This paper describes a set of statistical and graphical tools that can be used to identify statistically valid market signals as arbitrarily complex and smooth functions of one to five indicator variables. By combining local polynomial regression with Newey-West style variance estimators, it is possible to construct valid t-statistic functions that can be used as market timing trading signals or as inputs into larger models. A Windows based statistical and graphical analysis package known as GlassBox is introduced as a feasible way to quickly conduct the type of analysis described in this paper. Given the voluminous output created by high dimensional smoothing methods, the ability to represent and quickly graph 1,000's of data points in a high dimensional space is of critical importance. GlassBox is capable of creating 5-D graphs which can be used to identify highly complex, yet systematic patterns in the data. GlassBox also allows the user to quickly drill down into the data, as a means of identifying levels of smoothness based on conditional 2-D and 3-D plots.
Back