Expert Trading Systems Modeling Financial Markets with Kernel Regression [Hardcover]

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.Data Modeling of Time Series.

Kernel Regression.

High-Performance Kernel Regression.

Kernel Regression Software Performance.

Modeling Strategies.

Creating Trading Systems.

Appendices.

Bibliography.

Index.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.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 mlÃ9