An application of genetic programming to investment system optimization
Charles E. Smith · 1999
The Ned Davis Research Evolutionary Optimizer (NEO) is a tool that performs genetic programming optimization of quantitative investment systems. It selects combinations of commands, arguments, and parameters that form nearly optimal programs for investment timing or asset allocation. The primary inputs to NEO are a set of market or economic data series and a template that limits the types of code that can be generated. The output is a program (in NDR's proprietary language Technalyzer) that provides investment timing signals or asset allocation recommendations.