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Informationen zum Autor JOHN R. WOLBERG, PhD, is a professor of mechanical engineering at the Technion-Israel Institute of Technology in Haifa, Israel. An expert in financial data modeling, he does research and consulting for leading financial institutions, and has worked with some of the pioneers of computerized trading. Dr. Wolberg holds a bachelor's degree in mechanical engineering from Cornell University and a PhD in nuclear engineering from MIT. Klappentext Expert Trading Systems "This book is an excellent introduction to advanced statistical modeling of financial markets. Wolberg's explanation of kernel regression is lucid and direct. The author carefully leads readers through each stage of a trade system design and points out to them any potential difficulties they might encounter along the way. In addition, the examples give a concrete grasp of the subject without getting tangled up in any lengthy mathematical derivation." -Peter F. Borish, President, Computer Trading Corporation "The successful application of advanced modeling methods to the development of expert trading systems and financial market forecasting models requires both theoretical and practical knowledge. Wolberg was a pioneer in the development and application of kernel regression modeling to this area, and his book displays both deep theoretical understanding and practical knowledge in a highly readable how-to manner. Moreover, Wolberg's advanced kernel regression algorithm is orders of magnitude faster than existing methods, thus broadening its application tremendously. I highly recommend this book to any practitioner in this area." -David Aronson, President, Raden Research Group Inc. "Kernel regression is a powerful statistical modeling technique that gives excellent performance in a wide variety of applications, including financial market prediction. Its use has traditionally been limited by its potentially overwhelming computational requirements, but Wolberg provides an effective algorithm that speeds computation by orders of magnitude, making it universally available." -Timothy Masters, author of Neural, Novel & Hybrid Algorithms for Time Series Prediction "This book presents an excellent overview of nonlinear modeling techniques used to build predictive models for financial time series. It is suitable both as a text for a financial modeling course or for a financial analyst who wants to use kernel methods for modeling. Wolberg describes his innovative approach to speeding up kernel regression, which allows these methods to be applied to a more complex set of problems. His software can be used to develop, test, and generate technical trading systems with more flexibility than other software that is commonly available." -Sandor Straus, PhD, Merfin, LLC, former partner of Renaissance Technology Corp. Zusammenfassung Mittlerweile gibt es eine regelrechte Flut von Computerprogrammen, mit deren Hilfe man die Richtung der Marktentwicklung vorhersagen kann. Deshalb greifen immer mehr professionelle Händler und versierte Privatanleger zu mathematischen Modellen, um Prognosesysteme zu entwickeln. Die Kernel Regression ist eine beliebte Technik zur Erstellung von Datenmodellen, die rasch zu brauchbaren Ergebnissen führt. Dieses Buch führt Sie ein in die Methodik zur Erstellung von Datenmodellen, die für die Entwicklung von Handelssystemen wichtig sind. Darüber hinaus wird detailliert erläutert, wie man die Bedeutung der erzielten Ergebnisse bestimmt und bewertet. Inhaltsverzeichnis Data Modeling of Time Series. Kernel Regression. High-Performance Kernel Regression. Kernel Regression Software Performance. Modeling Strategies. Creating Trading Systems. Appendices. Bibliography. Index....
