|  MAY 1983

Data Filtering Methods For Technical Analysis by ANTHONY WARREN, Ph.D./Technical Analysis

Data Filtering Methods For Technical Analysis by ANTHONY WARREN, Ph.D./Technical Analysis staff writer Data filtering methods such as moving averages are quite prevalent in many trading systems. In this article we will discuss a methodology for selecting appropriate data filters based on Fourier spectrum analysis, and the basics on how to use smoothing filters for trading decisions. In the course of this article we will attempt to familiarize the reader with data filtering from a frequency domain point of view (i.e. cyclic). The reader need not be concerned with the mathematics of Fourier analysis, but should begin to appreciate this methodology as a powerful tool for understanding and applying many trading systems. LINEAR FILTERING: FREQUENCY DOMAIN THEORY Suppose we desire to apply data filtering to time series x(i) i=1...N, such as the stock market daily closes. In general, a linear filter is defined by a fixed set of weights (w(j) j=1...M), where M is the length of the data filter. The output of the filter is a second time series

by Anthony W. Warren, Ph.D.