Tools for Computational Finance offers a clear explanation of computational issues arising in financial mathematics. The new third edition is thoroughly revised and significantly extended, including an extensive new section on analytic methods, focused mainly on interpolation approach and quadratic approximation. Other new material is devoted to risk-neutrality, early-exercise curves, multidimensional Black-Scholes models, the integral representation of options and the derivation of the Black-Scholes equation. New figures, more exercises, and expanded background material make this guide a real must-to-have for everyone working in the world of financial engineering.
Over the last decades the financial markets worldwide underwent tremendous changes, which gave birth to an infinite number of new financial products. Derivatives are the most important innovation with regard to volume that are currently issued on many different underlyings, thus enabling investors to easily buy or sell many different financial products or commodities. This work takes the different aspects of derivatives into account and, after explaining the theoretical background, presents three possible applications for derivatives. First, technical trading methods are applied to intraday futures data, a method which has gained great importance during the last few years. In the next section, a pricing model is developed for profit participation certificates by means of a structural form model. Later, this model is used to price several profit participation certificates traded at the EUWAX in Stuttgart. In the last part, an event study methodology is applied by using implied volatilities to test the influence of a change in a firm's leverage on its risk, as measured by the volatility implied in option prices.
With a wealth of examples and exercises, this is a brand new edition of a classic work on multivariate data analysis. A key advantage of the work is its accessibility. This is because, in its focus on applications, the book presents the tools and concepts of multivariate data analysis in a way that is understandable for non-mathematicians and practitioners who need to analyze statistical data. In this second edition a wider scope of methods and applications of multivariate statistical analysis is introduced. All quantlets have been translated into the R and Matlab language and are made available online.