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Expert Trading Systems: Modeling Financial Markets with Kernel Regression: 89 (Wiley Trading) - Tapa dura
Sinopsis
With the proliferation of computer programs to predict market direction, professional traders and sophisticated individual investors have increasingly turned to mathematical modeling to develop predictive systems. Kernel regression is a popular data modeling technique that can yield useful results fast.
Provides data modeling methodology used to develop trading systems.
* Shows how to design, test, and measure the significance of results
John R. Wolberg (Haifa, Israel) is professor of mechanical engineering at the Haifa Institute in Israel. He does research and consulting in data modeling in the financial services area.
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Acerca del 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.
De la contraportada
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.
De la solapa interior
Expert Trading Systems Investors and traders have long relied upon mathematical models to forecast changes in stock prices and market volatility. Until recently, two distinct approaches to modeling have dominated the field: technical analysis, which focuses on patterns in price data, and fundamental analysis, which considers a broad range of economic variables. Now, however, thanks to the dramatic increase in low-cost computing power, powerful new methods have emerged known as multidimensional nonlinear computer modeling. This book focuses on one of the most important of these new methods, kernel regression, a nonlinear, nonparametric modeling technique that is capable of handling massive amounts of widely diverse data and generating predictions with all the speed and accuracy of the most sophisticated neural networks, using a mere fraction of the computing power. Written by mathematician and computerized trading systems pioneer John Wolberg, Expert Trading Systems is a practical introduction to kernel regression modeling for traders and investors without a background in advanced statistics or applied mathematics. Dr. Wolberg clearly and systematically explains the basic principles of time series forecasting and kernel regression modeling. He then provides step-by-step guidance on how to design, develop, test, and measure the reliability of cutting-edge kernel regression computerized trading systems for trading all financial markets, including the stock, bond, option, futures, and derivative markets. In addition, Dr. Wolberg describes methods for combining kernel regression with neural networks to further enhance the speed and accuracy of a trading program. And he explores various risk management methods, such as combining models to enhance the reward-to-risk ratio. The first practical guide to one of today's most powerful new price and volatility modeling techniques, Expert Trading Systems is a valuable working resource for traders and investors.
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Expert Trading Systems : Modeling Financial Markets with Kernel Regression
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Wiley & Sons, Incorporated, John, 2000
ISBN 10: 0471345083
ISBN 13: 9780471345084
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