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Expert Trading Systems – John R. Wolberg

About this book

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.

From the Inside Flap

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 a success utility of superior modeling strategies to the improvement of professional buying and selling structures and economic marketplace forecasting fashions calls for each theoretical and realistic information. Wolberg become a pioneer withinside the improvement and alertness of kernel regression modeling to this area, and his ee-e book shows each deep theoretical know-how and realistic information in a particularly readable how-to manner.

Moreover, Wolberg’s superior kernel regression set of rules is orders of significance quicker than current strategies, for this reason broadening its utility tremendously. I particularly advocate this ee-e book to any practitioner on this area. -David Aronson, President, Raden Research Group Inc. Kernel regression is a effective statistical modeling method that offers extremely good overall performance in a huge sort of applications, such as economic marketplace prediction.

Its use has historically been constrained with the aid of using its doubtlessly overwhelming computational requirements, however Wolberg offers an powerful set of rules that speeds computation with the aid of using orders of significance, making it universally available.

-Timothy Masters, writer of Neural, Novel & Hybrid Algorithms for Time Series Prediction This ee-e book gives an extremely good evaluation of nonlinear modeling strategies used to construct predictive fashions for economic time series. It is appropriate each as a textual content for a economic modeling path or for a economic analyst who desires to use kernel strategies for modeling. Wolberg describes his modern technique to dashing up kernel regression, which permits those strategies to be carried out to a greater complicated set of problems. His software program may be used to develop, test, and generate technical buying and selling structures with greater flexibility than different software program this is usually available. -Sandor Straus, PhD, Merfin, LLC, former associate of Renaissance Technology Corp.

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