Thesis (Ph. D.)--University of Washington, 2005. / Vita. Includes bibliographical references (p. 171).

Thesis (Licenciado en Contaduría)--Universidad Nacional Autónoma de México, 1983. / At head of title: Universidad Nacional Autonoma de Mexico. Facultad de Contaduria y Administracion. Includes bibliographical references (leaves [235]-238).

Thesis (D.A.)--Illinois State University, 2002. / Title from title page screen, viewed November 29, 2005. Dissertation Committee: Thomas Shilgalis (chair), Kenneth Berk, Patricia Klass, Beverly Rich, Charles Vanden Eynden. Includes bibliographical references (leaves 60-61) and abstract. Also available in print.

Thesis (Ph. D.)--Dept. of Economics. University of Missouri--Kansas City, 2005. / "A dissertation in economics and social science consortium." Advisor: James I. Sturgeon. Typescript. Vita. Title from "catalog record" of the print edition Description based on contents viewed June 26, 2006. Includes bibliographical references (leaves 149-161 ). Online version of the print edition.

The Vanna-Volga (VV) method has been in wide use as one of the major tools for several years among foreign exchange (FX) trading desks. Despite its popularity, the properties of the VV method are not well studied and understood. This thesis attempts to understand better why and when the VV method makes sense, and how to use it better. Often under practical circumstances the state of calibration can be described as being frequent but imperfect. To take advantage of this level of calibration, we studied the properties and benefits of the Karasinski method, and extended this method to a few useful applications. We have found that the Karasinski method, if used with a reasonably calibrated model, can provide significant performance improvement over the VV method.The VV and Karasinski chapters contain most of the original research in this thesis; there are a wealth of discoveries made in these chapters. Novel methods and applications related to the VV and Karasinski methods are proposed, and some of which can be readily applied to the practical trading environment. To make the VV and Karasinski methods work well in practice, the numerical issues for computing the price and Greeks have been carefully addressed with finite difference schemes that are second-order convergent and fast to compute. As an example of easy-to-compute but difficult-to-calibrate model candidates for the Karasinski method, the Multi-Heston model has been discussed too. A sound computational preparation enables the VV and in particular Karasinski methods to enjoy high viability as being fast, efficient and practical. This thesis is tailored to the purpose of making a detailed study on these useful methods whose great potential has not been adequately understood and fully realised.

In this thesis we address problems associated with financial modelling from a Bayesian point of view. Specifically, we look at the problem of calibrating financial models, measuring the model uncertainty of a claim and choosing an optimal hedging strategy. Throughout the study, the local volatility model is used as a working example to clarify the proposed methods. This thesis assumes a prior probability density for the unknown parameter in a model we try to calibrate. The prior probability density regularises the ill-posedness of the calibration problem. Further observations of market prices are used to update this prior, using Bayes law, and give a posterior probability density for the unknown model parameter. Resulting Bayes estimators are shown to be consistent for finite-dimensional model parameters. The posterior density is then used to compute the Bayesian model average price. In tests on local volatility models it is shown that this price is closer than the prices of comparable calibration methods to the price given by the true model. The second part of the thesis focuses on quantifying model uncertainty. Using the framework for market risk measures we propose axioms for new classes of model uncertainty measures. Similar to the market risk case, we prove representation theorems for coherent and convex model uncertainty measures. Example measures from the latter class are provided using the Bayesian posterior. These are used to value the model uncertainty for a range of financial contracts priced in the local volatility model. In the final part of the thesis we propose a method for selecting the model, from a set of candidate models, that optimises the hedging of a specified financial contract. In particular we choose the model whose corresponding price and hedge optimises some hedging performance indicator. The selection problem is solved using Bayesian loss functions to encapsulate the loss from using one model to price and hedge when the true model is a different model. Linkages are made with convex model uncertainty measures and traditional utility functions. Numerical experiments on a stochastic volatility model and the local volatility model show that the Bayesian strategy can outperform traditional strategies, especially for exotic options.

Thesis: Ph.D.--University of Western Sydney, Macarthur.Faculty of Business and Technology. 1998.

Thesis (M.Comm. (Hons.)) -- University of Western Sydney, 2002. / "An empirical study of the project finance risk pricing decision made by Australian project leaders in terms of project finance risk weighting and degree of self-insight" Bibliography : leaves 98-105.

Thesis (Ph.D.)--University of Western Sydney, 2007. / A thesis presented to the University of Western Sydney, College of Business, School of Law, in fulfilment of the requirements for the degree of Doctor of Philosophy. Includes bibliographies.

Thesis (M.A.)--University of Hong Kong, 1991.