to the Voronoi diagram and the natural neighbor concept. First, an idea for the generalization of B-spline surfaces to unstructured knot sets over Voronoi diagrams is investigated. Then, a previously proposed method for \(C^2\) smooth natural neighbor interpolation is backed with concrete guidelines for its implementation. Smooth natural neighbor interpolation is also one of many applications requiring derivatives of the input data. The generation of derivative information in scattered data with the help of natural neighbors is described in detail. In a different setting, the computation of a discrete harmonic function in a point cloud is considered, and an observation is presented that relates natural neighbor coordinates to a continuous dependency between discrete harmonic functions and the coordinates of the point cloud. Attention is then turned to integrating the flexibility and meritable properties of natural neighbor interpolation into a framework that allows the algorithmically transparent and smooth extrapolation of any known natural neighbor interpolant. Finally, essential properties are proved for a recently introduced novel finite element tessellation technique in which a Delaunay triangulation is transformed into a unique polygonal tessellation.